• Minecraft Players Are Amazed by One Small Recent Change

    Some Minecraft players are amazed by how realistic deep water looks in the popular sandbox game after the recent Vibrant Visuals update. Minecraft always had a charming aesthetic, but this recent update really improved the game’s visuals, surprising long-time fans.
    #minecraft #players #are #amazed #one
    Minecraft Players Are Amazed by One Small Recent Change
    Some Minecraft players are amazed by how realistic deep water looks in the popular sandbox game after the recent Vibrant Visuals update. Minecraft always had a charming aesthetic, but this recent update really improved the game’s visuals, surprising long-time fans. #minecraft #players #are #amazed #one
    GAMERANT.COM
    Minecraft Players Are Amazed by One Small Recent Change
    Some Minecraft players are amazed by how realistic deep water looks in the popular sandbox game after the recent Vibrant Visuals update. Minecraft always had a charming aesthetic, but this recent update really improved the game’s visuals, surprising long-time fans.
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  • BOUNCING FROM RUBBER DUCKIES AND FLYING SHEEP TO CLONES FOR THE BOYS SEASON 4

    By TREVOR HOGG
    Images courtesy of Prime Video.

    For those seeking an alternative to the MCU, Prime Video has two offerings of the live-action and animated variety that take the superhero genre into R-rated territory where the hands of the god-like figures get dirty, bloodied and severed. “The Boys is about the intersection of celebrity and politics using superheroes,” states Stephan Fleet, VFX Supervisor on The Boys. “Sometimes I see the news and I don’t even know we can write to catch up to it! But we try. Invincible is an intense look at an alternate DC Universe that has more grit to the superhero side of it all. On one hand, I was jealous watching Season 1 of Invincible because in animation you can do things that you can’t do in real life on a budget.” Season 4 does not tone down the blood, gore and body count. Fleet notes, “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!”

    When Splintersplits in two, the cloning effect was inspired by cellular mitosis.

    “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!”
    —Stephan Fleet, VFX Supervisor

    A total of 1,600 visual effects shots were created for the eight episodes by ILM, Pixomondo, MPC Toronto, Spin VFX, DNEG, Untold Studios, Luma Pictures and Rocket Science VFX. Previs was a critical part of the process. “We have John Griffith, who owns a small company called CNCPT out of Texas, and he does wonderful Unreal Engine level previs,” Fleet remarks. “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” Founding Director of Federal Bureau of Superhuman Affairs, Victoria Neuman, literally gets ripped in half by two tendrils coming out of Compound V-enhanced Billy Butcher, the leader of superhero resistance group The Boys. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.”

    Multiple plates were shot to enable Simon Pegg to phase through the actor laying in a hospital bed.

    Testing can get rather elaborate. “For that end scene with Butcher’s tendrils, the room was two stories, and we were able to put the camera up high along with a bunch of blood cannons,” Fleet recalls. “When the body rips in half and explodes, there is a practical component. We rained down a bunch of real blood and guts right in front of Huey. It’s a known joke that we like to douse Jack Quaid with blood as much as possible! In this case, the special effects team led by Hudson Kenny needed to test it the day before, and I said, “I’ll be the guinea pig for the test.’ They covered the whole place with plastic like it was a Dexter kill room because you don’t want to destroy the set. I’m standing there in a white hazmat suit with goggles on, covered from head to toe in plastic and waiting as they’re tweaking all of these things. It sounds like World War II going on. They’re on walkie talkies to each other, and then all of a sudden, it’s ‘Five, four, three, two, one…’  And I get exploded with blood. I wanted to see what it was like, and it’s intense.”

    “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.”
    —Stephan Fleet, VFX Supervisor

    The Deep has a love affair with an octopus called Ambrosius, voiced by Tilda Swinton. “It’s implied bestiality!” Fleet laughs. “I would call it more of a romance. What was fun from my perspective is that I knew what the look was going to be, so then it’s about putting in the details and the animation. One of the instincts that you always have when you’re making a sea creature that talks to a humanyou tend to want to give it human gestures and eyebrows. Erik Kripkesaid, ‘No. We have to find things that an octopus could do that conveys the same emotion.’ That’s when ideas came in, such as putting a little The Deep toy inside the water tank. When Ambrosius is trying to have an intimate moment or connect with him, she can wrap a tentacle around that. My favorite experience doing Ambrosius was when The Deep is reading poetry to her on a bed. CG creatures touching humans is one of the more complicated things to do and make look real. Ambrosius’ tentacles reach for his arm, and it becomes an intimate moment. More than touching the skin, displacing the bedsheet as Ambrosius moved ended up becoming a lot of CG, and we had to go back and forth a few times to get that looking right; that turned out to be tricky.”

    A building is replaced by a massive crowd attending a rally being held by Homelander.

    In a twisted form of sexual foreplay, Sister Sage has The Deep perform a transorbital lobotomy on her. “Thank you, Amazon for selling lobotomy tools as novelty items!” Fleet chuckles. “We filmed it with a lobotomy tool on set. There is a lot of safety involved in doing something like that. Obviously, you don’t want to put any performer in any situation where they come close to putting anything real near their eye. We created this half lobotomy tool and did this complicated split screen with the lobotomy tool on a teeter totter. The Deep wasin one shot and Sister Sage reacted in the other shot. To marry the two ended up being a lot of CG work. Then there are these close-ups which are full CG. I always keep a dummy head that is painted gray that I use all of the time for reference. In macrophotography I filmed this lobotomy tool going right into the eye area. I did that because the tool is chrome, so it’s reflective and has ridges. It has an interesting reflective property. I was able to see how and what part of the human eye reflects onto the tool. A lot of that shot became about realistic reflections and lighting on the tool. Then heavy CG for displacing the eye and pushing the lobotomy tool into it. That was one of the more complicated sequences that we had to achieve.”

    In order to create an intimate moment between Ambrosius and The Deep, a toy version of the superhero was placed inside of the water tank that she could wrap a tentacle around.

    “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.”
    —Stephan Fleet, VFX Supervisor

    Sheep and chickens embark on a violent rampage courtesy of Compound V with the latter piercing the chest of a bodyguard belonging to Victoria Neuman. “Weirdly, that was one of our more traditional shots,’ Fleet states. “What is fun about that one is I asked for real chickens as reference. The chicken flying through his chest is real. It’s our chicken wrangler in green suit gently tossing a chicken. We blended two real plates together with some CG in the middle.” A connection was made with a sci-fi classic. “The sheep kill this bull, and we shot it is in this narrow corridor of fencing. When they run, I always equated it as the Trench Run in Star Wars and looked at the sheep as TIE fighters or X-wings coming at them.” The scene was one of the scarier moments for the visual effects team. Fleet explains, “When I read the script, I thought this could be the moment where we jump the shark. For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.”

    The sheep injected with Compound V develop the ability to fly and were shot in an imperfect manner to help ground the scenes.

    Once injected with Compound V, Hugh Campbell Sr.develops the ability to phase through objects, including human beings. “We called it the Bro-nut because his name in the script is Wall Street Bro,” Fleet notes. “That was a complicated motion control shot, repeating the move over and over again. We had to shoot multiple plates of Simon Pegg and the guy in the bed. Special effects and prosthetics created a dummy guy with a hole in his chest with practical blood dripping down. It was meshing it together and getting the timing right in post. On top of that, there was the CG blood immediately around Simon Pegg.” The phasing effect had to avoid appearing as a dissolve. “I had this idea of doing high-frequency vibration on the X axis loosely based on how The Flash vibrates through walls. You want everything to have a loose motivation that then helps trigger the visuals. We tried not to overcomplicate that because, ultimately, you want something like that to be quick. If you spend too much time on phasing, it can look cheesy. In our case, it was a lot of false walls. Simon Pegg is running into a greenscreen hole which we plug in with a wall or coming out of one. I went off the actor’s action, and we added a light opacity mix with some X-axis shake.”

    Providing a different twist to the fights was the replacement of spurting blood with photoreal rubber duckies during a drug-induced hallucination.

    Homelanderbreaks a mirror which emphasizes his multiple personality disorder. “The original plan was that special effects was going to pre-break a mirror, and we were going to shoot Anthony Starr moving his head doing all of the performances in the different parts of the mirror,” Fleet reveals. “This was all based on a photo that my ex-brother-in-law sent me. He was walking down a street in Glendale, California, came across a broken mirror that someone had thrown out, and took a photo of himself where he had five heads in the mirror. We get there on the day, and I’m realizing that this is really complicated. Anthony has to do these five different performances, and we have to deal with infinite mirrors. At the last minute, I said, ‘We have to do this on a clean mirror.’ We did it on a clear mirror and gave Anthony different eyelines. The mirror break was all done in post, and we were able to cheat his head slightly and art-direct where the break crosses his chin. Editorial was able to do split screens for the timing of the dialogue.”

    “For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.”
    —Stephan Fleet, VFX Supervisor

    Initially, the plan was to use a practical mirror, but creating a digital version proved to be the more effective solution.

    A different spin on the bloodbath occurs during a fight when a drugged Frenchiehallucinates as Kimiko Miyashirogoes on a killing spree. “We went back and forth with a lot of different concepts for what this hallucination would be,” Fleet remarks. “When we filmed it, we landed on Frenchie having a synesthesia moment where he’s seeing a lot of abstract colors flying in the air. We started getting into that in post and it wasn’t working. We went back to the rubber duckies, which goes back to the story of him in the bathtub. What’s in the bathtub? Rubber duckies, bubbles and water. There was a lot of physics and logic required to figure out how these rubber duckies could float out of someone’s neck. We decided on bubbles when Kimiko hits people’s heads. At one point, we had water when she got shot, but it wasn’t working, so we killed it. We probably did about 100 different versions. We got really detailed with our rubber duckie modeling because we didn’t want it to look cartoony. That took a long time.”

    Ambrosius, voiced by Tilda Swinton, gets a lot more screentime in Season 4.

    When Splintersplits in two was achieved heavily in CG. “Erik threw out the words ‘cellular mitosis’ early on as something he wanted to use,” Fleet states. “We shot Rob Benedict on a greenscreen doing all of the different performances for the clones that pop out. It was a crazy amount of CG work with Houdini and particle and skin effects. We previs’d the sequence so we had specific actions. One clone comes out to the right and the other pulls backwards.” What tends to go unnoticed by many is Splinter’s clones setting up for a press conference being held by Firecracker. “It’s funny how no one brings up the 22-hour motion control shot that we had to do with Splinter on the stage, which was the most complicated shot!” Fleet observes. “We have this sweeping long shot that brings you into the room and follows Splinter as he carries a container to the stage and hands it off to a clone, and then you reveal five more of them interweaving each other and interacting with all of these objects. It’s like a minute-long dance. First off, you have to choreograph it. We previs’d it, but then you need to get people to do it. We hired dancers and put different colored armbands on them. The camera is like another performer, and a metronome is going, which enables you to find a pace. That took about eight hours of rehearsal. Then Rob has to watch each one of their performances and mimic it to the beat. When he is handing off a box of cables, it’s to a double who is going to have to be erased and be him on the other side. They have to be almost perfect in their timing and lineup in order to take it over in visual effects and make it work.”
    #bouncing #rubber #duckies #flying #sheep
    BOUNCING FROM RUBBER DUCKIES AND FLYING SHEEP TO CLONES FOR THE BOYS SEASON 4
    By TREVOR HOGG Images courtesy of Prime Video. For those seeking an alternative to the MCU, Prime Video has two offerings of the live-action and animated variety that take the superhero genre into R-rated territory where the hands of the god-like figures get dirty, bloodied and severed. “The Boys is about the intersection of celebrity and politics using superheroes,” states Stephan Fleet, VFX Supervisor on The Boys. “Sometimes I see the news and I don’t even know we can write to catch up to it! But we try. Invincible is an intense look at an alternate DC Universe that has more grit to the superhero side of it all. On one hand, I was jealous watching Season 1 of Invincible because in animation you can do things that you can’t do in real life on a budget.” Season 4 does not tone down the blood, gore and body count. Fleet notes, “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” When Splintersplits in two, the cloning effect was inspired by cellular mitosis. “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” —Stephan Fleet, VFX Supervisor A total of 1,600 visual effects shots were created for the eight episodes by ILM, Pixomondo, MPC Toronto, Spin VFX, DNEG, Untold Studios, Luma Pictures and Rocket Science VFX. Previs was a critical part of the process. “We have John Griffith, who owns a small company called CNCPT out of Texas, and he does wonderful Unreal Engine level previs,” Fleet remarks. “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” Founding Director of Federal Bureau of Superhuman Affairs, Victoria Neuman, literally gets ripped in half by two tendrils coming out of Compound V-enhanced Billy Butcher, the leader of superhero resistance group The Boys. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” Multiple plates were shot to enable Simon Pegg to phase through the actor laying in a hospital bed. Testing can get rather elaborate. “For that end scene with Butcher’s tendrils, the room was two stories, and we were able to put the camera up high along with a bunch of blood cannons,” Fleet recalls. “When the body rips in half and explodes, there is a practical component. We rained down a bunch of real blood and guts right in front of Huey. It’s a known joke that we like to douse Jack Quaid with blood as much as possible! In this case, the special effects team led by Hudson Kenny needed to test it the day before, and I said, “I’ll be the guinea pig for the test.’ They covered the whole place with plastic like it was a Dexter kill room because you don’t want to destroy the set. I’m standing there in a white hazmat suit with goggles on, covered from head to toe in plastic and waiting as they’re tweaking all of these things. It sounds like World War II going on. They’re on walkie talkies to each other, and then all of a sudden, it’s ‘Five, four, three, two, one…’  And I get exploded with blood. I wanted to see what it was like, and it’s intense.” “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” —Stephan Fleet, VFX Supervisor The Deep has a love affair with an octopus called Ambrosius, voiced by Tilda Swinton. “It’s implied bestiality!” Fleet laughs. “I would call it more of a romance. What was fun from my perspective is that I knew what the look was going to be, so then it’s about putting in the details and the animation. One of the instincts that you always have when you’re making a sea creature that talks to a humanyou tend to want to give it human gestures and eyebrows. Erik Kripkesaid, ‘No. We have to find things that an octopus could do that conveys the same emotion.’ That’s when ideas came in, such as putting a little The Deep toy inside the water tank. When Ambrosius is trying to have an intimate moment or connect with him, she can wrap a tentacle around that. My favorite experience doing Ambrosius was when The Deep is reading poetry to her on a bed. CG creatures touching humans is one of the more complicated things to do and make look real. Ambrosius’ tentacles reach for his arm, and it becomes an intimate moment. More than touching the skin, displacing the bedsheet as Ambrosius moved ended up becoming a lot of CG, and we had to go back and forth a few times to get that looking right; that turned out to be tricky.” A building is replaced by a massive crowd attending a rally being held by Homelander. In a twisted form of sexual foreplay, Sister Sage has The Deep perform a transorbital lobotomy on her. “Thank you, Amazon for selling lobotomy tools as novelty items!” Fleet chuckles. “We filmed it with a lobotomy tool on set. There is a lot of safety involved in doing something like that. Obviously, you don’t want to put any performer in any situation where they come close to putting anything real near their eye. We created this half lobotomy tool and did this complicated split screen with the lobotomy tool on a teeter totter. The Deep wasin one shot and Sister Sage reacted in the other shot. To marry the two ended up being a lot of CG work. Then there are these close-ups which are full CG. I always keep a dummy head that is painted gray that I use all of the time for reference. In macrophotography I filmed this lobotomy tool going right into the eye area. I did that because the tool is chrome, so it’s reflective and has ridges. It has an interesting reflective property. I was able to see how and what part of the human eye reflects onto the tool. A lot of that shot became about realistic reflections and lighting on the tool. Then heavy CG for displacing the eye and pushing the lobotomy tool into it. That was one of the more complicated sequences that we had to achieve.” In order to create an intimate moment between Ambrosius and The Deep, a toy version of the superhero was placed inside of the water tank that she could wrap a tentacle around. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” —Stephan Fleet, VFX Supervisor Sheep and chickens embark on a violent rampage courtesy of Compound V with the latter piercing the chest of a bodyguard belonging to Victoria Neuman. “Weirdly, that was one of our more traditional shots,’ Fleet states. “What is fun about that one is I asked for real chickens as reference. The chicken flying through his chest is real. It’s our chicken wrangler in green suit gently tossing a chicken. We blended two real plates together with some CG in the middle.” A connection was made with a sci-fi classic. “The sheep kill this bull, and we shot it is in this narrow corridor of fencing. When they run, I always equated it as the Trench Run in Star Wars and looked at the sheep as TIE fighters or X-wings coming at them.” The scene was one of the scarier moments for the visual effects team. Fleet explains, “When I read the script, I thought this could be the moment where we jump the shark. For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” The sheep injected with Compound V develop the ability to fly and were shot in an imperfect manner to help ground the scenes. Once injected with Compound V, Hugh Campbell Sr.develops the ability to phase through objects, including human beings. “We called it the Bro-nut because his name in the script is Wall Street Bro,” Fleet notes. “That was a complicated motion control shot, repeating the move over and over again. We had to shoot multiple plates of Simon Pegg and the guy in the bed. Special effects and prosthetics created a dummy guy with a hole in his chest with practical blood dripping down. It was meshing it together and getting the timing right in post. On top of that, there was the CG blood immediately around Simon Pegg.” The phasing effect had to avoid appearing as a dissolve. “I had this idea of doing high-frequency vibration on the X axis loosely based on how The Flash vibrates through walls. You want everything to have a loose motivation that then helps trigger the visuals. We tried not to overcomplicate that because, ultimately, you want something like that to be quick. If you spend too much time on phasing, it can look cheesy. In our case, it was a lot of false walls. Simon Pegg is running into a greenscreen hole which we plug in with a wall or coming out of one. I went off the actor’s action, and we added a light opacity mix with some X-axis shake.” Providing a different twist to the fights was the replacement of spurting blood with photoreal rubber duckies during a drug-induced hallucination. Homelanderbreaks a mirror which emphasizes his multiple personality disorder. “The original plan was that special effects was going to pre-break a mirror, and we were going to shoot Anthony Starr moving his head doing all of the performances in the different parts of the mirror,” Fleet reveals. “This was all based on a photo that my ex-brother-in-law sent me. He was walking down a street in Glendale, California, came across a broken mirror that someone had thrown out, and took a photo of himself where he had five heads in the mirror. We get there on the day, and I’m realizing that this is really complicated. Anthony has to do these five different performances, and we have to deal with infinite mirrors. At the last minute, I said, ‘We have to do this on a clean mirror.’ We did it on a clear mirror and gave Anthony different eyelines. The mirror break was all done in post, and we were able to cheat his head slightly and art-direct where the break crosses his chin. Editorial was able to do split screens for the timing of the dialogue.” “For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” —Stephan Fleet, VFX Supervisor Initially, the plan was to use a practical mirror, but creating a digital version proved to be the more effective solution. A different spin on the bloodbath occurs during a fight when a drugged Frenchiehallucinates as Kimiko Miyashirogoes on a killing spree. “We went back and forth with a lot of different concepts for what this hallucination would be,” Fleet remarks. “When we filmed it, we landed on Frenchie having a synesthesia moment where he’s seeing a lot of abstract colors flying in the air. We started getting into that in post and it wasn’t working. We went back to the rubber duckies, which goes back to the story of him in the bathtub. What’s in the bathtub? Rubber duckies, bubbles and water. There was a lot of physics and logic required to figure out how these rubber duckies could float out of someone’s neck. We decided on bubbles when Kimiko hits people’s heads. At one point, we had water when she got shot, but it wasn’t working, so we killed it. We probably did about 100 different versions. We got really detailed with our rubber duckie modeling because we didn’t want it to look cartoony. That took a long time.” Ambrosius, voiced by Tilda Swinton, gets a lot more screentime in Season 4. When Splintersplits in two was achieved heavily in CG. “Erik threw out the words ‘cellular mitosis’ early on as something he wanted to use,” Fleet states. “We shot Rob Benedict on a greenscreen doing all of the different performances for the clones that pop out. It was a crazy amount of CG work with Houdini and particle and skin effects. We previs’d the sequence so we had specific actions. One clone comes out to the right and the other pulls backwards.” What tends to go unnoticed by many is Splinter’s clones setting up for a press conference being held by Firecracker. “It’s funny how no one brings up the 22-hour motion control shot that we had to do with Splinter on the stage, which was the most complicated shot!” Fleet observes. “We have this sweeping long shot that brings you into the room and follows Splinter as he carries a container to the stage and hands it off to a clone, and then you reveal five more of them interweaving each other and interacting with all of these objects. It’s like a minute-long dance. First off, you have to choreograph it. We previs’d it, but then you need to get people to do it. We hired dancers and put different colored armbands on them. The camera is like another performer, and a metronome is going, which enables you to find a pace. That took about eight hours of rehearsal. Then Rob has to watch each one of their performances and mimic it to the beat. When he is handing off a box of cables, it’s to a double who is going to have to be erased and be him on the other side. They have to be almost perfect in their timing and lineup in order to take it over in visual effects and make it work.” #bouncing #rubber #duckies #flying #sheep
    WWW.VFXVOICE.COM
    BOUNCING FROM RUBBER DUCKIES AND FLYING SHEEP TO CLONES FOR THE BOYS SEASON 4
    By TREVOR HOGG Images courtesy of Prime Video. For those seeking an alternative to the MCU, Prime Video has two offerings of the live-action and animated variety that take the superhero genre into R-rated territory where the hands of the god-like figures get dirty, bloodied and severed. “The Boys is about the intersection of celebrity and politics using superheroes,” states Stephan Fleet, VFX Supervisor on The Boys. “Sometimes I see the news and I don’t even know we can write to catch up to it! But we try. Invincible is an intense look at an alternate DC Universe that has more grit to the superhero side of it all. On one hand, I was jealous watching Season 1 of Invincible because in animation you can do things that you can’t do in real life on a budget.” Season 4 does not tone down the blood, gore and body count. Fleet notes, “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” When Splinter (Rob Benedict) splits in two, the cloning effect was inspired by cellular mitosis. “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” —Stephan Fleet, VFX Supervisor A total of 1,600 visual effects shots were created for the eight episodes by ILM, Pixomondo, MPC Toronto, Spin VFX, DNEG, Untold Studios, Luma Pictures and Rocket Science VFX. Previs was a critical part of the process. “We have John Griffith [Previs Director], who owns a small company called CNCPT out of Texas, and he does wonderful Unreal Engine level previs,” Fleet remarks. “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” Founding Director of Federal Bureau of Superhuman Affairs, Victoria Neuman, literally gets ripped in half by two tendrils coming out of Compound V-enhanced Billy Butcher, the leader of superhero resistance group The Boys. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” Multiple plates were shot to enable Simon Pegg to phase through the actor laying in a hospital bed. Testing can get rather elaborate. “For that end scene with Butcher’s tendrils, the room was two stories, and we were able to put the camera up high along with a bunch of blood cannons,” Fleet recalls. “When the body rips in half and explodes, there is a practical component. We rained down a bunch of real blood and guts right in front of Huey. It’s a known joke that we like to douse Jack Quaid with blood as much as possible! In this case, the special effects team led by Hudson Kenny needed to test it the day before, and I said, “I’ll be the guinea pig for the test.’ They covered the whole place with plastic like it was a Dexter kill room because you don’t want to destroy the set. I’m standing there in a white hazmat suit with goggles on, covered from head to toe in plastic and waiting as they’re tweaking all of these things. It sounds like World War II going on. They’re on walkie talkies to each other, and then all of a sudden, it’s ‘Five, four, three, two, one…’  And I get exploded with blood. I wanted to see what it was like, and it’s intense.” “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” —Stephan Fleet, VFX Supervisor The Deep has a love affair with an octopus called Ambrosius, voiced by Tilda Swinton. “It’s implied bestiality!” Fleet laughs. “I would call it more of a romance. What was fun from my perspective is that I knew what the look was going to be [from Season 3], so then it’s about putting in the details and the animation. One of the instincts that you always have when you’re making a sea creature that talks to a human [is] you tend to want to give it human gestures and eyebrows. Erik Kripke [Creator, Executive Producer, Showrunner, Director, Writer] said, ‘No. We have to find things that an octopus could do that conveys the same emotion.’ That’s when ideas came in, such as putting a little The Deep toy inside the water tank. When Ambrosius is trying to have an intimate moment or connect with him, she can wrap a tentacle around that. My favorite experience doing Ambrosius was when The Deep is reading poetry to her on a bed. CG creatures touching humans is one of the more complicated things to do and make look real. Ambrosius’ tentacles reach for his arm, and it becomes an intimate moment. More than touching the skin, displacing the bedsheet as Ambrosius moved ended up becoming a lot of CG, and we had to go back and forth a few times to get that looking right; that turned out to be tricky.” A building is replaced by a massive crowd attending a rally being held by Homelander. In a twisted form of sexual foreplay, Sister Sage has The Deep perform a transorbital lobotomy on her. “Thank you, Amazon for selling lobotomy tools as novelty items!” Fleet chuckles. “We filmed it with a lobotomy tool on set. There is a lot of safety involved in doing something like that. Obviously, you don’t want to put any performer in any situation where they come close to putting anything real near their eye. We created this half lobotomy tool and did this complicated split screen with the lobotomy tool on a teeter totter. The Deep was [acting in a certain way] in one shot and Sister Sage reacted in the other shot. To marry the two ended up being a lot of CG work. Then there are these close-ups which are full CG. I always keep a dummy head that is painted gray that I use all of the time for reference. In macrophotography I filmed this lobotomy tool going right into the eye area. I did that because the tool is chrome, so it’s reflective and has ridges. It has an interesting reflective property. I was able to see how and what part of the human eye reflects onto the tool. A lot of that shot became about realistic reflections and lighting on the tool. Then heavy CG for displacing the eye and pushing the lobotomy tool into it. That was one of the more complicated sequences that we had to achieve.” In order to create an intimate moment between Ambrosius and The Deep, a toy version of the superhero was placed inside of the water tank that she could wrap a tentacle around. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” —Stephan Fleet, VFX Supervisor Sheep and chickens embark on a violent rampage courtesy of Compound V with the latter piercing the chest of a bodyguard belonging to Victoria Neuman. “Weirdly, that was one of our more traditional shots,’ Fleet states. “What is fun about that one is I asked for real chickens as reference. The chicken flying through his chest is real. It’s our chicken wrangler in green suit gently tossing a chicken. We blended two real plates together with some CG in the middle.” A connection was made with a sci-fi classic. “The sheep kill this bull, and we shot it is in this narrow corridor of fencing. When they run, I always equated it as the Trench Run in Star Wars and looked at the sheep as TIE fighters or X-wings coming at them.” The scene was one of the scarier moments for the visual effects team. Fleet explains, “When I read the script, I thought this could be the moment where we jump the shark. For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” The sheep injected with Compound V develop the ability to fly and were shot in an imperfect manner to help ground the scenes. Once injected with Compound V, Hugh Campbell Sr. (Simon Pegg) develops the ability to phase through objects, including human beings. “We called it the Bro-nut because his name in the script is Wall Street Bro,” Fleet notes. “That was a complicated motion control shot, repeating the move over and over again. We had to shoot multiple plates of Simon Pegg and the guy in the bed. Special effects and prosthetics created a dummy guy with a hole in his chest with practical blood dripping down. It was meshing it together and getting the timing right in post. On top of that, there was the CG blood immediately around Simon Pegg.” The phasing effect had to avoid appearing as a dissolve. “I had this idea of doing high-frequency vibration on the X axis loosely based on how The Flash vibrates through walls. You want everything to have a loose motivation that then helps trigger the visuals. We tried not to overcomplicate that because, ultimately, you want something like that to be quick. If you spend too much time on phasing, it can look cheesy. In our case, it was a lot of false walls. Simon Pegg is running into a greenscreen hole which we plug in with a wall or coming out of one. I went off the actor’s action, and we added a light opacity mix with some X-axis shake.” Providing a different twist to the fights was the replacement of spurting blood with photoreal rubber duckies during a drug-induced hallucination. Homelander (Anthony Starr) breaks a mirror which emphasizes his multiple personality disorder. “The original plan was that special effects was going to pre-break a mirror, and we were going to shoot Anthony Starr moving his head doing all of the performances in the different parts of the mirror,” Fleet reveals. “This was all based on a photo that my ex-brother-in-law sent me. He was walking down a street in Glendale, California, came across a broken mirror that someone had thrown out, and took a photo of himself where he had five heads in the mirror. We get there on the day, and I’m realizing that this is really complicated. Anthony has to do these five different performances, and we have to deal with infinite mirrors. At the last minute, I said, ‘We have to do this on a clean mirror.’ We did it on a clear mirror and gave Anthony different eyelines. The mirror break was all done in post, and we were able to cheat his head slightly and art-direct where the break crosses his chin. Editorial was able to do split screens for the timing of the dialogue.” “For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” —Stephan Fleet, VFX Supervisor Initially, the plan was to use a practical mirror, but creating a digital version proved to be the more effective solution. A different spin on the bloodbath occurs during a fight when a drugged Frenchie (Tomer Capone) hallucinates as Kimiko Miyashiro (Karen Fukuhara) goes on a killing spree. “We went back and forth with a lot of different concepts for what this hallucination would be,” Fleet remarks. “When we filmed it, we landed on Frenchie having a synesthesia moment where he’s seeing a lot of abstract colors flying in the air. We started getting into that in post and it wasn’t working. We went back to the rubber duckies, which goes back to the story of him in the bathtub. What’s in the bathtub? Rubber duckies, bubbles and water. There was a lot of physics and logic required to figure out how these rubber duckies could float out of someone’s neck. We decided on bubbles when Kimiko hits people’s heads. At one point, we had water when she got shot, but it wasn’t working, so we killed it. We probably did about 100 different versions. We got really detailed with our rubber duckie modeling because we didn’t want it to look cartoony. That took a long time.” Ambrosius, voiced by Tilda Swinton, gets a lot more screentime in Season 4. When Splinter (Rob Benedict) splits in two was achieved heavily in CG. “Erik threw out the words ‘cellular mitosis’ early on as something he wanted to use,” Fleet states. “We shot Rob Benedict on a greenscreen doing all of the different performances for the clones that pop out. It was a crazy amount of CG work with Houdini and particle and skin effects. We previs’d the sequence so we had specific actions. One clone comes out to the right and the other pulls backwards.” What tends to go unnoticed by many is Splinter’s clones setting up for a press conference being held by Firecracker (Valorie Curry). “It’s funny how no one brings up the 22-hour motion control shot that we had to do with Splinter on the stage, which was the most complicated shot!” Fleet observes. “We have this sweeping long shot that brings you into the room and follows Splinter as he carries a container to the stage and hands it off to a clone, and then you reveal five more of them interweaving each other and interacting with all of these objects. It’s like a minute-long dance. First off, you have to choreograph it. We previs’d it, but then you need to get people to do it. We hired dancers and put different colored armbands on them. The camera is like another performer, and a metronome is going, which enables you to find a pace. That took about eight hours of rehearsal. Then Rob has to watch each one of their performances and mimic it to the beat. When he is handing off a box of cables, it’s to a double who is going to have to be erased and be him on the other side. They have to be almost perfect in their timing and lineup in order to take it over in visual effects and make it work.”
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  • Hey everyone! Are you ready to unleash your creativity? Today, I want to share a fantastic tip from John R. Nyquist's new tutorial: Text Inside a Circle! Using Blender's Pen tool, you can create stunning 2D art that will amaze your friends and elevate your projects!

    With Blender 4.4, the possibilities are endless! Dive into the world of design with the Grease Pencil and watch your ideas come to life! Remember, every masterpiece starts with a simple sketch. So let's get inspired and create something beautiful together!

    #BlenderTips #CreativeJourney #2DArt #Inspiration #BlenderCommunity
    🌟 Hey everyone! Are you ready to unleash your creativity? 🎨✨ Today, I want to share a fantastic tip from John R. Nyquist's new tutorial: Text Inside a Circle! Using Blender's Pen tool, you can create stunning 2D art that will amaze your friends and elevate your projects! 🖌️💫 With Blender 4.4, the possibilities are endless! Dive into the world of design with the Grease Pencil and watch your ideas come to life! Remember, every masterpiece starts with a simple sketch. 🌈 So let's get inspired and create something beautiful together! 💖 #BlenderTips #CreativeJourney #2DArt #Inspiration #BlenderCommunity
    Quick Tip: Text Inside a Circle
    Learn a useful trick with Blender's Pen tool with this new tutorial by John R. Nyquist. For the new Bits of Blender logo (my series of quick tips and tutorials for the Blender community), I used Blender 4.4 to create the 2D art. I began with thumbnai
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  • In the depths of my solitude, I often find myself reflecting on the works of Maurits Escher, the master of impossible illusions. His art, a blend of reality and impossibility, echoes the very essence of my own existence. Like the infinite staircases that lead nowhere, I feel trapped in an unending loop, where my heart yearns for connection but finds only shadows and silence.

    Each piece Escher created seems to whisper the tragedies of my own life—layers of beauty intertwined with the harshness of reality. How can something so captivating feel so isolating? Just as Escher's designs defy logic and reason, my emotions twist and turn, leaving me in a maze of longing and despair. The world outside continues to spin, yet I am frozen in a moment where joy feels like a distant memory, an illusion I can never quite grasp.

    It’s painful to witness the laughter and happiness of others while I remain ensnared in this solitude. I watch as life unfolds in vibrant colors around me, while I sit in monochrome, a silent observer of a reality I can’t seem to touch. Relationships become intricate puzzles, beautiful yet impossible to solve, leaving me feeling more alone than ever. Just like Escher’s art, which captivates yet confounds, I find myself caught in the paradox of wanting to connect but fearing the inevitable disappointment that follows.

    In moments of despair, I seek solace within the lines and curves of Escher's work, each piece a poignant reminder of the beauty that can exist alongside pain. It’s a bittersweet comfort, knowing that others have created worlds that defy the ordinary, yet it also amplifies my sense of isolation. To be a dreamer in a world that feels so unattainable is a heavy burden to bear. I am trapped in my own impossible illusion, yearning for the day when the world will feel a little less distant and a little more like home.

    As I traverse this winding path of existence, I am left to ponder: is it possible to find solace in the impossible? Can I transform my heartache into something beautiful, akin to Escher's masterpieces? Or will I remain just another fleeting thought in a world full of intricate designs that I can only admire from afar?

    In the end, I am just a lost soul, hoping that one day I will break free from this illusion of the impossible and find a place where I truly belong. Until then, I will continue to search for meaning in the chaos, just like Escher, who saw potential in the impossible.

    #Isolation #Heartache #Escher #Illusion #ArtandLife
    In the depths of my solitude, I often find myself reflecting on the works of Maurits Escher, the master of impossible illusions. His art, a blend of reality and impossibility, echoes the very essence of my own existence. Like the infinite staircases that lead nowhere, I feel trapped in an unending loop, where my heart yearns for connection but finds only shadows and silence. 💔 Each piece Escher created seems to whisper the tragedies of my own life—layers of beauty intertwined with the harshness of reality. How can something so captivating feel so isolating? Just as Escher's designs defy logic and reason, my emotions twist and turn, leaving me in a maze of longing and despair. The world outside continues to spin, yet I am frozen in a moment where joy feels like a distant memory, an illusion I can never quite grasp. 🌧️ It’s painful to witness the laughter and happiness of others while I remain ensnared in this solitude. I watch as life unfolds in vibrant colors around me, while I sit in monochrome, a silent observer of a reality I can’t seem to touch. Relationships become intricate puzzles, beautiful yet impossible to solve, leaving me feeling more alone than ever. Just like Escher’s art, which captivates yet confounds, I find myself caught in the paradox of wanting to connect but fearing the inevitable disappointment that follows. 😢 In moments of despair, I seek solace within the lines and curves of Escher's work, each piece a poignant reminder of the beauty that can exist alongside pain. It’s a bittersweet comfort, knowing that others have created worlds that defy the ordinary, yet it also amplifies my sense of isolation. To be a dreamer in a world that feels so unattainable is a heavy burden to bear. I am trapped in my own impossible illusion, yearning for the day when the world will feel a little less distant and a little more like home. 🌌 As I traverse this winding path of existence, I am left to ponder: is it possible to find solace in the impossible? Can I transform my heartache into something beautiful, akin to Escher's masterpieces? Or will I remain just another fleeting thought in a world full of intricate designs that I can only admire from afar? In the end, I am just a lost soul, hoping that one day I will break free from this illusion of the impossible and find a place where I truly belong. Until then, I will continue to search for meaning in the chaos, just like Escher, who saw potential in the impossible. #Isolation #Heartache #Escher #Illusion #ArtandLife
    Maurits Escher, l’illusion de l’impossible
    Escher est un "mathémagicien" qui a réalisé des œuvres réalistes et pourtant physiquement irréalisables, mêlant art et mathématiques. L’article Maurits Escher, l’illusion de l’impossible est apparu en premier sur Graphéine - Agence de com
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  • In a world filled with noise and confusion, I often find myself wandering through the shadows of my own thoughts, feeling the weight of solitude pressing down on my heart. Life seems to be a maze of unanswered questions, and every attempt to connect with others feels like reaching for a mirage, only to grasp nothing but empty air.

    The moments of joy I once held close now feel like distant memories, echoes of laughter fading into silence. I watch as others move forward, their lives intertwined in a tapestry of companionship and love, while I remain a mere spectator, lost in a sea of loneliness. The more I search for meaning, the more isolated I feel, as if I am trapped within an invisible cage of despair.

    Sometimes, I think about how a multi-criteria search form could be a metaphor for my life—a tool that should help me filter through the chaos and find what truly matters. But instead, I am left with a default search, sifting through the mundane and the ordinary, finding little that resonates with my heart. The longing for depth and connection grows stronger, yet I find myself surrounded by barriers that prevent me from reaching out.

    Each day feels like a quest for something more, a yearning for authenticity in a world that often feels superficial. The possibility of a more advanced search for companionship seems like a distant dream. I wish I could apply those multi-criteria filters to my emotions, to sift through the layers of hurt and find the moments of true connection. But here I am, feeling invisible, as if my heart is a book with pages torn out—lost to time and forgotten by the world.

    In these quiet moments, I hold onto the hope that perhaps one day, I will find the right filters to navigate this labyrinth of loneliness. Until then, I carry my heart in silence, longing for the day when the search will lead me to a place where I truly belong.

    #Loneliness #Heartbreak #EmotionalJourney #SearchingForConnection #FeelingLost
    In a world filled with noise and confusion, I often find myself wandering through the shadows of my own thoughts, feeling the weight of solitude pressing down on my heart. Life seems to be a maze of unanswered questions, and every attempt to connect with others feels like reaching for a mirage, only to grasp nothing but empty air. 💔 The moments of joy I once held close now feel like distant memories, echoes of laughter fading into silence. I watch as others move forward, their lives intertwined in a tapestry of companionship and love, while I remain a mere spectator, lost in a sea of loneliness. The more I search for meaning, the more isolated I feel, as if I am trapped within an invisible cage of despair. 🥀 Sometimes, I think about how a multi-criteria search form could be a metaphor for my life—a tool that should help me filter through the chaos and find what truly matters. But instead, I am left with a default search, sifting through the mundane and the ordinary, finding little that resonates with my heart. The longing for depth and connection grows stronger, yet I find myself surrounded by barriers that prevent me from reaching out. Each day feels like a quest for something more, a yearning for authenticity in a world that often feels superficial. The possibility of a more advanced search for companionship seems like a distant dream. I wish I could apply those multi-criteria filters to my emotions, to sift through the layers of hurt and find the moments of true connection. But here I am, feeling invisible, as if my heart is a book with pages torn out—lost to time and forgotten by the world. 📖 In these quiet moments, I hold onto the hope that perhaps one day, I will find the right filters to navigate this labyrinth of loneliness. Until then, I carry my heart in silence, longing for the day when the search will lead me to a place where I truly belong. #Loneliness #Heartbreak #EmotionalJourney #SearchingForConnection #FeelingLost
    Un formulaire de recherche multi-critères
    Un formulaire de recherche multi-critères, ou recherche avancée, est un outil qui se distingue du module natif de WordPress en permettant à un utilisateur d’utiliser des options de recherche additionnelles et ainsi d’obtenir des résultats plus précis
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  • Ansys: R&D Engineer II (Remote - East Coast, US)

    Requisition #: 16890 Our Mission: Powering Innovation That Drives Human Advancement When visionary companies need to know how their world-changing ideas will perform, they close the gap between design and reality with Ansys simulation. For more than 50 years, Ansys software has enabled innovators across industries to push boundaries by using the predictive power of simulation. From sustainable transportation to advanced semiconductors, from satellite systems to life-saving medical devices, the next great leaps in human advancement will be powered by Ansys. Innovate With Ansys, Power Your Career. Summary / Role Purpose The R&D Engineer II contributes to the development of software products and supporting systems. In this role, the R&D Engineer II will collaborate with a team of expert professionals to understand customer requirements and accomplish development objectives. Key Duties and Responsibilities Performs moderately complex development activities, including the design, implementation, maintenance, testing and documentation of software modules and sub-systems Understands and employs best practices Performs moderately complex bug verification, release testing and beta support for assigned products. Researches problems discovered by QA or product support and develops solutions Understands the marketing requirements for a product, including target environment, performance criteria and competitive issues Works under the general supervision of a development manager Minimum Education/Certification Requirements and Experience BS in Computer Science, Applied Mathematics, Engineering, or other natural science disciplines with 3-5 years' experience or MS with minimum 2 years experience Working experience within technical software development proven by academic, research, or industry projects. Good understanding and skills in object-oriented programming Experience with Java and C# / .NET Role can be remote, must be based on the East Coast due to timezone Preferred Qualifications and Skills Experience with C++, Python, in addition to Java and C# / .NET Knowledge of Task-Based Asynchronous design patternExposure to model-based systems engineering concepts Working knowledge of SysML Know-how on cloud computing technologies like micro-service architectures, RPC frameworks, REST APIs, etc. Knowledge of software security best practices Experience working on an Agile software development team Technical knowledge and experience with various engineering tools and methodologies, such as Finite Element simulation, CAD modeling, and Systems Architecture modelling is a plus Ability to assist more junior developers on an as-needed basis Ability to learn quickly and to collaborate with others in a geographically distributed team Excellent communication and interpersonal skills At Ansys, we know that changing the world takes vision, skill, and each other. We fuel new ideas, build relationships, and help each other realize our greatest potential. We are ONE Ansys. We operate on three key components: our commitments to stakeholders, our values that guide how we work together, and our actions to deliver results. As ONE Ansys, we are powering innovation that drives human advancement Our Commitments:Amaze with innovative products and solutionsMake our customers incredibly successfulAct with integrityEnsure employees thrive and shareholders prosper Our Values:Adaptability: Be open, welcome what's nextCourage: Be courageous, move forward passionatelyGenerosity: Be generous, share, listen, serveAuthenticity: Be you, make us stronger Our Actions:We commit to audacious goalsWe work seamlessly as a teamWe demonstrate masteryWe deliver outstanding resultsVALUES IN ACTION Ansys is committed to powering the people who power human advancement. We believe in creating and nurturing a workplace that supports and welcomes people of all backgrounds; encouraging them to bring their talents and experience to a workplace where they are valued and can thrive. Our culture is grounded in our four core values of adaptability, courage, generosity, and authenticity. Through our behaviors and actions, these values foster higher team performance and greater innovation for our customers. We're proud to offer programs, available to all employees, to further impact innovation and business outcomes, such as employee networks and learning communities that inform solutions for our globally minded customer base. WELCOME WHAT'S NEXT IN YOUR CAREER AT ANSYS At Ansys, you will find yourself among the sharpest minds and most visionary leaders across the globe. Collectively, we strive to change the world with innovative technology and transformational solutions. With a prestigious reputation in working with well-known, world-class companies, standards at Ansys are high - met by those willing to rise to the occasion and meet those challenges head on. Our team is passionate about pushing the limits of world-class simulation technology, empowering our customers to turn their design concepts into successful, innovative products faster and at a lower cost. Ready to feel inspired? Check out some of our recent customer stories, here and here . At Ansys, it's about the learning, the discovery, and the collaboration. It's about the "what's next" as much as the "mission accomplished." And it's about the melding of disciplined intellect with strategic direction and results that have, can, and do impact real people in real ways. All this is forged within a working environment built on respect, autonomy, and ethics.CREATING A PLACE WE'RE PROUD TO BEAnsys is an S&P 500 company and a member of the NASDAQ-100. We are proud to have been recognized for the following more recent awards, although our list goes on: Newsweek's Most Loved Workplace globally and in the U.S., Gold Stevie Award Winner, America's Most Responsible Companies, Fast Company World Changing Ideas, Great Place to Work Certified.For more information, please visit us at Ansys is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other protected characteristics.Ansys does not accept unsolicited referrals for vacancies, and any unsolicited referral will become the property of Ansys. Upon hire, no fee will be owed to the agency, person, or entity.Apply NowLet's start your dream job Apply now Meet JobCopilot: Your Personal AI Job HunterAutomatically Apply to Remote Full-Stack Programming JobsJust set your preferences and Job Copilot will do the rest-finding, filtering, and applying while you focus on what matters. Activate JobCopilot
    #ansys #rampampd #engineer #remote #east
    Ansys: R&D Engineer II (Remote - East Coast, US)
    Requisition #: 16890 Our Mission: Powering Innovation That Drives Human Advancement When visionary companies need to know how their world-changing ideas will perform, they close the gap between design and reality with Ansys simulation. For more than 50 years, Ansys software has enabled innovators across industries to push boundaries by using the predictive power of simulation. From sustainable transportation to advanced semiconductors, from satellite systems to life-saving medical devices, the next great leaps in human advancement will be powered by Ansys. Innovate With Ansys, Power Your Career. Summary / Role Purpose The R&D Engineer II contributes to the development of software products and supporting systems. In this role, the R&D Engineer II will collaborate with a team of expert professionals to understand customer requirements and accomplish development objectives. Key Duties and Responsibilities Performs moderately complex development activities, including the design, implementation, maintenance, testing and documentation of software modules and sub-systems Understands and employs best practices Performs moderately complex bug verification, release testing and beta support for assigned products. Researches problems discovered by QA or product support and develops solutions Understands the marketing requirements for a product, including target environment, performance criteria and competitive issues Works under the general supervision of a development manager Minimum Education/Certification Requirements and Experience BS in Computer Science, Applied Mathematics, Engineering, or other natural science disciplines with 3-5 years' experience or MS with minimum 2 years experience Working experience within technical software development proven by academic, research, or industry projects. Good understanding and skills in object-oriented programming Experience with Java and C# / .NET Role can be remote, must be based on the East Coast due to timezone Preferred Qualifications and Skills Experience with C++, Python, in addition to Java and C# / .NET Knowledge of Task-Based Asynchronous design patternExposure to model-based systems engineering concepts Working knowledge of SysML Know-how on cloud computing technologies like micro-service architectures, RPC frameworks, REST APIs, etc. Knowledge of software security best practices Experience working on an Agile software development team Technical knowledge and experience with various engineering tools and methodologies, such as Finite Element simulation, CAD modeling, and Systems Architecture modelling is a plus Ability to assist more junior developers on an as-needed basis Ability to learn quickly and to collaborate with others in a geographically distributed team Excellent communication and interpersonal skills At Ansys, we know that changing the world takes vision, skill, and each other. We fuel new ideas, build relationships, and help each other realize our greatest potential. We are ONE Ansys. We operate on three key components: our commitments to stakeholders, our values that guide how we work together, and our actions to deliver results. As ONE Ansys, we are powering innovation that drives human advancement Our Commitments:Amaze with innovative products and solutionsMake our customers incredibly successfulAct with integrityEnsure employees thrive and shareholders prosper Our Values:Adaptability: Be open, welcome what's nextCourage: Be courageous, move forward passionatelyGenerosity: Be generous, share, listen, serveAuthenticity: Be you, make us stronger Our Actions:We commit to audacious goalsWe work seamlessly as a teamWe demonstrate masteryWe deliver outstanding resultsVALUES IN ACTION Ansys is committed to powering the people who power human advancement. We believe in creating and nurturing a workplace that supports and welcomes people of all backgrounds; encouraging them to bring their talents and experience to a workplace where they are valued and can thrive. Our culture is grounded in our four core values of adaptability, courage, generosity, and authenticity. Through our behaviors and actions, these values foster higher team performance and greater innovation for our customers. We're proud to offer programs, available to all employees, to further impact innovation and business outcomes, such as employee networks and learning communities that inform solutions for our globally minded customer base. WELCOME WHAT'S NEXT IN YOUR CAREER AT ANSYS At Ansys, you will find yourself among the sharpest minds and most visionary leaders across the globe. Collectively, we strive to change the world with innovative technology and transformational solutions. With a prestigious reputation in working with well-known, world-class companies, standards at Ansys are high - met by those willing to rise to the occasion and meet those challenges head on. Our team is passionate about pushing the limits of world-class simulation technology, empowering our customers to turn their design concepts into successful, innovative products faster and at a lower cost. Ready to feel inspired? Check out some of our recent customer stories, here and here . At Ansys, it's about the learning, the discovery, and the collaboration. It's about the "what's next" as much as the "mission accomplished." And it's about the melding of disciplined intellect with strategic direction and results that have, can, and do impact real people in real ways. All this is forged within a working environment built on respect, autonomy, and ethics.CREATING A PLACE WE'RE PROUD TO BEAnsys is an S&P 500 company and a member of the NASDAQ-100. We are proud to have been recognized for the following more recent awards, although our list goes on: Newsweek's Most Loved Workplace globally and in the U.S., Gold Stevie Award Winner, America's Most Responsible Companies, Fast Company World Changing Ideas, Great Place to Work Certified.For more information, please visit us at Ansys is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other protected characteristics.Ansys does not accept unsolicited referrals for vacancies, and any unsolicited referral will become the property of Ansys. Upon hire, no fee will be owed to the agency, person, or entity.Apply NowLet's start your dream job Apply now Meet JobCopilot: Your Personal AI Job HunterAutomatically Apply to Remote Full-Stack Programming JobsJust set your preferences and Job Copilot will do the rest-finding, filtering, and applying while you focus on what matters. Activate JobCopilot #ansys #rampampd #engineer #remote #east
    WEWORKREMOTELY.COM
    Ansys: R&D Engineer II (Remote - East Coast, US)
    Requisition #: 16890 Our Mission: Powering Innovation That Drives Human Advancement When visionary companies need to know how their world-changing ideas will perform, they close the gap between design and reality with Ansys simulation. For more than 50 years, Ansys software has enabled innovators across industries to push boundaries by using the predictive power of simulation. From sustainable transportation to advanced semiconductors, from satellite systems to life-saving medical devices, the next great leaps in human advancement will be powered by Ansys. Innovate With Ansys, Power Your Career. Summary / Role Purpose The R&D Engineer II contributes to the development of software products and supporting systems. In this role, the R&D Engineer II will collaborate with a team of expert professionals to understand customer requirements and accomplish development objectives. Key Duties and Responsibilities Performs moderately complex development activities, including the design, implementation, maintenance, testing and documentation of software modules and sub-systems Understands and employs best practices Performs moderately complex bug verification, release testing and beta support for assigned products. Researches problems discovered by QA or product support and develops solutions Understands the marketing requirements for a product, including target environment, performance criteria and competitive issues Works under the general supervision of a development manager Minimum Education/Certification Requirements and Experience BS in Computer Science, Applied Mathematics, Engineering, or other natural science disciplines with 3-5 years' experience or MS with minimum 2 years experience Working experience within technical software development proven by academic, research, or industry projects. Good understanding and skills in object-oriented programming Experience with Java and C# / .NET Role can be remote, must be based on the East Coast due to timezone Preferred Qualifications and Skills Experience with C++, Python, in addition to Java and C# / .NET Knowledge of Task-Based Asynchronous design pattern (TAP) Exposure to model-based systems engineering concepts Working knowledge of SysML Know-how on cloud computing technologies like micro-service architectures, RPC frameworks (e.g., gRPC), REST APIs, etc. Knowledge of software security best practices Experience working on an Agile software development team Technical knowledge and experience with various engineering tools and methodologies, such as Finite Element simulation, CAD modeling, and Systems Architecture modelling is a plus Ability to assist more junior developers on an as-needed basis Ability to learn quickly and to collaborate with others in a geographically distributed team Excellent communication and interpersonal skills At Ansys, we know that changing the world takes vision, skill, and each other. We fuel new ideas, build relationships, and help each other realize our greatest potential. We are ONE Ansys. We operate on three key components: our commitments to stakeholders, our values that guide how we work together, and our actions to deliver results. As ONE Ansys, we are powering innovation that drives human advancement Our Commitments:Amaze with innovative products and solutionsMake our customers incredibly successfulAct with integrityEnsure employees thrive and shareholders prosper Our Values:Adaptability: Be open, welcome what's nextCourage: Be courageous, move forward passionatelyGenerosity: Be generous, share, listen, serveAuthenticity: Be you, make us stronger Our Actions:We commit to audacious goalsWe work seamlessly as a teamWe demonstrate masteryWe deliver outstanding resultsVALUES IN ACTION Ansys is committed to powering the people who power human advancement. We believe in creating and nurturing a workplace that supports and welcomes people of all backgrounds; encouraging them to bring their talents and experience to a workplace where they are valued and can thrive. Our culture is grounded in our four core values of adaptability, courage, generosity, and authenticity. Through our behaviors and actions, these values foster higher team performance and greater innovation for our customers. We're proud to offer programs, available to all employees, to further impact innovation and business outcomes, such as employee networks and learning communities that inform solutions for our globally minded customer base. WELCOME WHAT'S NEXT IN YOUR CAREER AT ANSYS At Ansys, you will find yourself among the sharpest minds and most visionary leaders across the globe. Collectively, we strive to change the world with innovative technology and transformational solutions. With a prestigious reputation in working with well-known, world-class companies, standards at Ansys are high - met by those willing to rise to the occasion and meet those challenges head on. Our team is passionate about pushing the limits of world-class simulation technology, empowering our customers to turn their design concepts into successful, innovative products faster and at a lower cost. Ready to feel inspired? Check out some of our recent customer stories, here and here . At Ansys, it's about the learning, the discovery, and the collaboration. It's about the "what's next" as much as the "mission accomplished." And it's about the melding of disciplined intellect with strategic direction and results that have, can, and do impact real people in real ways. All this is forged within a working environment built on respect, autonomy, and ethics.CREATING A PLACE WE'RE PROUD TO BEAnsys is an S&P 500 company and a member of the NASDAQ-100. We are proud to have been recognized for the following more recent awards, although our list goes on: Newsweek's Most Loved Workplace globally and in the U.S., Gold Stevie Award Winner, America's Most Responsible Companies, Fast Company World Changing Ideas, Great Place to Work Certified (China, Greece, France, India, Japan, Korea, Spain, Sweden, Taiwan, and U.K.).For more information, please visit us at Ansys is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other protected characteristics.Ansys does not accept unsolicited referrals for vacancies, and any unsolicited referral will become the property of Ansys. Upon hire, no fee will be owed to the agency, person, or entity.Apply NowLet's start your dream job Apply now Meet JobCopilot: Your Personal AI Job HunterAutomatically Apply to Remote Full-Stack Programming JobsJust set your preferences and Job Copilot will do the rest-finding, filtering, and applying while you focus on what matters. Activate JobCopilot
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  • Turning Points: Accept & Proceed

    12 June, 2025

    In our turning points series, design studios share some of the key moments that shaped their business. This week, we meet Accept & Proceed.

    Accept & Proceed is a London based brand and design studio that works with clients like NASA, Nike and LEGO.
    Founder David Johnston talks us through some of the decisions that defined his business.
    In 2006, Johnston took the leap to start his own business, armed with a good name and a willingness to bend the truth about his team…
    I’d gone through my career learning from big organisations, and one small organisation, and I felt like I wasn’t happy where I was. It was my dad who encouraged me to take a leap of faith and try and go it alone. With nothing more than a month’s wages in the bank and a lot of energy, I decided to go and set up an agency.
    That really just means giving yourself a name and starting to promote yourself in the world.
    Accept & Proceed founder David Johnston
    I think the name itself is a very important thing. I wanted something that was memorable but also layered in meaning. A name that starts with an “a” is very beneficial when you’re being listed in the index of books and things like that.
    But it became a bit of a compass for the way that we wanted to create work, around accepting the status quo for what it is, but with a continual commitment to proceed nonetheless.
    Because I didn’t have anyone to work with, in those early months I just made up email addresses of people that didn’t exist. That allowed me to cost projects up for multiple people. That’s obviously a degree of hustle I wouldn’t encourage in everyone, but it meant I was able to charge multiple day rates for projects where I was playing the role of four or five people.
    Self-initiated projects have long been part of the studio’s DNA and played a key role in building key client relationships.
    A&P by… was a brief to explore these letterforms without any commercial intent apart from the joy of creative expression. I started reaching out to illustrators and artists and photographers and designers that I really rated, and the things that started coming back were incredible.
    I was overwhelmed by the amount of energy and passion that people like Mr Bingo and Jason Evans were bringing to this.
    I think in so many ways, the answer to everything is community. I’ve gone on to work with a lot of the people that created these, and they also became friends. It was an early example of dissolving these illusionary boundaries around what an agency might be, but also expanding and amplifying your potential.
    The first of Accept & Proceed’s Light Calendars
    Then in 2006, I was trying to establish our portfolio and I wanted something to send out into the world that would also be an example of how Accept & Proceed thinks about design. I landed on these data visualisations that show the amount of light and darkness that would happen in London in the year ahead.
    I worked with a freelance designer called Stephen Heath on the first one – he is now our creative director.
    This kickstarted a 10-year exploration, and they became a rite of passage for new designers that came into the studio, to take that very similar data and express it in completely new ways. It culminated in an exhibition in London in 2016, showing ten years’ of prints.
    They were a labour of love, but they also meant that every single year we had a number of prints that we could send out to new potential contacts. Still when I go to the global headquarters of Nike in Beaverton in Portland, I’m amazed at how many of these sit in leaders’ offices there.
    When we first got a finance director, they couldn’t believe how much we’d invested as a business in things like this – we even had our own gallery for a while. It doesn’t make sense from a purely numbers mindset, but if you put things out there for authentic reasons, there are ripple effects over time.
    In 2017, the studio became a B-corp, the fourth creative agency in the UK to get this accreditation.
    Around 2016, I couldn’t help but look around – as we probably all have at varying points over the last 10 years – and wondered, what the fuck is going on?
    All these systems are not fit for purpose for the future – financial systems, food systems, relationship systems, energy systems. They’re not working. And I was like shit, are we part of the problem?
    Accept & Proceed’s work for the NASA Jet Propulsion Laboratory
    I’ve always thought of brand as a piece of technology that can fundamentally change our actions and the world around us. That comes with a huge responsibility.
    We probably paid four months’ wages of two people full-time just to get accredited, so it’s quite a high bar. But I like that the programme shackles you to this idea of improvement. You can’t rest on your laurels if you want to be re-accredited. It’s like the way design works as an iterative process – you have to keep getting better.
    In 2019, Johnston and his team started thinking seriously about the studio’s own brand, and created a punchy, nuanced new positioning.
    We got to a point where we’d proven we could help brands achieve their commercial aims. But we wanted to hold a position ourselves, not just be a conduit between a brand and its audience.
    It still amazes me that so few agencies actually stand for anything. We realised that all the things – vision, mission, principles – that we’ve been creating for brands for years, we hadn’t done for ourselves.
    It’s a bit like when you see a hairdresser with a really dodgy haircut. But it’s hard to cut your own hair.
    So we went through that process, which was really difficult, and we landed on “Design for the future” as our promise to the world.
    And if you’re going to have that as a promise, you better be able to describe the world you’re creating through your work, which we call “the together world.”
    Accept & Proceed’s work for Second Sea
    We stand at this most incredible moment in history where the latest technology and science is catching up with ancient wisdom, to know that we must become more entangled, more together, more whole.
    And we’ve assessed five global shifts that are happening in order to be able to take us towards a more together world through our work – interbeing, reciprocity, healing, resilience and liberation.
    The year before last, we lost three global rebrand projects based on our positioning. Every one of them said to me, “You’re right but we’re not ready.”
    But this year, I think the product market fit of what we’ve been saying for the last five years is really starting to mesh. We’re working with Arc’teryx on their 2030 landscape, evolving Nike’s move to zero, and working with LEGO on what their next 100 years might look like, which is mind-boggling work.
    I don’t think we could have won any of those opportunities had we not been talking for quite a long time about design for the future.
    In 2023, Johnston started a sunrise gathering on Hackney Marshes, which became a very significant part of his life.
    I had the flu and I had a vision in my dreamy fluey state of a particular spot on Hackney Marshes where people were gathering and watching the sunrise. I happened to tell my friend, the poet Thomas Sharp this, and he said, “That’s a premonition. You have to make it happen.”
    The first year there were five of us – this year there were 300 people for the spring equinox in March.
    I don’t fully know what these gatherings will lead to. Will Accept & Proceed start to introduce the seasons to the way we operate as a business? It’s a thought I’ve had percolating, but I don’t know. Will it be something else?
    One of the 2024 sunrise gatherings organised by Accept & Proceed founder David Johnston
    I do know that there’s major learnings around authentic community building for brands. We should do away with these buckets we put people into, of age group and location. They aren’t very true. It’s fascinating to see the breadth of people who come to these gatherings.
    Me and Laura were thinking at some point of moving out of London, but I think these sunrise gatherings are now my reason to stay. It’s the thing I didn’t know I needed until I had it. They have made London complete for me.
    There’s something so ancient about watching our star rise, and the reminder that we are actually just animals crawling upon the surface of a planet of mud. That’s what’s real. But it can be hard to remember that when you’re sitting at your computer in the studio.
    These gatherings help me better understand creativity’s true potential, for brands, for the world, and for us.

    Design disciplines in this article

    Brands in this article

    What to read next

    Features

    Turning Points: Cultural branding agency EDIT

    Brand Identity
    20 Nov, 2024
    #turning #points #accept #ampamp #proceed
    Turning Points: Accept & Proceed
    12 June, 2025 In our turning points series, design studios share some of the key moments that shaped their business. This week, we meet Accept & Proceed. Accept & Proceed is a London based brand and design studio that works with clients like NASA, Nike and LEGO. Founder David Johnston talks us through some of the decisions that defined his business. In 2006, Johnston took the leap to start his own business, armed with a good name and a willingness to bend the truth about his team… I’d gone through my career learning from big organisations, and one small organisation, and I felt like I wasn’t happy where I was. It was my dad who encouraged me to take a leap of faith and try and go it alone. With nothing more than a month’s wages in the bank and a lot of energy, I decided to go and set up an agency. That really just means giving yourself a name and starting to promote yourself in the world. Accept & Proceed founder David Johnston I think the name itself is a very important thing. I wanted something that was memorable but also layered in meaning. A name that starts with an “a” is very beneficial when you’re being listed in the index of books and things like that. But it became a bit of a compass for the way that we wanted to create work, around accepting the status quo for what it is, but with a continual commitment to proceed nonetheless. Because I didn’t have anyone to work with, in those early months I just made up email addresses of people that didn’t exist. That allowed me to cost projects up for multiple people. That’s obviously a degree of hustle I wouldn’t encourage in everyone, but it meant I was able to charge multiple day rates for projects where I was playing the role of four or five people. Self-initiated projects have long been part of the studio’s DNA and played a key role in building key client relationships. A&P by… was a brief to explore these letterforms without any commercial intent apart from the joy of creative expression. I started reaching out to illustrators and artists and photographers and designers that I really rated, and the things that started coming back were incredible. I was overwhelmed by the amount of energy and passion that people like Mr Bingo and Jason Evans were bringing to this. I think in so many ways, the answer to everything is community. I’ve gone on to work with a lot of the people that created these, and they also became friends. It was an early example of dissolving these illusionary boundaries around what an agency might be, but also expanding and amplifying your potential. The first of Accept & Proceed’s Light Calendars Then in 2006, I was trying to establish our portfolio and I wanted something to send out into the world that would also be an example of how Accept & Proceed thinks about design. I landed on these data visualisations that show the amount of light and darkness that would happen in London in the year ahead. I worked with a freelance designer called Stephen Heath on the first one – he is now our creative director. This kickstarted a 10-year exploration, and they became a rite of passage for new designers that came into the studio, to take that very similar data and express it in completely new ways. It culminated in an exhibition in London in 2016, showing ten years’ of prints. They were a labour of love, but they also meant that every single year we had a number of prints that we could send out to new potential contacts. Still when I go to the global headquarters of Nike in Beaverton in Portland, I’m amazed at how many of these sit in leaders’ offices there. When we first got a finance director, they couldn’t believe how much we’d invested as a business in things like this – we even had our own gallery for a while. It doesn’t make sense from a purely numbers mindset, but if you put things out there for authentic reasons, there are ripple effects over time. In 2017, the studio became a B-corp, the fourth creative agency in the UK to get this accreditation. Around 2016, I couldn’t help but look around – as we probably all have at varying points over the last 10 years – and wondered, what the fuck is going on? All these systems are not fit for purpose for the future – financial systems, food systems, relationship systems, energy systems. They’re not working. And I was like shit, are we part of the problem? Accept & Proceed’s work for the NASA Jet Propulsion Laboratory I’ve always thought of brand as a piece of technology that can fundamentally change our actions and the world around us. That comes with a huge responsibility. We probably paid four months’ wages of two people full-time just to get accredited, so it’s quite a high bar. But I like that the programme shackles you to this idea of improvement. You can’t rest on your laurels if you want to be re-accredited. It’s like the way design works as an iterative process – you have to keep getting better. In 2019, Johnston and his team started thinking seriously about the studio’s own brand, and created a punchy, nuanced new positioning. We got to a point where we’d proven we could help brands achieve their commercial aims. But we wanted to hold a position ourselves, not just be a conduit between a brand and its audience. It still amazes me that so few agencies actually stand for anything. We realised that all the things – vision, mission, principles – that we’ve been creating for brands for years, we hadn’t done for ourselves. It’s a bit like when you see a hairdresser with a really dodgy haircut. But it’s hard to cut your own hair. So we went through that process, which was really difficult, and we landed on “Design for the future” as our promise to the world. And if you’re going to have that as a promise, you better be able to describe the world you’re creating through your work, which we call “the together world.” Accept & Proceed’s work for Second Sea We stand at this most incredible moment in history where the latest technology and science is catching up with ancient wisdom, to know that we must become more entangled, more together, more whole. And we’ve assessed five global shifts that are happening in order to be able to take us towards a more together world through our work – interbeing, reciprocity, healing, resilience and liberation. The year before last, we lost three global rebrand projects based on our positioning. Every one of them said to me, “You’re right but we’re not ready.” But this year, I think the product market fit of what we’ve been saying for the last five years is really starting to mesh. We’re working with Arc’teryx on their 2030 landscape, evolving Nike’s move to zero, and working with LEGO on what their next 100 years might look like, which is mind-boggling work. I don’t think we could have won any of those opportunities had we not been talking for quite a long time about design for the future. In 2023, Johnston started a sunrise gathering on Hackney Marshes, which became a very significant part of his life. I had the flu and I had a vision in my dreamy fluey state of a particular spot on Hackney Marshes where people were gathering and watching the sunrise. I happened to tell my friend, the poet Thomas Sharp this, and he said, “That’s a premonition. You have to make it happen.” The first year there were five of us – this year there were 300 people for the spring equinox in March. I don’t fully know what these gatherings will lead to. Will Accept & Proceed start to introduce the seasons to the way we operate as a business? It’s a thought I’ve had percolating, but I don’t know. Will it be something else? One of the 2024 sunrise gatherings organised by Accept & Proceed founder David Johnston I do know that there’s major learnings around authentic community building for brands. We should do away with these buckets we put people into, of age group and location. They aren’t very true. It’s fascinating to see the breadth of people who come to these gatherings. Me and Laura were thinking at some point of moving out of London, but I think these sunrise gatherings are now my reason to stay. It’s the thing I didn’t know I needed until I had it. They have made London complete for me. There’s something so ancient about watching our star rise, and the reminder that we are actually just animals crawling upon the surface of a planet of mud. That’s what’s real. But it can be hard to remember that when you’re sitting at your computer in the studio. These gatherings help me better understand creativity’s true potential, for brands, for the world, and for us. Design disciplines in this article Brands in this article What to read next Features Turning Points: Cultural branding agency EDIT Brand Identity 20 Nov, 2024 #turning #points #accept #ampamp #proceed
    WWW.DESIGNWEEK.CO.UK
    Turning Points: Accept & Proceed
    12 June, 2025 In our turning points series, design studios share some of the key moments that shaped their business. This week, we meet Accept & Proceed. Accept & Proceed is a London based brand and design studio that works with clients like NASA, Nike and LEGO. Founder David Johnston talks us through some of the decisions that defined his business. In 2006, Johnston took the leap to start his own business, armed with a good name and a willingness to bend the truth about his team… I’d gone through my career learning from big organisations, and one small organisation, and I felt like I wasn’t happy where I was. It was my dad who encouraged me to take a leap of faith and try and go it alone. With nothing more than a month’s wages in the bank and a lot of energy, I decided to go and set up an agency. That really just means giving yourself a name and starting to promote yourself in the world. Accept & Proceed founder David Johnston I think the name itself is a very important thing. I wanted something that was memorable but also layered in meaning. A name that starts with an “a” is very beneficial when you’re being listed in the index of books and things like that. But it became a bit of a compass for the way that we wanted to create work, around accepting the status quo for what it is, but with a continual commitment to proceed nonetheless. Because I didn’t have anyone to work with, in those early months I just made up email addresses of people that didn’t exist. That allowed me to cost projects up for multiple people. That’s obviously a degree of hustle I wouldn’t encourage in everyone, but it meant I was able to charge multiple day rates for projects where I was playing the role of four or five people. Self-initiated projects have long been part of the studio’s DNA and played a key role in building key client relationships. A&P by… was a brief to explore these letterforms without any commercial intent apart from the joy of creative expression. I started reaching out to illustrators and artists and photographers and designers that I really rated, and the things that started coming back were incredible. I was overwhelmed by the amount of energy and passion that people like Mr Bingo and Jason Evans were bringing to this. I think in so many ways, the answer to everything is community. I’ve gone on to work with a lot of the people that created these, and they also became friends. It was an early example of dissolving these illusionary boundaries around what an agency might be, but also expanding and amplifying your potential. The first of Accept & Proceed’s Light Calendars Then in 2006, I was trying to establish our portfolio and I wanted something to send out into the world that would also be an example of how Accept & Proceed thinks about design. I landed on these data visualisations that show the amount of light and darkness that would happen in London in the year ahead. I worked with a freelance designer called Stephen Heath on the first one – he is now our creative director. This kickstarted a 10-year exploration, and they became a rite of passage for new designers that came into the studio, to take that very similar data and express it in completely new ways. It culminated in an exhibition in London in 2016, showing ten years’ of prints. They were a labour of love, but they also meant that every single year we had a number of prints that we could send out to new potential contacts. Still when I go to the global headquarters of Nike in Beaverton in Portland, I’m amazed at how many of these sit in leaders’ offices there. When we first got a finance director, they couldn’t believe how much we’d invested as a business in things like this – we even had our own gallery for a while. It doesn’t make sense from a purely numbers mindset, but if you put things out there for authentic reasons, there are ripple effects over time. In 2017, the studio became a B-corp, the fourth creative agency in the UK to get this accreditation. Around 2016, I couldn’t help but look around – as we probably all have at varying points over the last 10 years – and wondered, what the fuck is going on? All these systems are not fit for purpose for the future – financial systems, food systems, relationship systems, energy systems. They’re not working. And I was like shit, are we part of the problem? Accept & Proceed’s work for the NASA Jet Propulsion Laboratory I’ve always thought of brand as a piece of technology that can fundamentally change our actions and the world around us. That comes with a huge responsibility. We probably paid four months’ wages of two people full-time just to get accredited, so it’s quite a high bar. But I like that the programme shackles you to this idea of improvement. You can’t rest on your laurels if you want to be re-accredited. It’s like the way design works as an iterative process – you have to keep getting better. In 2019, Johnston and his team started thinking seriously about the studio’s own brand, and created a punchy, nuanced new positioning. We got to a point where we’d proven we could help brands achieve their commercial aims. But we wanted to hold a position ourselves, not just be a conduit between a brand and its audience. It still amazes me that so few agencies actually stand for anything. We realised that all the things – vision, mission, principles – that we’ve been creating for brands for years, we hadn’t done for ourselves. It’s a bit like when you see a hairdresser with a really dodgy haircut. But it’s hard to cut your own hair. So we went through that process, which was really difficult, and we landed on “Design for the future” as our promise to the world. And if you’re going to have that as a promise, you better be able to describe the world you’re creating through your work, which we call “the together world.” Accept & Proceed’s work for Second Sea We stand at this most incredible moment in history where the latest technology and science is catching up with ancient wisdom, to know that we must become more entangled, more together, more whole. And we’ve assessed five global shifts that are happening in order to be able to take us towards a more together world through our work – interbeing, reciprocity, healing, resilience and liberation. The year before last, we lost three global rebrand projects based on our positioning. Every one of them said to me, “You’re right but we’re not ready.” But this year, I think the product market fit of what we’ve been saying for the last five years is really starting to mesh. We’re working with Arc’teryx on their 2030 landscape, evolving Nike’s move to zero, and working with LEGO on what their next 100 years might look like, which is mind-boggling work. I don’t think we could have won any of those opportunities had we not been talking for quite a long time about design for the future. In 2023, Johnston started a sunrise gathering on Hackney Marshes, which became a very significant part of his life. I had the flu and I had a vision in my dreamy fluey state of a particular spot on Hackney Marshes where people were gathering and watching the sunrise. I happened to tell my friend, the poet Thomas Sharp this, and he said, “That’s a premonition. You have to make it happen.” The first year there were five of us – this year there were 300 people for the spring equinox in March. I don’t fully know what these gatherings will lead to. Will Accept & Proceed start to introduce the seasons to the way we operate as a business? It’s a thought I’ve had percolating, but I don’t know. Will it be something else? One of the 2024 sunrise gatherings organised by Accept & Proceed founder David Johnston I do know that there’s major learnings around authentic community building for brands. We should do away with these buckets we put people into, of age group and location. They aren’t very true. It’s fascinating to see the breadth of people who come to these gatherings. Me and Laura were thinking at some point of moving out of London, but I think these sunrise gatherings are now my reason to stay. It’s the thing I didn’t know I needed until I had it. They have made London complete for me. There’s something so ancient about watching our star rise, and the reminder that we are actually just animals crawling upon the surface of a planet of mud. That’s what’s real. But it can be hard to remember that when you’re sitting at your computer in the studio. These gatherings help me better understand creativity’s true potential, for brands, for the world, and for us. Design disciplines in this article Brands in this article What to read next Features Turning Points: Cultural branding agency EDIT Brand Identity 20 Nov, 2024
    0 Reacties 0 aandelen
  • 15 riveting images from the 2025 UN World Oceans Day Photo Competition

    Big and Small Underwater Faces — 3rd Place.
    Trips to the Antarctic Peninsula always yield amazing encounters with leopard seals. Boldly approaching me and baring his teeth, this individual was keen to point out that this part of Antarctica was his territory. This picture was shot at dusk, resulting in the rather moody atmosphere.
     
    Credit: Lars von Ritter Zahony/ World Ocean’s Day

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    The striking eye of a humpback whale named Sweet Girl peers at the camera. Just four days later, she would be dead, hit by a speeding boat and one of the 20,000 whales killed by ship strikes each year. Photographer Rachel Moore’s captivating imageof Sweet Girl earned top honors at the 2025 United Nations World Oceans Day Photo Competition.
    Wonder: Sustaining What Sustains Us — WinnerThis photo, taken in Mo’orea, French Polynesia in 2024, captures the eye of a humpback whale named Sweet Girl, just days before her tragic death. Four days after I captured this intimate moment, she was struck and killed by a fast-moving ship. Her death serves as a heartbreaking reminder of the 20,000 whales lost to ship strikes every year. We are using her story to advocate for stronger protections, petitioning for stricter speed laws around Tahiti and Mo’orea during whale season. I hope Sweet Girl’s legacy will spark real change to protect these incredible animals and prevent further senseless loss.Credit: Rachel Moore/ United Nations World Oceans Day www.unworldoceansday.org
    Now in its twelfth year, the competition coordinated in collaboration between the UN Division for Ocean Affairs and the Law of the Sea, DivePhotoGuide, Oceanic Global, and  the Intergovernmental Oceanographic Commission of UNESCO. Each year, thousands of underwater photographers submit images that judges award prizes for across four categories: Big and Small Underwater Faces, Underwater Seascapes, Above Water Seascapes, and Wonder: Sustaining What Sustains Us.
    This year’s winning images include a curious leopard seal, a swarm of jellyfish, and a very grumpy looking Japanese warbonnet. Given our oceans’ perilous state, all competition participants were required to sign a charter of 14 commitments regarding ethics in photography.
    Underwater Seascapes — Honorable MentionWith only orcas as their natural predators, leopard seals are Antarctica’s most versatile hunters, preying on everything from fish and cephalopods to penguins and other seals. Gentoo penguins are a favored menu item, and leopard seals can be observed patrolling the waters around their colonies. For this shot, I used a split image to capture both worlds: the gentoo penguin colony in the background with the leopard seal on the hunt in the foreground.Credit: Lars von Ritter Zahony/ United Nations World Oceans Day www.unworldoceansday.org
    Above Water Seascapes – WinnerA serene lake cradled by arid dunes, where a gentle stream breathes life into the heart of Mother Earth’s creation: Captured from an airplane, this image reveals the powerful contrasts and hidden beauty where land and ocean meet, reminding us that the ocean is the source of all life and that everything in nature is deeply connected. The location is a remote stretch of coastline near Shark Bay, Western Australia.Credit: Leander Nardin/ United Nations World Oceans Day www.unworldoceansday.org
    Above Water Seascapes — 3rd PlaceParadise Harbour is one of the most beautiful places on the Antarctic Peninsula. When I visited, the sea was extremely calm, and I was lucky enough to witness a wonderfully clear reflection of the Suárez Glacierin the water. The only problem was the waves created by our speedboat, and the only way to capture the perfect reflection was to lie on the bottom of the boat while it moved towards the glacier.Credit: Andrey Nosik/ United Nations World Oceans Day www.unworldoceansday.org
    Underwater Seascapes — 3rd Place“La Rapadura” is a natural hidden treasure on the northern coast of Tenerife, in the Spanish territory of the Canary Islands. Only discovered in 1996, it is one of the most astonishing underwater landscapes in the world, consistently ranking among the planet’s best dive sites. These towering columns of basalt are the result of volcanic processes that occurred between 500,000 and a million years ago. The formation was created when a basaltic lava flow reached the ocean, where, upon cooling and solidifying, it contracted, creating natural structures often compared to the pipes of church organs. Located in a region where marine life has been impacted by once common illegal fishing practices, this stunning natural monument has both geological and ecological value, and scientists and underwater photographers are advocating for its protection.Credit: Pedro Carrillo/ United Nations World Oceans Day www.unworldoceansday.org
    Underwater Seascapes — WinnerThis year, I had the incredible opportunity to visit a jellyfish lake during a liveaboard trip around southern Raja Ampat, Indonesia. Being surrounded by millions of jellyfish, which have evolved to lose their stinging ability due to the absence of predators, was one of the most breathtaking experiences I’ve ever had.Credit: Dani Escayola/ United Nations World Oceans Day www.unworldoceansday.org
    Underwater Seascapes — 2nd PlaceThis shot captures a school of rays resting at a cleaning station in Mauritius, where strong currents once attracted them regularly. Some rays grew accustomed to divers, allowing close encounters like this. Sadly, after the severe bleaching that the reefs here suffered last year, such gatherings have become rare, and I fear I may not witness this again at the same spot.Credit: Gerald Rambert/ United Nations World Oceans Day www.unworldoceansday.org
    Wonder: Sustaining What Sustains Us — 3rd PlaceShot in Cuba’s Jardines de la Reina—a protected shark sanctuary—this image captures a Caribbean reef shark weaving through a group of silky sharks near the surface. Using a slow shutter and strobes as the shark pivoted sharply, the motion blurred into a wave-like arc across its head, lit by the golden hues of sunset. The abundance and behavior of sharks here is a living symbol of what protected oceans can look like.Credit: Steven Lopez/ United Nations World Oceans Day www.unworldoceansday.org
     Above Water Seascapes — 2nd PlaceNorthern gannetssoar above the dramatic cliffs of Scotland’s Hermaness National Nature Reserve, their sleek white bodies and black-tipped wings slicing through the Shetland winds. These seabirds, the largest in the North Atlantic, are renowned for their striking plunge-dives, reaching speeds up to 100 kphas they hunt for fish beneath the waves. The cliffs of Hermaness provide ideal nesting sites, with updrafts aiding their take-offs and landings. Each spring, thousands return to this rugged coastline, forming one of the UK’s most significant gannet colonies. It was a major challenge to take photos at the edge of these cliffs at almost 200 meterswith the winds up to 30 kph.Credit: Nur Tucker/ United Nations World Oceans Day www.unworldoceansday.org
    Above Water Seascapes — Honorable MentionA South Atlantic swell breaks on the Dungeons Reef off the Cape Peninsula, South Africa, shot while photographing a big-wave surf session in October 2017. It’s the crescendoing sounds of these breaking swells that always amazes me.Credit: Ken Findlay/ United Nations World Oceans Day www.unworldoceansday.org
    Wonder: Sustaining What Sustains Us — Honorable MentionHumpback whales in their thousands migrate along the Ningaloo Reef in Western Australia every year on the way to and from their calving grounds. In four seasons of swimming with them on the reef here, this is the only encounter I’ve had like this one. This pair of huge adult whales repeatedly spy-hopped alongside us, seeking to interact with and investigate us, leaving me completely breathless. The female in the foreground was much more confident than the male behind and would constantly make close approaches, whilst the male hung back a little, still interested but shy. After more than 10 years working with wildlife in the water, this was one of the best experiences of my life.Credit: Ollie Clarke/ United Nations World Oceans Day www.unworldoceansday.org
    Big and Small Underwater Faces — 2nd PlaceOn one of my many blackwater dives in Anilao, in the Philippines, my guide and I spotted something moving erratically at a depth of around 20 meters, about 10 to 15 centimeters in size. We quickly realized that it was a rare blanket octopus. As we approached, it opened up its beautiful blanket, revealing its multicolored mantle. I managed to take a few shots before it went on its way. I felt truly privileged to have captured this fascinating deep-sea cephalopod. Among its many unique characteristics, this species exhibits some of the most extreme sexual size-dimorphism in nature, with females weighing up to 40,000 times more than males.Credit: Giacomo Marchione/ United Nations World Oceans Day www.unworldoceansday.org
    Big and Small Underwater Faces – WinnerThis photo of a Japanese warbonnetwas captured in the Sea of Japan, about 50 milessouthwest of Vladivostok, Russia. I found the ornate fish at a depth of about 30 meters, under the stern of a shipwreck. This species does not appear to be afraid of divers—on the contrary, it seems to enjoy the attention—and it even tried to sit on the dome port of my camera.Credit: Andrey Nosik/ United Nations World Oceans Day www.unworldoceansday.org
    Wonder: Sustaining What Sustains Us — 2nd PlaceA juvenile pinnate batfishcaptured with a slow shutter speed, a snooted light, and deliberate camera panning to create a sense of motion and drama. Juvenile pinnate batfish are known for their striking black bodies outlined in vibrant orange—a coloration they lose within just a few months as they mature. I encountered this restless subject in the tropical waters of Indonesia’s Lembeh Strait. Capturing this image took patience and persistence over two dives, as these active young fish constantly dart for cover in crevices, making the shot particularly challenging.Credit: Luis Arpa/ United Nations World Oceans Day www.unworldoceansday.org
    #riveting #images #world #oceans #dayphoto
    15 riveting images from the 2025 UN World Oceans Day Photo Competition
    Big and Small Underwater Faces — 3rd Place. Trips to the Antarctic Peninsula always yield amazing encounters with leopard seals. Boldly approaching me and baring his teeth, this individual was keen to point out that this part of Antarctica was his territory. This picture was shot at dusk, resulting in the rather moody atmosphere.   Credit: Lars von Ritter Zahony/ World Ocean’s Day Get the Popular Science daily newsletter💡 Breakthroughs, discoveries, and DIY tips sent every weekday. The striking eye of a humpback whale named Sweet Girl peers at the camera. Just four days later, she would be dead, hit by a speeding boat and one of the 20,000 whales killed by ship strikes each year. Photographer Rachel Moore’s captivating imageof Sweet Girl earned top honors at the 2025 United Nations World Oceans Day Photo Competition. Wonder: Sustaining What Sustains Us — WinnerThis photo, taken in Mo’orea, French Polynesia in 2024, captures the eye of a humpback whale named Sweet Girl, just days before her tragic death. Four days after I captured this intimate moment, she was struck and killed by a fast-moving ship. Her death serves as a heartbreaking reminder of the 20,000 whales lost to ship strikes every year. We are using her story to advocate for stronger protections, petitioning for stricter speed laws around Tahiti and Mo’orea during whale season. I hope Sweet Girl’s legacy will spark real change to protect these incredible animals and prevent further senseless loss.Credit: Rachel Moore/ United Nations World Oceans Day www.unworldoceansday.org Now in its twelfth year, the competition coordinated in collaboration between the UN Division for Ocean Affairs and the Law of the Sea, DivePhotoGuide, Oceanic Global, and  the Intergovernmental Oceanographic Commission of UNESCO. Each year, thousands of underwater photographers submit images that judges award prizes for across four categories: Big and Small Underwater Faces, Underwater Seascapes, Above Water Seascapes, and Wonder: Sustaining What Sustains Us. This year’s winning images include a curious leopard seal, a swarm of jellyfish, and a very grumpy looking Japanese warbonnet. Given our oceans’ perilous state, all competition participants were required to sign a charter of 14 commitments regarding ethics in photography. Underwater Seascapes — Honorable MentionWith only orcas as their natural predators, leopard seals are Antarctica’s most versatile hunters, preying on everything from fish and cephalopods to penguins and other seals. Gentoo penguins are a favored menu item, and leopard seals can be observed patrolling the waters around their colonies. For this shot, I used a split image to capture both worlds: the gentoo penguin colony in the background with the leopard seal on the hunt in the foreground.Credit: Lars von Ritter Zahony/ United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes – WinnerA serene lake cradled by arid dunes, where a gentle stream breathes life into the heart of Mother Earth’s creation: Captured from an airplane, this image reveals the powerful contrasts and hidden beauty where land and ocean meet, reminding us that the ocean is the source of all life and that everything in nature is deeply connected. The location is a remote stretch of coastline near Shark Bay, Western Australia.Credit: Leander Nardin/ United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes — 3rd PlaceParadise Harbour is one of the most beautiful places on the Antarctic Peninsula. When I visited, the sea was extremely calm, and I was lucky enough to witness a wonderfully clear reflection of the Suárez Glacierin the water. The only problem was the waves created by our speedboat, and the only way to capture the perfect reflection was to lie on the bottom of the boat while it moved towards the glacier.Credit: Andrey Nosik/ United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — 3rd Place“La Rapadura” is a natural hidden treasure on the northern coast of Tenerife, in the Spanish territory of the Canary Islands. Only discovered in 1996, it is one of the most astonishing underwater landscapes in the world, consistently ranking among the planet’s best dive sites. These towering columns of basalt are the result of volcanic processes that occurred between 500,000 and a million years ago. The formation was created when a basaltic lava flow reached the ocean, where, upon cooling and solidifying, it contracted, creating natural structures often compared to the pipes of church organs. Located in a region where marine life has been impacted by once common illegal fishing practices, this stunning natural monument has both geological and ecological value, and scientists and underwater photographers are advocating for its protection.Credit: Pedro Carrillo/ United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — WinnerThis year, I had the incredible opportunity to visit a jellyfish lake during a liveaboard trip around southern Raja Ampat, Indonesia. Being surrounded by millions of jellyfish, which have evolved to lose their stinging ability due to the absence of predators, was one of the most breathtaking experiences I’ve ever had.Credit: Dani Escayola/ United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — 2nd PlaceThis shot captures a school of rays resting at a cleaning station in Mauritius, where strong currents once attracted them regularly. Some rays grew accustomed to divers, allowing close encounters like this. Sadly, after the severe bleaching that the reefs here suffered last year, such gatherings have become rare, and I fear I may not witness this again at the same spot.Credit: Gerald Rambert/ United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — 3rd PlaceShot in Cuba’s Jardines de la Reina—a protected shark sanctuary—this image captures a Caribbean reef shark weaving through a group of silky sharks near the surface. Using a slow shutter and strobes as the shark pivoted sharply, the motion blurred into a wave-like arc across its head, lit by the golden hues of sunset. The abundance and behavior of sharks here is a living symbol of what protected oceans can look like.Credit: Steven Lopez/ United Nations World Oceans Day www.unworldoceansday.org  Above Water Seascapes — 2nd PlaceNorthern gannetssoar above the dramatic cliffs of Scotland’s Hermaness National Nature Reserve, their sleek white bodies and black-tipped wings slicing through the Shetland winds. These seabirds, the largest in the North Atlantic, are renowned for their striking plunge-dives, reaching speeds up to 100 kphas they hunt for fish beneath the waves. The cliffs of Hermaness provide ideal nesting sites, with updrafts aiding their take-offs and landings. Each spring, thousands return to this rugged coastline, forming one of the UK’s most significant gannet colonies. It was a major challenge to take photos at the edge of these cliffs at almost 200 meterswith the winds up to 30 kph.Credit: Nur Tucker/ United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes — Honorable MentionA South Atlantic swell breaks on the Dungeons Reef off the Cape Peninsula, South Africa, shot while photographing a big-wave surf session in October 2017. It’s the crescendoing sounds of these breaking swells that always amazes me.Credit: Ken Findlay/ United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — Honorable MentionHumpback whales in their thousands migrate along the Ningaloo Reef in Western Australia every year on the way to and from their calving grounds. In four seasons of swimming with them on the reef here, this is the only encounter I’ve had like this one. This pair of huge adult whales repeatedly spy-hopped alongside us, seeking to interact with and investigate us, leaving me completely breathless. The female in the foreground was much more confident than the male behind and would constantly make close approaches, whilst the male hung back a little, still interested but shy. After more than 10 years working with wildlife in the water, this was one of the best experiences of my life.Credit: Ollie Clarke/ United Nations World Oceans Day www.unworldoceansday.org Big and Small Underwater Faces — 2nd PlaceOn one of my many blackwater dives in Anilao, in the Philippines, my guide and I spotted something moving erratically at a depth of around 20 meters, about 10 to 15 centimeters in size. We quickly realized that it was a rare blanket octopus. As we approached, it opened up its beautiful blanket, revealing its multicolored mantle. I managed to take a few shots before it went on its way. I felt truly privileged to have captured this fascinating deep-sea cephalopod. Among its many unique characteristics, this species exhibits some of the most extreme sexual size-dimorphism in nature, with females weighing up to 40,000 times more than males.Credit: Giacomo Marchione/ United Nations World Oceans Day www.unworldoceansday.org Big and Small Underwater Faces – WinnerThis photo of a Japanese warbonnetwas captured in the Sea of Japan, about 50 milessouthwest of Vladivostok, Russia. I found the ornate fish at a depth of about 30 meters, under the stern of a shipwreck. This species does not appear to be afraid of divers—on the contrary, it seems to enjoy the attention—and it even tried to sit on the dome port of my camera.Credit: Andrey Nosik/ United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — 2nd PlaceA juvenile pinnate batfishcaptured with a slow shutter speed, a snooted light, and deliberate camera panning to create a sense of motion and drama. Juvenile pinnate batfish are known for their striking black bodies outlined in vibrant orange—a coloration they lose within just a few months as they mature. I encountered this restless subject in the tropical waters of Indonesia’s Lembeh Strait. Capturing this image took patience and persistence over two dives, as these active young fish constantly dart for cover in crevices, making the shot particularly challenging.Credit: Luis Arpa/ United Nations World Oceans Day www.unworldoceansday.org #riveting #images #world #oceans #dayphoto
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    15 riveting images from the 2025 UN World Oceans Day Photo Competition
    Big and Small Underwater Faces — 3rd Place. Trips to the Antarctic Peninsula always yield amazing encounters with leopard seals (Hydrurga leptonyx). Boldly approaching me and baring his teeth, this individual was keen to point out that this part of Antarctica was his territory. This picture was shot at dusk, resulting in the rather moody atmosphere.   Credit: Lars von Ritter Zahony (Germany) / World Ocean’s Day Get the Popular Science daily newsletter💡 Breakthroughs, discoveries, and DIY tips sent every weekday. The striking eye of a humpback whale named Sweet Girl peers at the camera. Just four days later, she would be dead, hit by a speeding boat and one of the 20,000 whales killed by ship strikes each year. Photographer Rachel Moore’s captivating image (seen below) of Sweet Girl earned top honors at the 2025 United Nations World Oceans Day Photo Competition. Wonder: Sustaining What Sustains Us — WinnerThis photo, taken in Mo’orea, French Polynesia in 2024, captures the eye of a humpback whale named Sweet Girl, just days before her tragic death. Four days after I captured this intimate moment, she was struck and killed by a fast-moving ship. Her death serves as a heartbreaking reminder of the 20,000 whales lost to ship strikes every year. We are using her story to advocate for stronger protections, petitioning for stricter speed laws around Tahiti and Mo’orea during whale season. I hope Sweet Girl’s legacy will spark real change to protect these incredible animals and prevent further senseless loss.Credit: Rachel Moore (USA) / United Nations World Oceans Day www.unworldoceansday.org Now in its twelfth year, the competition coordinated in collaboration between the UN Division for Ocean Affairs and the Law of the Sea, DivePhotoGuide (DPG), Oceanic Global, and  the Intergovernmental Oceanographic Commission of UNESCO. Each year, thousands of underwater photographers submit images that judges award prizes for across four categories: Big and Small Underwater Faces, Underwater Seascapes, Above Water Seascapes, and Wonder: Sustaining What Sustains Us. This year’s winning images include a curious leopard seal, a swarm of jellyfish, and a very grumpy looking Japanese warbonnet. Given our oceans’ perilous state, all competition participants were required to sign a charter of 14 commitments regarding ethics in photography. Underwater Seascapes — Honorable MentionWith only orcas as their natural predators, leopard seals are Antarctica’s most versatile hunters, preying on everything from fish and cephalopods to penguins and other seals. Gentoo penguins are a favored menu item, and leopard seals can be observed patrolling the waters around their colonies. For this shot, I used a split image to capture both worlds: the gentoo penguin colony in the background with the leopard seal on the hunt in the foreground.Credit: Lars von Ritter Zahony (Germany) / United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes – WinnerA serene lake cradled by arid dunes, where a gentle stream breathes life into the heart of Mother Earth’s creation: Captured from an airplane, this image reveals the powerful contrasts and hidden beauty where land and ocean meet, reminding us that the ocean is the source of all life and that everything in nature is deeply connected. The location is a remote stretch of coastline near Shark Bay, Western Australia.Credit: Leander Nardin (Austria) / United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes — 3rd PlaceParadise Harbour is one of the most beautiful places on the Antarctic Peninsula. When I visited, the sea was extremely calm, and I was lucky enough to witness a wonderfully clear reflection of the Suárez Glacier (aka Petzval Glacier) in the water. The only problem was the waves created by our speedboat, and the only way to capture the perfect reflection was to lie on the bottom of the boat while it moved towards the glacier.Credit: Andrey Nosik (Russia) / United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — 3rd Place“La Rapadura” is a natural hidden treasure on the northern coast of Tenerife, in the Spanish territory of the Canary Islands. Only discovered in 1996, it is one of the most astonishing underwater landscapes in the world, consistently ranking among the planet’s best dive sites. These towering columns of basalt are the result of volcanic processes that occurred between 500,000 and a million years ago. The formation was created when a basaltic lava flow reached the ocean, where, upon cooling and solidifying, it contracted, creating natural structures often compared to the pipes of church organs. Located in a region where marine life has been impacted by once common illegal fishing practices, this stunning natural monument has both geological and ecological value, and scientists and underwater photographers are advocating for its protection. (Model: Yolanda Garcia)Credit: Pedro Carrillo (Spain) / United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — WinnerThis year, I had the incredible opportunity to visit a jellyfish lake during a liveaboard trip around southern Raja Ampat, Indonesia. Being surrounded by millions of jellyfish, which have evolved to lose their stinging ability due to the absence of predators, was one of the most breathtaking experiences I’ve ever had.Credit: Dani Escayola (Spain) / United Nations World Oceans Day www.unworldoceansday.org Underwater Seascapes — 2nd PlaceThis shot captures a school of rays resting at a cleaning station in Mauritius, where strong currents once attracted them regularly. Some rays grew accustomed to divers, allowing close encounters like this. Sadly, after the severe bleaching that the reefs here suffered last year, such gatherings have become rare, and I fear I may not witness this again at the same spot.Credit: Gerald Rambert (Mauritius) / United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — 3rd PlaceShot in Cuba’s Jardines de la Reina—a protected shark sanctuary—this image captures a Caribbean reef shark weaving through a group of silky sharks near the surface. Using a slow shutter and strobes as the shark pivoted sharply, the motion blurred into a wave-like arc across its head, lit by the golden hues of sunset. The abundance and behavior of sharks here is a living symbol of what protected oceans can look like.Credit: Steven Lopez (USA) / United Nations World Oceans Day www.unworldoceansday.org  Above Water Seascapes — 2nd PlaceNorthern gannets (Morus bassanus) soar above the dramatic cliffs of Scotland’s Hermaness National Nature Reserve, their sleek white bodies and black-tipped wings slicing through the Shetland winds. These seabirds, the largest in the North Atlantic, are renowned for their striking plunge-dives, reaching speeds up to 100 kph (60 mph) as they hunt for fish beneath the waves. The cliffs of Hermaness provide ideal nesting sites, with updrafts aiding their take-offs and landings. Each spring, thousands return to this rugged coastline, forming one of the UK’s most significant gannet colonies. It was a major challenge to take photos at the edge of these cliffs at almost 200 meters (650 feet) with the winds up to 30 kph (20 mph).Credit: Nur Tucker (UK/Turkey) / United Nations World Oceans Day www.unworldoceansday.org Above Water Seascapes — Honorable MentionA South Atlantic swell breaks on the Dungeons Reef off the Cape Peninsula, South Africa, shot while photographing a big-wave surf session in October 2017. It’s the crescendoing sounds of these breaking swells that always amazes me.Credit: Ken Findlay (South Africa) / United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — Honorable MentionHumpback whales in their thousands migrate along the Ningaloo Reef in Western Australia every year on the way to and from their calving grounds. In four seasons of swimming with them on the reef here, this is the only encounter I’ve had like this one. This pair of huge adult whales repeatedly spy-hopped alongside us, seeking to interact with and investigate us, leaving me completely breathless. The female in the foreground was much more confident than the male behind and would constantly make close approaches, whilst the male hung back a little, still interested but shy. After more than 10 years working with wildlife in the water, this was one of the best experiences of my life.Credit: Ollie Clarke (UK) / United Nations World Oceans Day www.unworldoceansday.org Big and Small Underwater Faces — 2nd PlaceOn one of my many blackwater dives in Anilao, in the Philippines, my guide and I spotted something moving erratically at a depth of around 20 meters (65 feet), about 10 to 15 centimeters in size. We quickly realized that it was a rare blanket octopus (Tremoctopus sp.). As we approached, it opened up its beautiful blanket, revealing its multicolored mantle. I managed to take a few shots before it went on its way. I felt truly privileged to have captured this fascinating deep-sea cephalopod. Among its many unique characteristics, this species exhibits some of the most extreme sexual size-dimorphism in nature, with females weighing up to 40,000 times more than males.Credit: Giacomo Marchione (Italy) / United Nations World Oceans Day www.unworldoceansday.org Big and Small Underwater Faces – WinnerThis photo of a Japanese warbonnet (Chirolophis japonicus) was captured in the Sea of Japan, about 50 miles (80 kilometers) southwest of Vladivostok, Russia. I found the ornate fish at a depth of about 30 meters (100 feet), under the stern of a shipwreck. This species does not appear to be afraid of divers—on the contrary, it seems to enjoy the attention—and it even tried to sit on the dome port of my camera.Credit: Andrey Nosik (Russia) / United Nations World Oceans Day www.unworldoceansday.org Wonder: Sustaining What Sustains Us — 2nd PlaceA juvenile pinnate batfish (Platax pinnatus) captured with a slow shutter speed, a snooted light, and deliberate camera panning to create a sense of motion and drama. Juvenile pinnate batfish are known for their striking black bodies outlined in vibrant orange—a coloration they lose within just a few months as they mature. I encountered this restless subject in the tropical waters of Indonesia’s Lembeh Strait. Capturing this image took patience and persistence over two dives, as these active young fish constantly dart for cover in crevices, making the shot particularly challenging.Credit: Luis Arpa (Spain) / United Nations World Oceans Day www.unworldoceansday.org
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  • How AI is reshaping the future of healthcare and medical research

    Transcript       
    PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”          
    This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.   
    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?    
    In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.  The book passage I read at the top is from “Chapter 10: The Big Black Bag.” 
    In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.   
    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open. 
    As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.  
    Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home. 
    Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.     
    Here’s my conversation with Bill Gates and Sébastien Bubeck. 
    LEE: Bill, welcome. 
    BILL GATES: Thank you. 
    LEE: Seb … 
    SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here. 
    LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening? 
    And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?  
    GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines. 
    And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.  
    And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weaknessthat, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning. 
    LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that? 
    GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, … 
    LEE: Right.  
    GATES: … that is a bit weird.  
    LEE: Yeah. 
    GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training. 
    LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent. 
    BUBECK: Yes.  
    LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSRto join and start investigating this thing seriously. And the first person I pulled in was you. 
    BUBECK: Yeah. 
    LEE: And so what were your first encounters? Because I actually don’t remember what happened then. 
    BUBECK: Oh, I remember it very well.My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3. 
    I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1. 
    So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair.And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts. 
    So this was really, to me, the first moment where I saw some understanding in those models.  
    LEE: So this was, just to get the timing right, that was before I pulled you into the tent. 
    BUBECK: That was before. That was like a year before. 
    LEE: Right.  
    BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4. 
    So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.  
    So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x. 
    And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?  
    LEE: Yeah.
    BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.  
    LEE:One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine. 
    And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.  
    And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.  
    I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book. 
    But the main purpose of this conversation isn’t to reminisce aboutor indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements. 
    But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today? 
    You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.  
    Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork? 
    GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.  
    It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision. 
    But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view. 
    LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients.Does that make sense to you? 
    BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong? 
    Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.  
    Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them. 
    And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT. And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.  
    Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way. 
    It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine. 
    LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all? 
    GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that. 
    The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa,
    So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.  
    LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking? 
    GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.  
    The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.  
    LEE: Right.  
    GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.  
    LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication. 
    BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE, for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI. 
    It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for. 
    LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes. 
    I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?  
    That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential.What’s up with that? 
    BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back thatversion of GPT-4o, so now we don’t have the sycophant version out there. 
    Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF, where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad. 
    But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model. 
    So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model. 
    LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and … 
    BUBECK: It’s a very difficult, very difficult balance. 
    LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models? 
    GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there. 
    Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?  
    Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there.
    LEE: Yeah.
    GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake. 
    LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on. 
    BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGIthat kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything. 
    That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects.So it’s … I think it’s an important example to have in mind. 
    LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two? 
    BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it. 
    LEE: So we have about three hours of stuff to talk about, but our time is actually running low.
    BUBECK: Yes, yes, yes.  
    LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now? 
    GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.  
    The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities. 
    And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period. 
    LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers? 
    GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them. 
    LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.  
    I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why. 
    BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and seeproduced what you wanted. So I absolutely agree with that.  
    And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini. So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.  
    LEE: Yeah. 
    BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.  
    Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not. 
    Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision. 
    LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist … 
    BUBECK: Yeah.
    LEE: … or an endocrinologist might not.
    BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know.
    LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today? 
    BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later. 
    And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …  
    LEE: Will AI prescribe your medicines? Write your prescriptions? 
    BUBECK: I think yes. I think yes. 
    LEE: OK. Bill? 
    GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate?
    And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelectedjust on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries. 
    You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that. 
    LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.  
    I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.  
    GATES: Yeah. Thanks, you guys. 
    BUBECK: Thank you, Peter. Thanks, Bill. 
    LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.   
    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.  
    And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.  
    One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.  
    HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings. 
    You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.  
    If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.  
    I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.  
    Until next time.  
    #how #reshaping #future #healthcare #medical
    How AI is reshaping the future of healthcare and medical research
    Transcript        PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”           This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?     In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.  The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open.  As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.   Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home.  Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.      Here’s my conversation with Bill Gates and Sébastien Bubeck.  LEE: Bill, welcome.  BILL GATES: Thank you.  LEE: Seb …  SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here.  LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening?  And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?   GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines.  And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.   And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weaknessthat, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning.  LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that?  GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, …  LEE: Right.   GATES: … that is a bit weird.   LEE: Yeah.  GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training.  LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent.  BUBECK: Yes.   LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSRto join and start investigating this thing seriously. And the first person I pulled in was you.  BUBECK: Yeah.  LEE: And so what were your first encounters? Because I actually don’t remember what happened then.  BUBECK: Oh, I remember it very well.My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3.  I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1.  So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair.And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts.  So this was really, to me, the first moment where I saw some understanding in those models.   LEE: So this was, just to get the timing right, that was before I pulled you into the tent.  BUBECK: That was before. That was like a year before.  LEE: Right.   BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4.  So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.   So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x.  And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?   LEE: Yeah. BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.   LEE:One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine.  And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.   And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.   I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book.  But the main purpose of this conversation isn’t to reminisce aboutor indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements.  But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today?  You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.   Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork?  GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.   It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision.  But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view.  LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients.Does that make sense to you?  BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong?  Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.   Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them.  And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT. And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.   Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way.  It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine.  LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all?  GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that.  The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa, So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.   LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking?  GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.   The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.   LEE: Right.   GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.   LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication.  BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE, for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI.  It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for.  LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes.  I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?   That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential.What’s up with that?  BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back thatversion of GPT-4o, so now we don’t have the sycophant version out there.  Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF, where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad.  But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model.  So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model.  LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and …  BUBECK: It’s a very difficult, very difficult balance.  LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models?  GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there.  Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?   Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there. LEE: Yeah. GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake.  LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on.  BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGIthat kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything.  That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects.So it’s … I think it’s an important example to have in mind.  LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two?  BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it.  LEE: So we have about three hours of stuff to talk about, but our time is actually running low. BUBECK: Yes, yes, yes.   LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now?  GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.   The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities.  And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period.  LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers?  GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them.  LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.   I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why.  BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and seeproduced what you wanted. So I absolutely agree with that.   And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini. So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.   LEE: Yeah.  BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.   Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not.  Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision.  LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist …  BUBECK: Yeah. LEE: … or an endocrinologist might not. BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know. LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today?  BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later.  And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …   LEE: Will AI prescribe your medicines? Write your prescriptions?  BUBECK: I think yes. I think yes.  LEE: OK. Bill?  GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate? And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelectedjust on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries.  You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that.  LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.   I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.   GATES: Yeah. Thanks, you guys.  BUBECK: Thank you, Peter. Thanks, Bill.  LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.   And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.   One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.   HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings.  You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.   If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.   I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.   Until next time.   #how #reshaping #future #healthcare #medical
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    How AI is reshaping the future of healthcare and medical research
    Transcript [MUSIC]      [BOOK PASSAGE]   PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”   [END OF BOOK PASSAGE]     [THEME MUSIC]     This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?     In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.   [THEME MUSIC FADES] The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open.  As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.   Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home.  Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.    [TRANSITION MUSIC]   Here’s my conversation with Bill Gates and Sébastien Bubeck.  LEE: Bill, welcome.  BILL GATES: Thank you.  LEE: Seb …  SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here.  LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening?  And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?   GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines.  And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.   And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weakness [LAUGHTER] that, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning.  LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that?  GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, …  LEE: Right.   GATES: … that is a bit weird.   LEE: Yeah.  GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training.  LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent. [LAUGHS]  BUBECK: Yes.   LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSR [Microsoft Research] to join and start investigating this thing seriously. And the first person I pulled in was you.  BUBECK: Yeah.  LEE: And so what were your first encounters? Because I actually don’t remember what happened then.  BUBECK: Oh, I remember it very well. [LAUGHS] My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3.  I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1.  So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair. [LAUGHTER] And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts.  So this was really, to me, the first moment where I saw some understanding in those models.   LEE: So this was, just to get the timing right, that was before I pulled you into the tent.  BUBECK: That was before. That was like a year before.  LEE: Right.   BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4.  So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.   So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x.  And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?   LEE: Yeah. BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.   LEE: [LAUGHS] One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine.  And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.   And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.   I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book.  But the main purpose of this conversation isn’t to reminisce about [LAUGHS] or indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements.  But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today?  You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.   Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork?  GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.   It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision.  But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view.  LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients. [LAUGHTER] Does that make sense to you?  BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong?  Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.   Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them.  And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT (opens in new tab). And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.   Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way.  It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine.  LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all?  GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that.  The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa, So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.   LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking?  GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.   The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.   LEE: Right.   GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.   LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication.  BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE [United States Medical Licensing Examination], for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI.  It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for.  LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes.  I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?   That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential. [LAUGHTER] What’s up with that?  BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back that [LAUGHS] version of GPT-4o, so now we don’t have the sycophant version out there.  Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF [reinforcement learning from human feedback], where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad.  But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model.  So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model.  LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and …  BUBECK: It’s a very difficult, very difficult balance.  LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models?  GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there.  Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?   Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there. LEE: Yeah. GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake.  LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on.  BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGI [artificial general intelligence] that kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything.  That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects. [LAUGHTER] So it’s … I think it’s an important example to have in mind.  LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two?  BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it.  LEE: So we have about three hours of stuff to talk about, but our time is actually running low. BUBECK: Yes, yes, yes.   LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now?  GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.   The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities.  And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period.  LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers?  GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them.  LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.   I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why.  BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and see [if you have] produced what you wanted. So I absolutely agree with that.   And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini (opens in new tab). So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.   LEE: Yeah.  BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.   Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not.  Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision.  LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist …  BUBECK: Yeah. LEE: … or an endocrinologist might not. BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know. LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today?  BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later.  And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …   LEE: Will AI prescribe your medicines? Write your prescriptions?  BUBECK: I think yes. I think yes.  LEE: OK. Bill?  GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate? And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelected [LAUGHTER] just on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries.  You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that.  LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.   I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.  [TRANSITION MUSIC]  GATES: Yeah. Thanks, you guys.  BUBECK: Thank you, Peter. Thanks, Bill.  LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.   And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.   One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.   HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings.  You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.   If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.  [THEME MUSIC]  I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.   Until next time.   [MUSIC FADES]
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  • Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals

    Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals
    She spent nearly 40 years taking theater and dance pictures, providing glimpses behind the scenes and creating images that the public couldn’t otherwise access

    Stephanie Rudig

    - Freelance Writer

    June 11, 2025

    Photographer Martha Swope sitting on a floor covered with prints of her photos in 1987
    Andrea Legge / © NYPL

    Martha Swope wanted to be a dancer. She moved from her home state of Texas to New York to attend the School of American Ballet, hoping to start a career in dance. Swope also happened to be an amateur photographer. So, in 1957, a fellow classmate invited her to bring her camera and document rehearsals for a little theater show he was working on. The classmate was director and choreographer Jerome Robbins, and the show was West Side Story.
    One of those rehearsal shots ended up in Life magazine, and Swope quickly started getting professional bookings. It’s notoriously tough to make it on Broadway, but through photography, Swope carved out a career capturing theater and dance. Over the course of nearly four decades, she photographed hundreds more rehearsals, productions and promotional studio shots.

    Unidentified male chorus members dancing during rehearsals for musical West Side Story in 1957

    Martha Swope / © NYPL

    At a time when live performances were not often or easily captured, Swope’s photographs caught the animated moments and distilled the essence of a show into a single image: André De Shields clad in a jumpsuit as the title character in The Wiz, Patti LuPone with her arms raised overhead in Evita, the cast of Cats leaping in feline formations, a close-up of a forlorn Sheryl Lee Ralph in Dreamgirls and the row of dancers obscuring their faces with their headshots in A Chorus Line were all captured by Swope’s camera. She was also the house photographer for the New York City Ballet and the Martha Graham Dance Company and photographed other major dance companies such as the Ailey School.
    Her vision of the stage became fairly ubiquitous, with Playbill reporting that in the late 1970s, two-thirds of Broadway productions were photographed by Swope, meaning her work dominated theater and dance coverage. Carol Rosegg was early in her photography career when she heard that Swope was looking for an assistant. “I didn't frankly even know who she was,” Rosegg says. “Then the press agent who told me said, ‘Pick up any New York Times and you’ll find out.’”
    Swope’s background as a dancer likely equipped her to press the shutter at the exact right moment to capture movement, and to know when everyone on stage was precisely posed. She taught herself photography and early on used a Brownie camera, a simple box model made by Kodak. “She was what she described as ‘a dancer with a Brownie,’” says Barbara Stratyner, a historian of the performing arts who curated exhibitions of Swope’s work at the New York Public Library.

    An ensemble of dancers in rehearsal for the stage production Cats in 1982

    Martha Swope / © NYPL

    “Dance was her first love,” Rosegg says. “She knew everything about dance. She would never use a photo of a dancer whose foot was wrong; the feet had to be perfect.”
    According to Rosegg, once the photo subjects knew she was shooting, “the anxiety level came down a little bit.” They knew that they’d look good in the resulting photos, and they likely trusted her intuition as a fellow dancer. Swope moved with the bearing of a dancer and often stood with her feet in ballet’s fourth position while she shot. She continued to take dance classes throughout her life, including at the prestigious Martha Graham School. Stratyner says, “As Graham got older,was, I think, the only person who was allowed to photograph rehearsals, because Graham didn’t want rehearsals shown.”
    Photographic technology and the theater and dance landscapes evolved greatly over the course of Swope’s career. Rosegg points out that at the start of her own career, cameras didn’t even automatically advance the film after each shot. She explains the delicate nature of working with film, saying, “When you were shooting film, you actually had to compose, because you had 35 shots and then you had to change your film.” Swope also worked during a period of changing over from all black-and-white photos to a mixture of black-and-white and color photography. Rosegg notes that simultaneously, Swope would shoot black-and-white, and she herself would shoot color. Looking at Swope’s portfolio is also an examination of increasingly crisp photo production. Advances in photography made shooting in the dark or capturing subjects under blinding stage lights easier, and they allowed for better zooming in from afar.

    Martha Graham rehearses dancer Takako Asakawa and others in Heretic, a dance work choreographed by Graham, in 1986

    Martha Swope / © NYPL

    It’s much more common nowadays to get a look behind the curtain of theater productions via social media. “The theater photographers of today need to supply so much content,” Rosegg says. “We didn’t have any of that, and getting to go backstage was kind of a big deal.”
    Photographers coming to document a rehearsal once might have been seen as an intrusion, but now, as Rosegg puts it, “everybody is desperate for you to come, and if you’re not there, they’re shooting it on their iPhone.”
    Even with exclusive behind-the-scenes access to the hottest tickets in town and the biggest stars of the day, Swope remained unpretentious. She lived and worked in a brownstone with her apartment above her studio, where the film was developed in a closet and the bathroom served as a darkroom. Rosegg recalls that a phone sat in the darkroom so they could be reached while printing, and she would be amazed at the big-name producers and theater glitterati who rang in while she was making prints in an unventilated space.

    From left to right: Paul Winfield, Ruby Dee, Marsha Jackson and Denzel Washington in the stage production Checkmates in 1988

    Martha Swope / © NYPL

    Swope’s approachability extended to how she chose to preserve her work. She originally sold her body of work to Time Life, and, according to Stratyner, she was unhappy with the way the photos became relatively inaccessible. She took back the rights to her collection and donated it to the New York Public Library, where many photos can be accessed by researchers in person, and the entire array of photos is available online to the public in the Digital Collections. Searching “Martha Swope” yields over 50,000 items from more than 800 productions, featuring a huge variety of figures, from a white-suited John Travolta busting a disco move in Saturday Night Fever to Andrew Lloyd Webber with Nancy Reagan at a performance of Phantom of the Opera.
    Swope’s extensive career was recognized in 2004 with a special Tony Award, a Tony Honors for Excellence in Theater, which are given intermittently to notable figures in theater who operate outside of traditional awards categories. She also received a lifetime achievement award from the League of Professional Theater Women in 2007. Though she retired in 1994 and died in 2017, her work still reverberates through dance and Broadway history today. For decades, she captured the fleeting moments of theater that would otherwise never be seen by the public. And her passion was clear and straightforward. As she once told an interviewer: “I’m not interested in what’s going on on my side of the camera. I’m interested in what’s happening on the other side.”

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    #meet #martha #swope #legendary #broadway
    Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals
    Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals She spent nearly 40 years taking theater and dance pictures, providing glimpses behind the scenes and creating images that the public couldn’t otherwise access Stephanie Rudig - Freelance Writer June 11, 2025 Photographer Martha Swope sitting on a floor covered with prints of her photos in 1987 Andrea Legge / © NYPL Martha Swope wanted to be a dancer. She moved from her home state of Texas to New York to attend the School of American Ballet, hoping to start a career in dance. Swope also happened to be an amateur photographer. So, in 1957, a fellow classmate invited her to bring her camera and document rehearsals for a little theater show he was working on. The classmate was director and choreographer Jerome Robbins, and the show was West Side Story. One of those rehearsal shots ended up in Life magazine, and Swope quickly started getting professional bookings. It’s notoriously tough to make it on Broadway, but through photography, Swope carved out a career capturing theater and dance. Over the course of nearly four decades, she photographed hundreds more rehearsals, productions and promotional studio shots. Unidentified male chorus members dancing during rehearsals for musical West Side Story in 1957 Martha Swope / © NYPL At a time when live performances were not often or easily captured, Swope’s photographs caught the animated moments and distilled the essence of a show into a single image: André De Shields clad in a jumpsuit as the title character in The Wiz, Patti LuPone with her arms raised overhead in Evita, the cast of Cats leaping in feline formations, a close-up of a forlorn Sheryl Lee Ralph in Dreamgirls and the row of dancers obscuring their faces with their headshots in A Chorus Line were all captured by Swope’s camera. She was also the house photographer for the New York City Ballet and the Martha Graham Dance Company and photographed other major dance companies such as the Ailey School. Her vision of the stage became fairly ubiquitous, with Playbill reporting that in the late 1970s, two-thirds of Broadway productions were photographed by Swope, meaning her work dominated theater and dance coverage. Carol Rosegg was early in her photography career when she heard that Swope was looking for an assistant. “I didn't frankly even know who she was,” Rosegg says. “Then the press agent who told me said, ‘Pick up any New York Times and you’ll find out.’” Swope’s background as a dancer likely equipped her to press the shutter at the exact right moment to capture movement, and to know when everyone on stage was precisely posed. She taught herself photography and early on used a Brownie camera, a simple box model made by Kodak. “She was what she described as ‘a dancer with a Brownie,’” says Barbara Stratyner, a historian of the performing arts who curated exhibitions of Swope’s work at the New York Public Library. An ensemble of dancers in rehearsal for the stage production Cats in 1982 Martha Swope / © NYPL “Dance was her first love,” Rosegg says. “She knew everything about dance. She would never use a photo of a dancer whose foot was wrong; the feet had to be perfect.” According to Rosegg, once the photo subjects knew she was shooting, “the anxiety level came down a little bit.” They knew that they’d look good in the resulting photos, and they likely trusted her intuition as a fellow dancer. Swope moved with the bearing of a dancer and often stood with her feet in ballet’s fourth position while she shot. She continued to take dance classes throughout her life, including at the prestigious Martha Graham School. Stratyner says, “As Graham got older,was, I think, the only person who was allowed to photograph rehearsals, because Graham didn’t want rehearsals shown.” Photographic technology and the theater and dance landscapes evolved greatly over the course of Swope’s career. Rosegg points out that at the start of her own career, cameras didn’t even automatically advance the film after each shot. She explains the delicate nature of working with film, saying, “When you were shooting film, you actually had to compose, because you had 35 shots and then you had to change your film.” Swope also worked during a period of changing over from all black-and-white photos to a mixture of black-and-white and color photography. Rosegg notes that simultaneously, Swope would shoot black-and-white, and she herself would shoot color. Looking at Swope’s portfolio is also an examination of increasingly crisp photo production. Advances in photography made shooting in the dark or capturing subjects under blinding stage lights easier, and they allowed for better zooming in from afar. Martha Graham rehearses dancer Takako Asakawa and others in Heretic, a dance work choreographed by Graham, in 1986 Martha Swope / © NYPL It’s much more common nowadays to get a look behind the curtain of theater productions via social media. “The theater photographers of today need to supply so much content,” Rosegg says. “We didn’t have any of that, and getting to go backstage was kind of a big deal.” Photographers coming to document a rehearsal once might have been seen as an intrusion, but now, as Rosegg puts it, “everybody is desperate for you to come, and if you’re not there, they’re shooting it on their iPhone.” Even with exclusive behind-the-scenes access to the hottest tickets in town and the biggest stars of the day, Swope remained unpretentious. She lived and worked in a brownstone with her apartment above her studio, where the film was developed in a closet and the bathroom served as a darkroom. Rosegg recalls that a phone sat in the darkroom so they could be reached while printing, and she would be amazed at the big-name producers and theater glitterati who rang in while she was making prints in an unventilated space. From left to right: Paul Winfield, Ruby Dee, Marsha Jackson and Denzel Washington in the stage production Checkmates in 1988 Martha Swope / © NYPL Swope’s approachability extended to how she chose to preserve her work. She originally sold her body of work to Time Life, and, according to Stratyner, she was unhappy with the way the photos became relatively inaccessible. She took back the rights to her collection and donated it to the New York Public Library, where many photos can be accessed by researchers in person, and the entire array of photos is available online to the public in the Digital Collections. Searching “Martha Swope” yields over 50,000 items from more than 800 productions, featuring a huge variety of figures, from a white-suited John Travolta busting a disco move in Saturday Night Fever to Andrew Lloyd Webber with Nancy Reagan at a performance of Phantom of the Opera. Swope’s extensive career was recognized in 2004 with a special Tony Award, a Tony Honors for Excellence in Theater, which are given intermittently to notable figures in theater who operate outside of traditional awards categories. She also received a lifetime achievement award from the League of Professional Theater Women in 2007. Though she retired in 1994 and died in 2017, her work still reverberates through dance and Broadway history today. For decades, she captured the fleeting moments of theater that would otherwise never be seen by the public. And her passion was clear and straightforward. As she once told an interviewer: “I’m not interested in what’s going on on my side of the camera. I’m interested in what’s happening on the other side.” Get the latest Travel & Culture stories in your inbox. #meet #martha #swope #legendary #broadway
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    Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals
    Meet Martha Swope, the Legendary Broadway Photographer Who Captured Iconic Moments From Hundreds of Productions and Rehearsals She spent nearly 40 years taking theater and dance pictures, providing glimpses behind the scenes and creating images that the public couldn’t otherwise access Stephanie Rudig - Freelance Writer June 11, 2025 Photographer Martha Swope sitting on a floor covered with prints of her photos in 1987 Andrea Legge / © NYPL Martha Swope wanted to be a dancer. She moved from her home state of Texas to New York to attend the School of American Ballet, hoping to start a career in dance. Swope also happened to be an amateur photographer. So, in 1957, a fellow classmate invited her to bring her camera and document rehearsals for a little theater show he was working on. The classmate was director and choreographer Jerome Robbins, and the show was West Side Story. One of those rehearsal shots ended up in Life magazine, and Swope quickly started getting professional bookings. It’s notoriously tough to make it on Broadway, but through photography, Swope carved out a career capturing theater and dance. Over the course of nearly four decades, she photographed hundreds more rehearsals, productions and promotional studio shots. Unidentified male chorus members dancing during rehearsals for musical West Side Story in 1957 Martha Swope / © NYPL At a time when live performances were not often or easily captured, Swope’s photographs caught the animated moments and distilled the essence of a show into a single image: André De Shields clad in a jumpsuit as the title character in The Wiz, Patti LuPone with her arms raised overhead in Evita, the cast of Cats leaping in feline formations, a close-up of a forlorn Sheryl Lee Ralph in Dreamgirls and the row of dancers obscuring their faces with their headshots in A Chorus Line were all captured by Swope’s camera. She was also the house photographer for the New York City Ballet and the Martha Graham Dance Company and photographed other major dance companies such as the Ailey School. Her vision of the stage became fairly ubiquitous, with Playbill reporting that in the late 1970s, two-thirds of Broadway productions were photographed by Swope, meaning her work dominated theater and dance coverage. Carol Rosegg was early in her photography career when she heard that Swope was looking for an assistant. “I didn't frankly even know who she was,” Rosegg says. “Then the press agent who told me said, ‘Pick up any New York Times and you’ll find out.’” Swope’s background as a dancer likely equipped her to press the shutter at the exact right moment to capture movement, and to know when everyone on stage was precisely posed. She taught herself photography and early on used a Brownie camera, a simple box model made by Kodak. “She was what she described as ‘a dancer with a Brownie,’” says Barbara Stratyner, a historian of the performing arts who curated exhibitions of Swope’s work at the New York Public Library. An ensemble of dancers in rehearsal for the stage production Cats in 1982 Martha Swope / © NYPL “Dance was her first love,” Rosegg says. “She knew everything about dance. She would never use a photo of a dancer whose foot was wrong; the feet had to be perfect.” According to Rosegg, once the photo subjects knew she was shooting, “the anxiety level came down a little bit.” They knew that they’d look good in the resulting photos, and they likely trusted her intuition as a fellow dancer. Swope moved with the bearing of a dancer and often stood with her feet in ballet’s fourth position while she shot. She continued to take dance classes throughout her life, including at the prestigious Martha Graham School. Stratyner says, “As Graham got older, [Swope] was, I think, the only person who was allowed to photograph rehearsals, because Graham didn’t want rehearsals shown.” Photographic technology and the theater and dance landscapes evolved greatly over the course of Swope’s career. Rosegg points out that at the start of her own career, cameras didn’t even automatically advance the film after each shot. She explains the delicate nature of working with film, saying, “When you were shooting film, you actually had to compose, because you had 35 shots and then you had to change your film.” Swope also worked during a period of changing over from all black-and-white photos to a mixture of black-and-white and color photography. Rosegg notes that simultaneously, Swope would shoot black-and-white, and she herself would shoot color. Looking at Swope’s portfolio is also an examination of increasingly crisp photo production. Advances in photography made shooting in the dark or capturing subjects under blinding stage lights easier, and they allowed for better zooming in from afar. Martha Graham rehearses dancer Takako Asakawa and others in Heretic, a dance work choreographed by Graham, in 1986 Martha Swope / © NYPL It’s much more common nowadays to get a look behind the curtain of theater productions via social media. “The theater photographers of today need to supply so much content,” Rosegg says. “We didn’t have any of that, and getting to go backstage was kind of a big deal.” Photographers coming to document a rehearsal once might have been seen as an intrusion, but now, as Rosegg puts it, “everybody is desperate for you to come, and if you’re not there, they’re shooting it on their iPhone.” Even with exclusive behind-the-scenes access to the hottest tickets in town and the biggest stars of the day, Swope remained unpretentious. She lived and worked in a brownstone with her apartment above her studio, where the film was developed in a closet and the bathroom served as a darkroom. Rosegg recalls that a phone sat in the darkroom so they could be reached while printing, and she would be amazed at the big-name producers and theater glitterati who rang in while she was making prints in an unventilated space. From left to right: Paul Winfield, Ruby Dee, Marsha Jackson and Denzel Washington in the stage production Checkmates in 1988 Martha Swope / © NYPL Swope’s approachability extended to how she chose to preserve her work. She originally sold her body of work to Time Life, and, according to Stratyner, she was unhappy with the way the photos became relatively inaccessible. She took back the rights to her collection and donated it to the New York Public Library, where many photos can be accessed by researchers in person, and the entire array of photos is available online to the public in the Digital Collections. Searching “Martha Swope” yields over 50,000 items from more than 800 productions, featuring a huge variety of figures, from a white-suited John Travolta busting a disco move in Saturday Night Fever to Andrew Lloyd Webber with Nancy Reagan at a performance of Phantom of the Opera. Swope’s extensive career was recognized in 2004 with a special Tony Award, a Tony Honors for Excellence in Theater, which are given intermittently to notable figures in theater who operate outside of traditional awards categories. She also received a lifetime achievement award from the League of Professional Theater Women in 2007. Though she retired in 1994 and died in 2017, her work still reverberates through dance and Broadway history today. For decades, she captured the fleeting moments of theater that would otherwise never be seen by the public. And her passion was clear and straightforward. As she once told an interviewer: “I’m not interested in what’s going on on my side of the camera. I’m interested in what’s happening on the other side.” Get the latest Travel & Culture stories in your inbox.
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