• Would you switch browsers for a chatbot?

    Hi, friends! Welcome to Installer No. 87, your guide to the best and Verge-iest stuff in the world.This week, I’ve been reading about Sabrina Carpenter and Khaby Lame and intimacy coordinators, finally making a dent in Barbarians at the Gate, watching all the Ben Schwartz and Friends I can find on YouTube, planning my days with the new Finalist beta, recklessly installing all the Apple developer betas after WWDC, thoroughly enjoying Dakota Johnson’s current press tour, and trying to clear all my inboxes before I go on parental leave. It’s… going.I also have for you a much-awaited new browser, a surprise update to a great photo editor, a neat trailer for a meh-looking movie, a classic Steve Jobs speech, and much more. Slightly shorter issue this week, sorry; there’s just a lot going on, but I didn’t want to leave y’all hanging entirely. Oh, and: we’ll be off next week, for Juneteenth, vacation, and general summer chaos reasons. We’ll be back in full force after that, though! Let’s get into it.The DropDia. I know there are a lot of Arc fans here in the Installerverse, and I know you, like me, will have a lot of feelings about the company’s new and extremely AI-focused browser. Personally, I don’t see leaving Arc anytime soon, but there are some really fascinating ideasin Dia already. Snapseed 3.0. I completely forgot Snapseed even existed, and now here’s a really nice update with a bunch of new editing tools and a nice new redesign! As straightforward photo editors go, this is one of the better ones. The new version is only on iOS right now, but I assume it’s heading to Android shortly.“I Tried To Make Something In America.” I was first turned onto the story of the Smarter Scrubber by a great Search Engine episode, and this is a great companion to the story about what it really takes to bring manufacturing back to the US. And why it’s hard to justify.. That link, and the trailer, will only do anything for you if you have a newer iPhone. But even if you don’t care about the movie, the trailer — which actually buzzes in sync with the car’s rumbles and revs — is just really, really cool. Android 16. You can’t get the cool, colorful new look just yet or the desktop mode I am extremely excited about — there’s a lot of good stuff in Android 16 but most of it is coming later. Still, Live Updates look good, and there’s some helpful accessibility stuff, as well.The Infinite Machine Olto. I am such a sucker for any kind of futuristic-looking electric scooter, and this one really hits the sweet spot. Part moped, part e-bike, all Blade Runner vibes. If it wasn’t then I would’ve probably ordered one already.The Fujifilm X-E5. I kept wondering why Fujifilm didn’t just make, like, a hundred different great-looking cameras at every imaginable price because everyone wants a camera this cool. Well, here we are! It’s a spin on the X100VI but with interchangeable lenses and a few power-user features. All my photographer friends are going to want this.Call Her Alex. I confess I’m no Call Her Daddy diehard, but I found this two-part doc on Alex Cooper really interesting. Cooper’s story is all about understanding people, the internet, and what it means to feel connected now. It’s all very low-stakes and somehow also existential? It’s only two parts, you should watch it.“Steve Jobs - 2005 Stanford Commencement Address.” For the 20th anniversary of Jobs’ famousspeech, the Steve Jobs Archive put together a big package of stories, notes, and other materials around the speech. Plus, a newly high-def version of the video. This one’s always worth the 15 minutes.Dune: Awakening. Dune has ascended to the rare territory of “I will check out anything from this franchise, ever, no questions asked.” This game is big on open-world survival and ornithopters, too, so it’s even more my kind of thing. And it’s apparently punishingly difficult in spots.CrowdsourcedHere’s what the Installer community is into this week. I want to know what you’re into right now as well! Email installer@theverge.com or message me on Signal — @davidpierce.11 — with your recommendations for anything and everything, and we’ll feature some of our favorites here every week. For even more great recommendations, check out the replies to this post on Threads and this post on Bluesky.“I had tried the paper planner in the leather Paper Republic journal but since have moved onto the Remarkable Paper Pro color e-ink device which takes everything you like about paper but makes it editable and color coded. Combine this with a Remarkable planner in PDF format off of Etsy and you are golden.” — Jason“I started reading a manga series from content creator Cory Kenshin called Monsters We Make. So far, I love it. Already preordered Vol. 2.” — Rob“I recently went down the third party controller rabbit hole after my trusty adapted Xbox One controller finally kicked the bucket, and I wanted something I could use across my PC, phone, handheld, Switch, etc. I’ve been playing with the GameSir Cyclone 2 for a few weeks, and it feels really deluxe. The thumbsticks are impossibly smooth and accurate thanks to its TMR joysticks. The face buttons took a second for my brain to adjust to; the short travel distance initially registered as mushy, but once I stopped trying to pound the buttons like I was at the arcade, I found the subtle mechanical click super satisfying.” — Sam“The Apple TV Plus miniseries Long Way Home. It’s Ewan McGregor and Charley Boorman’s fourth Long Way series. This time they are touring some European countries on vintage bikes that they fixed, and it’s such a light-hearted show from two really down to earth humans. Connecting with other people in different cultures and seeing their journey is such a treat!” — Esmael“Podcast recommendation: Devil and the Deep Blue Sea by Christianity Today. A deep dive into the Satanic Panic of the 80’s and 90’s.” — Drew“Splatoon 3and the new How to Train Your Dragon.” — Aaron“I can’t put Mario Kart World down. When I get tired of the intense Knockout Tour mode I go to Free Roam and try to knock out P-Switch challenges, some of which are really tough! I’m obsessed.” — Dave“Fable, a cool app for finding books with virtual book clubs. It’s the closest to a more cozy online bookstore with more honest reviews. I just wish you could click on the author’s name to see their other books.” — Astrid“This is the Summer Games Fest weekand there are a TON of game demos to try out on Steam. One that has caught my attention / play time the most is Wildgate. It’s a team based spaceship shooter where ship crews battle and try to escape with a powerful artifact.” — Sean“Battlefront 2 is back for some reason. Still looks great.” — IanSigning offI have long been fascinated by weather forecasting. I recommend Andrew Blum’s book, The Weather Machine, to people all the time, as a way to understand both how we learned to predict the weather and why it’s a literally culture-changing thing to be able to do so. And if you want to make yourself so, so angry, there’s a whole chunk of Michael Lewis’s book, The Fifth Risk, about how a bunch of companies managed to basically privatize forecasts… based on government data. The weather is a huge business, an extremely powerful political force, and even more important to our way of life than we realize. And we’re really good at predicting the weather!I’ve also been hearing for years that weather forecasting is a perfect use for AI. It’s all about vast quantities of historical data, tiny fluctuations in readings, and finding patterns that often don’t want to be found. So, of course, as soon as I read my colleague Justine Calma’s story about a new Google project called Weather Lab, I spent the next hour poking through the data to see how well DeepMind managed to predict and track recent storms. It’s deeply wonky stuff, but it’s cool to see Big Tech trying to figure out Mother Nature — and almost getting it right. Almost.See you next week!See More:
    #would #you #switch #browsers #chatbot
    Would you switch browsers for a chatbot?
    Hi, friends! Welcome to Installer No. 87, your guide to the best and Verge-iest stuff in the world.This week, I’ve been reading about Sabrina Carpenter and Khaby Lame and intimacy coordinators, finally making a dent in Barbarians at the Gate, watching all the Ben Schwartz and Friends I can find on YouTube, planning my days with the new Finalist beta, recklessly installing all the Apple developer betas after WWDC, thoroughly enjoying Dakota Johnson’s current press tour, and trying to clear all my inboxes before I go on parental leave. It’s… going.I also have for you a much-awaited new browser, a surprise update to a great photo editor, a neat trailer for a meh-looking movie, a classic Steve Jobs speech, and much more. Slightly shorter issue this week, sorry; there’s just a lot going on, but I didn’t want to leave y’all hanging entirely. Oh, and: we’ll be off next week, for Juneteenth, vacation, and general summer chaos reasons. We’ll be back in full force after that, though! Let’s get into it.The DropDia. I know there are a lot of Arc fans here in the Installerverse, and I know you, like me, will have a lot of feelings about the company’s new and extremely AI-focused browser. Personally, I don’t see leaving Arc anytime soon, but there are some really fascinating ideasin Dia already. Snapseed 3.0. I completely forgot Snapseed even existed, and now here’s a really nice update with a bunch of new editing tools and a nice new redesign! As straightforward photo editors go, this is one of the better ones. The new version is only on iOS right now, but I assume it’s heading to Android shortly.“I Tried To Make Something In America.” I was first turned onto the story of the Smarter Scrubber by a great Search Engine episode, and this is a great companion to the story about what it really takes to bring manufacturing back to the US. And why it’s hard to justify.. That link, and the trailer, will only do anything for you if you have a newer iPhone. But even if you don’t care about the movie, the trailer — which actually buzzes in sync with the car’s rumbles and revs — is just really, really cool. Android 16. You can’t get the cool, colorful new look just yet or the desktop mode I am extremely excited about — there’s a lot of good stuff in Android 16 but most of it is coming later. Still, Live Updates look good, and there’s some helpful accessibility stuff, as well.The Infinite Machine Olto. I am such a sucker for any kind of futuristic-looking electric scooter, and this one really hits the sweet spot. Part moped, part e-bike, all Blade Runner vibes. If it wasn’t then I would’ve probably ordered one already.The Fujifilm X-E5. I kept wondering why Fujifilm didn’t just make, like, a hundred different great-looking cameras at every imaginable price because everyone wants a camera this cool. Well, here we are! It’s a spin on the X100VI but with interchangeable lenses and a few power-user features. All my photographer friends are going to want this.Call Her Alex. I confess I’m no Call Her Daddy diehard, but I found this two-part doc on Alex Cooper really interesting. Cooper’s story is all about understanding people, the internet, and what it means to feel connected now. It’s all very low-stakes and somehow also existential? It’s only two parts, you should watch it.“Steve Jobs - 2005 Stanford Commencement Address.” For the 20th anniversary of Jobs’ famousspeech, the Steve Jobs Archive put together a big package of stories, notes, and other materials around the speech. Plus, a newly high-def version of the video. This one’s always worth the 15 minutes.Dune: Awakening. Dune has ascended to the rare territory of “I will check out anything from this franchise, ever, no questions asked.” This game is big on open-world survival and ornithopters, too, so it’s even more my kind of thing. And it’s apparently punishingly difficult in spots.CrowdsourcedHere’s what the Installer community is into this week. I want to know what you’re into right now as well! Email installer@theverge.com or message me on Signal — @davidpierce.11 — with your recommendations for anything and everything, and we’ll feature some of our favorites here every week. For even more great recommendations, check out the replies to this post on Threads and this post on Bluesky.“I had tried the paper planner in the leather Paper Republic journal but since have moved onto the Remarkable Paper Pro color e-ink device which takes everything you like about paper but makes it editable and color coded. Combine this with a Remarkable planner in PDF format off of Etsy and you are golden.” — Jason“I started reading a manga series from content creator Cory Kenshin called Monsters We Make. So far, I love it. Already preordered Vol. 2.” — Rob“I recently went down the third party controller rabbit hole after my trusty adapted Xbox One controller finally kicked the bucket, and I wanted something I could use across my PC, phone, handheld, Switch, etc. I’ve been playing with the GameSir Cyclone 2 for a few weeks, and it feels really deluxe. The thumbsticks are impossibly smooth and accurate thanks to its TMR joysticks. The face buttons took a second for my brain to adjust to; the short travel distance initially registered as mushy, but once I stopped trying to pound the buttons like I was at the arcade, I found the subtle mechanical click super satisfying.” — Sam“The Apple TV Plus miniseries Long Way Home. It’s Ewan McGregor and Charley Boorman’s fourth Long Way series. This time they are touring some European countries on vintage bikes that they fixed, and it’s such a light-hearted show from two really down to earth humans. Connecting with other people in different cultures and seeing their journey is such a treat!” — Esmael“Podcast recommendation: Devil and the Deep Blue Sea by Christianity Today. A deep dive into the Satanic Panic of the 80’s and 90’s.” — Drew“Splatoon 3and the new How to Train Your Dragon.” — Aaron“I can’t put Mario Kart World down. When I get tired of the intense Knockout Tour mode I go to Free Roam and try to knock out P-Switch challenges, some of which are really tough! I’m obsessed.” — Dave“Fable, a cool app for finding books with virtual book clubs. It’s the closest to a more cozy online bookstore with more honest reviews. I just wish you could click on the author’s name to see their other books.” — Astrid“This is the Summer Games Fest weekand there are a TON of game demos to try out on Steam. One that has caught my attention / play time the most is Wildgate. It’s a team based spaceship shooter where ship crews battle and try to escape with a powerful artifact.” — Sean“Battlefront 2 is back for some reason. Still looks great.” — IanSigning offI have long been fascinated by weather forecasting. I recommend Andrew Blum’s book, The Weather Machine, to people all the time, as a way to understand both how we learned to predict the weather and why it’s a literally culture-changing thing to be able to do so. And if you want to make yourself so, so angry, there’s a whole chunk of Michael Lewis’s book, The Fifth Risk, about how a bunch of companies managed to basically privatize forecasts… based on government data. The weather is a huge business, an extremely powerful political force, and even more important to our way of life than we realize. And we’re really good at predicting the weather!I’ve also been hearing for years that weather forecasting is a perfect use for AI. It’s all about vast quantities of historical data, tiny fluctuations in readings, and finding patterns that often don’t want to be found. So, of course, as soon as I read my colleague Justine Calma’s story about a new Google project called Weather Lab, I spent the next hour poking through the data to see how well DeepMind managed to predict and track recent storms. It’s deeply wonky stuff, but it’s cool to see Big Tech trying to figure out Mother Nature — and almost getting it right. Almost.See you next week!See More: #would #you #switch #browsers #chatbot
    WWW.THEVERGE.COM
    Would you switch browsers for a chatbot?
    Hi, friends! Welcome to Installer No. 87, your guide to the best and Verge-iest stuff in the world. (If you’re new here, welcome, happy It’s Officially Too Hot Now Week, and also you can read all the old editions at the Installer homepage.) This week, I’ve been reading about Sabrina Carpenter and Khaby Lame and intimacy coordinators, finally making a dent in Barbarians at the Gate, watching all the Ben Schwartz and Friends I can find on YouTube, planning my days with the new Finalist beta, recklessly installing all the Apple developer betas after WWDC, thoroughly enjoying Dakota Johnson’s current press tour, and trying to clear all my inboxes before I go on parental leave. It’s… going.I also have for you a much-awaited new browser, a surprise update to a great photo editor, a neat trailer for a meh-looking movie, a classic Steve Jobs speech, and much more. Slightly shorter issue this week, sorry; there’s just a lot going on, but I didn’t want to leave y’all hanging entirely. Oh, and: we’ll be off next week, for Juneteenth, vacation, and general summer chaos reasons. We’ll be back in full force after that, though! Let’s get into it.(As always, the best part of Installer is your ideas and tips. What do you want to know more about? What awesome tricks do you know that everyone else should? What app should everyone be using? Tell me everything: installer@theverge.com. And if you know someone else who might enjoy Installer, forward it to them and tell them to subscribe here.)The DropDia. I know there are a lot of Arc fans here in the Installerverse, and I know you, like me, will have a lot of feelings about the company’s new and extremely AI-focused browser. Personally, I don’t see leaving Arc anytime soon, but there are some really fascinating ideas (and nice design touches) in Dia already. Snapseed 3.0. I completely forgot Snapseed even existed, and now here’s a really nice update with a bunch of new editing tools and a nice new redesign! As straightforward photo editors go, this is one of the better ones. The new version is only on iOS right now, but I assume it’s heading to Android shortly.“I Tried To Make Something In America.” I was first turned onto the story of the Smarter Scrubber by a great Search Engine episode, and this is a great companion to the story about what it really takes to bring manufacturing back to the US. And why it’s hard to justify.. That link, and the trailer, will only do anything for you if you have a newer iPhone. But even if you don’t care about the movie, the trailer — which actually buzzes in sync with the car’s rumbles and revs — is just really, really cool. Android 16. You can’t get the cool, colorful new look just yet or the desktop mode I am extremely excited about — there’s a lot of good stuff in Android 16 but most of it is coming later. Still, Live Updates look good, and there’s some helpful accessibility stuff, as well.The Infinite Machine Olto. I am such a sucker for any kind of futuristic-looking electric scooter, and this one really hits the sweet spot. Part moped, part e-bike, all Blade Runner vibes. If it wasn’t $3,500, then I would’ve probably ordered one already.The Fujifilm X-E5. I kept wondering why Fujifilm didn’t just make, like, a hundred different great-looking cameras at every imaginable price because everyone wants a camera this cool. Well, here we are! It’s a spin on the X100VI but with interchangeable lenses and a few power-user features. All my photographer friends are going to want this.Call Her Alex. I confess I’m no Call Her Daddy diehard, but I found this two-part doc on Alex Cooper really interesting. Cooper’s story is all about understanding people, the internet, and what it means to feel connected now. It’s all very low-stakes and somehow also existential? It’s only two parts, you should watch it.“Steve Jobs - 2005 Stanford Commencement Address.” For the 20th anniversary of Jobs’ famous (and genuinely fabulous) speech, the Steve Jobs Archive put together a big package of stories, notes, and other materials around the speech. Plus, a newly high-def version of the video. This one’s always worth the 15 minutes.Dune: Awakening. Dune has ascended to the rare territory of “I will check out anything from this franchise, ever, no questions asked.” This game is big on open-world survival and ornithopters, too, so it’s even more my kind of thing. And it’s apparently punishingly difficult in spots.CrowdsourcedHere’s what the Installer community is into this week. I want to know what you’re into right now as well! Email installer@theverge.com or message me on Signal — @davidpierce.11 — with your recommendations for anything and everything, and we’ll feature some of our favorites here every week. For even more great recommendations, check out the replies to this post on Threads and this post on Bluesky.“I had tried the paper planner in the leather Paper Republic journal but since have moved onto the Remarkable Paper Pro color e-ink device which takes everything you like about paper but makes it editable and color coded. Combine this with a Remarkable planner in PDF format off of Etsy and you are golden.” — Jason“I started reading a manga series from content creator Cory Kenshin called Monsters We Make. So far, I love it. Already preordered Vol. 2.” — Rob“I recently went down the third party controller rabbit hole after my trusty adapted Xbox One controller finally kicked the bucket, and I wanted something I could use across my PC, phone, handheld, Switch, etc. I’ve been playing with the GameSir Cyclone 2 for a few weeks, and it feels really deluxe. The thumbsticks are impossibly smooth and accurate thanks to its TMR joysticks. The face buttons took a second for my brain to adjust to; the short travel distance initially registered as mushy, but once I stopped trying to pound the buttons like I was at the arcade, I found the subtle mechanical click super satisfying.” — Sam“The Apple TV Plus miniseries Long Way Home. It’s Ewan McGregor and Charley Boorman’s fourth Long Way series. This time they are touring some European countries on vintage bikes that they fixed, and it’s such a light-hearted show from two really down to earth humans. Connecting with other people in different cultures and seeing their journey is such a treat!” — Esmael“Podcast recommendation: Devil and the Deep Blue Sea by Christianity Today. A deep dive into the Satanic Panic of the 80’s and 90’s.” — Drew“Splatoon 3 (the free Switch 2 update) and the new How to Train Your Dragon.” — Aaron“I can’t put Mario Kart World down. When I get tired of the intense Knockout Tour mode I go to Free Roam and try to knock out P-Switch challenges, some of which are really tough! I’m obsessed.” — Dave“Fable, a cool app for finding books with virtual book clubs. It’s the closest to a more cozy online bookstore with more honest reviews. I just wish you could click on the author’s name to see their other books.” — Astrid“This is the Summer Games Fest week (formerly E3, RIP) and there are a TON of game demos to try out on Steam. One that has caught my attention / play time the most is Wildgate. It’s a team based spaceship shooter where ship crews battle and try to escape with a powerful artifact.” — Sean“Battlefront 2 is back for some reason. Still looks great.” — IanSigning offI have long been fascinated by weather forecasting. I recommend Andrew Blum’s book, The Weather Machine, to people all the time, as a way to understand both how we learned to predict the weather and why it’s a literally culture-changing thing to be able to do so. And if you want to make yourself so, so angry, there’s a whole chunk of Michael Lewis’s book, The Fifth Risk, about how a bunch of companies managed to basically privatize forecasts… based on government data. The weather is a huge business, an extremely powerful political force, and even more important to our way of life than we realize. And we’re really good at predicting the weather!I’ve also been hearing for years that weather forecasting is a perfect use for AI. It’s all about vast quantities of historical data, tiny fluctuations in readings, and finding patterns that often don’t want to be found. So, of course, as soon as I read my colleague Justine Calma’s story about a new Google project called Weather Lab, I spent the next hour poking through the data to see how well DeepMind managed to predict and track recent storms. It’s deeply wonky stuff, but it’s cool to see Big Tech trying to figure out Mother Nature — and almost getting it right. Almost.See you next week!See More:
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  • Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour

    Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour
    A new report indicates that the ROG Xbox Ally will be priced at around €599, while the more powerful ROG Xbox Ally X will cost €899.

    Posted By Joelle Daniels | On 16th, Jun. 2025

    While Microsoft and Asus have unveiled the ROG Xbox Ally and ROG Xbox Ally X handheld gaming systems, the companies have yet to confirm the prices or release dates for the two systems. While the announcement  mentioned that they will be launched later this year, a new report, courtesy of leaker Extas1s, indicates that pre-orders for both devices will be kicked off in August, with the launch then happening in October. As noted by Extas1s, the lower-powered ROG Xbox Ally is expected to be priced around €599. The leaker claims to have corroborated the pricing details for the handheld with two different Europe-based retailers. The more powerful ROG Xbox Ally X, on the other hand, is expected to be priced at €899. This would put its pricing in line with Asus’s own ROG Ally X. Previously, Asus senior manager of marketing content for gaming, Whitson Gordon, had revealed that pricing and power use were the two biggest reasons why both the ROG Xbox Ally and the ROG Xbox Ally X didn’t feature OLED displays. Rather, both systems will come equipped with 7-inch 1080p 120 Hz LCD displays with variable refresh rate capabilities. “We did some R&D and prototyping with OLED, but it’s still not where we want it to be when you factor VRR into the mix and we aren’t willing to give up VRR,” said Gordon. “I’ll draw that line in the sand right now. I am of the opinion that if a display doesn’t have variable refresh rate, it’s not a gaming display in the year 2025 as far as I’m concerned, right? That’s a must-have feature, and OLED with VRR right now draws significantly more power than the LCD that we’re currently using on the Ally and it costs more.” Explaining further that the decision ultimately also came down to keeping the pricing for both systems at reasonable levels, since buyers often tend to get handheld gaming systems as their secondary machiens, Gordon noted that both handhelds would have much higher price tags if OLED displays were used. “That’s all I’ll say about price,” said Gordon. “You have to align your expectations with the market and what we’re doing here. Adding 32GB, OLED, Z2 Extreme, and all of those extra bells and whistles would cost a lot more than the price bracket you guys are used to on the Ally, and the vast majority of users are not willing to pay that kind of price.” Shortly after its announcement, Microsoft and Asus had released a video where the two companies spoke about the various features of the ROG Xbox Ally and ROG Xbox Ally X. In the video, we also get to see an early hardware prototype of the handheld gaming system built inside a cardboard box. The ROG Xbox Ally runs on an AMD Ryzen Z2A chip, and has 16 GB of LPDDR5X-6400 RAM and 512 GB of storage. The ROG Xbox Ally X, on the other hand, runs on an AMD Ryzen Z2 Extreme chip, and has 24 GB of LPDDR5X-8000 RAM and 1 TB of storage. Both systems run on Windows. Tagged With:

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    Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour
    Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour A new report indicates that the ROG Xbox Ally will be priced at around €599, while the more powerful ROG Xbox Ally X will cost €899. Posted By Joelle Daniels | On 16th, Jun. 2025 While Microsoft and Asus have unveiled the ROG Xbox Ally and ROG Xbox Ally X handheld gaming systems, the companies have yet to confirm the prices or release dates for the two systems. While the announcement  mentioned that they will be launched later this year, a new report, courtesy of leaker Extas1s, indicates that pre-orders for both devices will be kicked off in August, with the launch then happening in October. As noted by Extas1s, the lower-powered ROG Xbox Ally is expected to be priced around €599. The leaker claims to have corroborated the pricing details for the handheld with two different Europe-based retailers. The more powerful ROG Xbox Ally X, on the other hand, is expected to be priced at €899. This would put its pricing in line with Asus’s own ROG Ally X. Previously, Asus senior manager of marketing content for gaming, Whitson Gordon, had revealed that pricing and power use were the two biggest reasons why both the ROG Xbox Ally and the ROG Xbox Ally X didn’t feature OLED displays. Rather, both systems will come equipped with 7-inch 1080p 120 Hz LCD displays with variable refresh rate capabilities. “We did some R&D and prototyping with OLED, but it’s still not where we want it to be when you factor VRR into the mix and we aren’t willing to give up VRR,” said Gordon. “I’ll draw that line in the sand right now. I am of the opinion that if a display doesn’t have variable refresh rate, it’s not a gaming display in the year 2025 as far as I’m concerned, right? That’s a must-have feature, and OLED with VRR right now draws significantly more power than the LCD that we’re currently using on the Ally and it costs more.” Explaining further that the decision ultimately also came down to keeping the pricing for both systems at reasonable levels, since buyers often tend to get handheld gaming systems as their secondary machiens, Gordon noted that both handhelds would have much higher price tags if OLED displays were used. “That’s all I’ll say about price,” said Gordon. “You have to align your expectations with the market and what we’re doing here. Adding 32GB, OLED, Z2 Extreme, and all of those extra bells and whistles would cost a lot more than the price bracket you guys are used to on the Ally, and the vast majority of users are not willing to pay that kind of price.” Shortly after its announcement, Microsoft and Asus had released a video where the two companies spoke about the various features of the ROG Xbox Ally and ROG Xbox Ally X. In the video, we also get to see an early hardware prototype of the handheld gaming system built inside a cardboard box. The ROG Xbox Ally runs on an AMD Ryzen Z2A chip, and has 16 GB of LPDDR5X-6400 RAM and 512 GB of storage. The ROG Xbox Ally X, on the other hand, runs on an AMD Ryzen Z2 Extreme chip, and has 24 GB of LPDDR5X-8000 RAM and 1 TB of storage. Both systems run on Windows. Tagged With: Elden Ring: Nightreign Publisher:Bandai Namco Developer:FromSoftware Platforms:PS5, Xbox Series X, PS4, Xbox One, PCView More FBC: Firebreak Publisher:Remedy Entertainment Developer:Remedy Entertainment Platforms:PS5, Xbox Series X, PCView More Death Stranding 2: On the Beach Publisher:Sony Developer:Kojima Productions Platforms:PS5View More Amazing Articles You Might Want To Check Out! Summer Game Fest 2025 Saw 89 Percent Growth in Live Concurrent Viewership Since Last Year This year's Summer Game Fest has been the most successful one so far, with around 1.5 million live viewers on ... Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour A new report indicates that the ROG Xbox Ally will be priced at around €599, while the more powerful ROG Xbo... Borderlands 4 Gets New Video Explaining the Process of Creating Vault Hunters According to the development team behind Borderlands 4, the creation of Vault Hunters is a studio-wide collabo... The Witcher 4 Team is Tapping Into the “Good Creative Chaos” From The Witcher 3’s Development Narrative director Philipp Weber says there are "new questions we want to answer because this is supposed to f... The Witcher 4 is Opting for “Console-First Development” to Ensure 60 FPS, Says VP of Tech However, CD Projekt RED's Charles Tremblay says 60 frames per second will be "extremely challenging" on the Xb... Red Dead Redemption Voice Actor Teases “Exciting News” for This Week Actor Rob Wiethoff teases an announcement, potentially the rumored release of Red Dead Redemption 2 on Xbox Se... View More #asus #rog #xbox #ally #start
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    Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour
    Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour A new report indicates that the ROG Xbox Ally will be priced at around €599, while the more powerful ROG Xbox Ally X will cost €899. Posted By Joelle Daniels | On 16th, Jun. 2025 While Microsoft and Asus have unveiled the ROG Xbox Ally and ROG Xbox Ally X handheld gaming systems, the companies have yet to confirm the prices or release dates for the two systems. While the announcement  mentioned that they will be launched later this year, a new report, courtesy of leaker Extas1s, indicates that pre-orders for both devices will be kicked off in August, with the launch then happening in October. As noted by Extas1s, the lower-powered ROG Xbox Ally is expected to be priced around €599. The leaker claims to have corroborated the pricing details for the handheld with two different Europe-based retailers. The more powerful ROG Xbox Ally X, on the other hand, is expected to be priced at €899. This would put its pricing in line with Asus’s own ROG Ally X. Previously, Asus senior manager of marketing content for gaming, Whitson Gordon, had revealed that pricing and power use were the two biggest reasons why both the ROG Xbox Ally and the ROG Xbox Ally X didn’t feature OLED displays. Rather, both systems will come equipped with 7-inch 1080p 120 Hz LCD displays with variable refresh rate capabilities. “We did some R&D and prototyping with OLED, but it’s still not where we want it to be when you factor VRR into the mix and we aren’t willing to give up VRR,” said Gordon. “I’ll draw that line in the sand right now. I am of the opinion that if a display doesn’t have variable refresh rate, it’s not a gaming display in the year 2025 as far as I’m concerned, right? That’s a must-have feature, and OLED with VRR right now draws significantly more power than the LCD that we’re currently using on the Ally and it costs more.” Explaining further that the decision ultimately also came down to keeping the pricing for both systems at reasonable levels, since buyers often tend to get handheld gaming systems as their secondary machiens, Gordon noted that both handhelds would have much higher price tags if OLED displays were used. “That’s all I’ll say about price,” said Gordon. “You have to align your expectations with the market and what we’re doing here. Adding 32GB, OLED, Z2 Extreme, and all of those extra bells and whistles would cost a lot more than the price bracket you guys are used to on the Ally, and the vast majority of users are not willing to pay that kind of price.” Shortly after its announcement, Microsoft and Asus had released a video where the two companies spoke about the various features of the ROG Xbox Ally and ROG Xbox Ally X. In the video, we also get to see an early hardware prototype of the handheld gaming system built inside a cardboard box. The ROG Xbox Ally runs on an AMD Ryzen Z2A chip, and has 16 GB of LPDDR5X-6400 RAM and 512 GB of storage. The ROG Xbox Ally X, on the other hand, runs on an AMD Ryzen Z2 Extreme chip, and has 24 GB of LPDDR5X-8000 RAM and 1 TB of storage. Both systems run on Windows. Tagged With: Elden Ring: Nightreign Publisher:Bandai Namco Developer:FromSoftware Platforms:PS5, Xbox Series X, PS4, Xbox One, PCView More FBC: Firebreak Publisher:Remedy Entertainment Developer:Remedy Entertainment Platforms:PS5, Xbox Series X, PCView More Death Stranding 2: On the Beach Publisher:Sony Developer:Kojima Productions Platforms:PS5View More Amazing Articles You Might Want To Check Out! Summer Game Fest 2025 Saw 89 Percent Growth in Live Concurrent Viewership Since Last Year This year's Summer Game Fest has been the most successful one so far, with around 1.5 million live viewers on ... Asus ROG Xbox Ally, ROG Xbox Ally X to Start Pre-Orders in August, Launch in October – Rumour A new report indicates that the ROG Xbox Ally will be priced at around €599, while the more powerful ROG Xbo... Borderlands 4 Gets New Video Explaining the Process of Creating Vault Hunters According to the development team behind Borderlands 4, the creation of Vault Hunters is a studio-wide collabo... The Witcher 4 Team is Tapping Into the “Good Creative Chaos” From The Witcher 3’s Development Narrative director Philipp Weber says there are "new questions we want to answer because this is supposed to f... The Witcher 4 is Opting for “Console-First Development” to Ensure 60 FPS, Says VP of Tech However, CD Projekt RED's Charles Tremblay says 60 frames per second will be "extremely challenging" on the Xb... Red Dead Redemption Voice Actor Teases “Exciting News” for This Week Actor Rob Wiethoff teases an announcement, potentially the rumored release of Red Dead Redemption 2 on Xbox Se... View More
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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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  • The Best Jaws Knockoffs of the Past 50 Years

    To this day, Jaws remains the best example of Steven Spielberg‘s genius as a filmmaker. He somehow took a middling pulp novel about a killer shark and turned it into a thrilling adventure about masculinity and economic desperation. And to the surprise of no one, the massive success of Jaws spawned a lot of knockoffs, a glut of movies about animals terrorizing communities. None of these reach the majesty of Jaws, of course. But here’s the thing—none of them had to be Jaws. Sure, it’s nice that Spielberg’s film has impeccably designed set pieces and compelling characters, but that’s not the main reason people go to animal attack movies. We really just want to watch people get attacked. And eaten.

    With such standards duly lowered, let’s take a look at the best animal attack movies that came out in the past half-century since Jaws first scared us out of the water. Of course this list doesn’t cover every movie inspired by Jaws, and some can argue that these movies were less inspired by Jaws than other nature revolts features, such as Alfred Hitchcock‘s The Birds. But every one of these flicks owes a debt to Jaws, either in inspiration or simply getting people interested in movies about animals eating people. Those warning aside, lets make like drunken revelers on Amity Island and dive right in!
    20. SharknadoSharknado almost doesn’t belong on this list because it’s less a movie and more of a meme, a precursor to Vines and TikTok trends. Yes, many fantastic movies have been made off of an incredibly high concept and a painfully low budget. Heck, that approach made Roger Corman’s career. But Sharknado‘s high concept—a tornado sweeps over the ocean and launches ravenous sharks into the mainland—comes with a self-satisfied smirk.
    Somehow, Sharknado managed to capture the imagination of the public, making it popular enough to launch five sequels. At the time, viewers defended it as a so bad it’s good-style movie like The Room. But today Sharknado‘s obvious attempts to be wacky are just bad, making the franchise one more embarrassing trend, ready to be forgotten.

    19. OrcaFor a long time, Orca had a reputation for being the most obvious Jaws ripoff, and with good reason—Italian producer Dino De Laurentiis, who would go on to support Flash Gordon, Manhunter, and truly launch David Lynch‘s career with Blue Velvet, wanted his own version of the Spielberg hit. On paper he had all the right ingredients, including a great cast with Richard Harris and Charlotte Rampling, and another oceanic threat, this time a killer whale.
    Orca boasts some impressive underwater cinematography, something that even Jaws largely lacks. But that’s the one thing Orca does better than Jaws. Everything else—character-building, suspense and scare scenes, basic plotting and storytelling—is done in such a haphazard manner that Orca plays more like an early mockbuster from the Asylum production companythan it does a product from a future Hollywood player.
    18. TentaclesAnother Italian cheapie riding off the success of Jaws, Tentacles at least manages to be fun in its ineptitude. A giant octopus feature, Tentacles is directed by Ovidio G. Assonitis, a man whose greatest claim to fame is that he annoyed first-time director James Cameron so much on Piranha II: The Spawning that he activated the future legend’s infamous refusal to compromise with studios and producers.
    Tentacles somehow has a pretty impressive cast, including John Huston, Shelly Winters, and Henry Fonda all picking up paychecks. None of them really do any hard work in Tentacles, but there’s something fun about watching these greats shake the the octopus limbs that are supposed to be attacking them, as if they’re in an Ed Wood picture.
    17. Kingdom of the SpidersSpielberg famously couldn’t get his mechanical shark to work, a happy accident that he overcame with incredibly tense scenes that merely suggested the monster’s presence. For his arachnids on the forgotten movie Kingdom of the Spiders, director John “Bud” Cardos has an even more formative tool to make up for the lack of effects magic: William Shatner.
    Shatner plays Rack Hansen, a veterinarian who discovers that the overuse of pesticides has killed off smaller insects and forced the tarantula population to seek larger prey, including humans. These types of ecological messages are common among creature features of the late ’70s, and they usually clang with hollow self-righteousness. But in Kingdom of the Spiders, Shatner delivers his lines with such blown out conviction that we enjoy his bluster, even if we don’t quite buy it.

    16. The MegThe idea of Jason Statham fighting a giant prehistoric shark is an idea so awesome, it’s shocking that his character from Spy didn’t already pitch it. And The Meg certainly does deliver when Statham’s character does commit to battle with the creature in the movie’s climax. The problem is that moment of absurd heroism comes only after a lot of long sappy nonsense.

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    It’s hard to figure out who is to blame for The Meg‘s failure. Director Jon Turteltaub hails from well-remembered Disney classics Cool Runnings and National Treasure. But too often he forgets how to pace an adventure film and gives into his most saccharine instincts here. One of the many Chinese/Hollywood co-produced blockbusters of the 2010s, The Meg also suffers from trying to innocuously please too wide an audience. Whatever the source, The Meg only fleetingly delivers on the promise of big time peril, wasting too much time on thin character beats.
    15. Lake PlacidI know already some people reading this are taking exception to Lake Placid‘s low ranking, complaining that this list isn’t showing enough respect to what they consider a zippy, irreverent take on a creature feature, one written by Ally McBeal creator David E. Kelley and co-starring Betty White. To those people, I can only say, “Please rewatch Lake Placid and then consider its ranking.”
    Lake Placid certainly has its fun moments, helped along by White as a kindly grandmother who keeps feeding a giant croc, Bill Pullman as a dumbfounded simple sheriff, and Oliver Platt as a rich adventurer. Their various one-liners are a pleasure to remember. But within the context of a movie stuffed with late ’90s irony, the constant snark gets tiresome, sapping out all the fun of a killer crocodile film.
    14. Open WaterLike Sharknado, Open Water had its fans for a few years but has fallen in most moviegoers’ esteem. Unlike Sharknado, Open Water is a real movie, just one that can’t sustain its premise for its entire runtime.
    Writer and director Chris Kentis draws inspiration from a real-life story about a husband and wife who were accidentally abandoned in the middle of the ocean by their scuba excursion group. The same thing happens to the movie’s Susan Watkinsand Daniel Travis, who respond to their predicament by airing out their relationship grievances, even as sharks start to surround them. Kentis commits to the reality of the couple’s bleak situation, which sets Open Water apart from the thrill-a-minute movies that mostly make up this list. But even with some shocking set pieces, Open Water feels too much like being stuck in car with a couple who hates each other and not enough like a shark attack thriller.

    13. Eaten AliveSpielberg’s artful execution of Jaws led many of the filmmakers who followed to attempt some semblance of character development and prestige, even if done without enthusiasm. Not so with Tobe Hooper, who followed up the genre-defining The Texas Chainsaw Massacre with Eaten Alive.
    Then again, Hooper draws just as much from Psycho as he does Jaws. Neville Brand plays Judd, the proprietor of a sleazy hotel on the bayou where slimy yokels do horrible things to one another. Amity Island, this is not. But when one of the visitors annoy Judd, he feeds them to the pet croc kept in the back. Eaten Alive is a nasty bit of work, but like most of Hooper’s oeuvre, it’s a lot of fun.
    12. ProphecyDirected by John Frankenheimer of The Manchurian Candidate and Grand Prix fame, Prophecy is easily the best of the more high-minded animal attack movies that followed Jaws. This landlocked film, written by David Seltzer, stars Robert Foxworth as Dr. Robert Verne, a veterinarian hired by the EPA to investigate bear attacks against loggers on a mountain in Maine. Along with his wife Maggie, Verne finds himself thrown into a conflict between the mining company and the local Indigenous population who resist them.
    Prophecy drips with an American hippy mentality that reads as pretty conservative today, making its depictions of Native people, including the leader played by Italian American actor Armand Assante, pretty embarrassing. But there is a mutant bear on the loose and Frankenheimer knows how to stage an exciting sequence, which makes Prophecy a worthwhile watch.
    11. Piranha 3DPiranha 3D begins with a denim-wearing fisherman named Matt, played by Richard Dreyfuss no less, falling into the water and immediately getting devoured by the titular flesh-eaters. This weird nod to Matt Hooper and Jaws instead of Joe Dante’s Piranha, the movie Piranha 3D is supposed to be remaking, is just one of the many oddities at play yhere. Screenwriters Pete Goldfinger and Josh Stolberg have some of the wacky energy and social satire of the original film, but director Alexandre Aja, a veteran of the French Extreme movement, includes so much nastiness in Piranha 3D that we’re not sure if we want to laugh or throw up.
    Still, there’s no denying the power of Piranha 3D‘s set pieces, including a shocking sequence in which the titular beasties attack an MTV/Girls Gone Wild Spring Break party and chaos ensues. Furthermore, Piranha 3D benefits from a strong cast, which includes Elizabeth Shue, Adam Scott, and Ving Rhames.

    10. AnacondaWith its many scenes involving an animal attacking a ragtag group on a boat, Anaconda clearly owes a debt to Jaws. However, with its corny characters and shoddy late ’90s CGI, Anaconda feels today less like a Jaws knockoff and more like a forerunner to Sharknado and the boom of lazy Syfy and Redbox horror movies that followed.
    Whatever its influences and legacy, there’s no denying that Anaconda is, itself, a pretty fun movie. Giant snakes make for good movie monsters, and the special effects have become dated in a way that feels charming. Moreover, Anaconda boasts a enjoyably unlikely cast, including Eric Stoltz as a scientist, Owen Wilson and Ice Cube as members of a documentary crew, and Jon Voight as what might be the most unhinged character of his career, second only to his crossbow enthusiast from Megalopolis.
    9. The ShallowsThe Shallows isn’t the highest-ranking shark attack movie on this list but it’s definitely the most frightening shark attack thriller since Jaws. That’s high praise, indeed, but The Shallows benefits from a lean and mean premise and clear direction by Jaume Collet-Serra, who has made some solid modern thrillers. The Shallows focuses almost entirely on med student Nancy Adams, who gets caught far from shore after the tide comes in and is hunted by a shark.
    A lot of the pleasure of The Shallows comes from seeing how Collet-Serra and screenwriter Anthony Jaswinski avoid the problems that plague many of the movies on this list. Adams is an incredibly competent character, and we pull for her even after the mistake that leaves her stranded. Moreover, The Shallows perfectly balances thrill sequences with character moments, making for one of the more well-rounded creature features of the past decade.
    8. RazorbackJaws, of course, has a fantastic opening scene, a thrilling sequence in which the shark kills a drunken skinny dipper. Of the movies on this list, only Razorback comes close to matching the original’s power, and it does so because director Russell Mulcahy, who would make Highlander next, goes for glossy absurdity. In the Razorback‘s first three minutes, a hulking wild boar smashes through the rural home of an elderly man in the Australian outback, carrying away his young grandson. Over the sounds of a synth score, the old man stumbles away from his now-burning house, screaming up into the sky.
    Sadly, the rest of Razorback cannot top that moment. Mulcahy directs the picture with lots of glossy style, while retaining the grit of the Australian New Wave movement. But budget restrictions keep the titular beast from really looking as cool as one would hope, and the movie’s loud, crazy tone can’t rely on Jaws-like power of suggestion.

    7. CrawlAlexandre Aja’s second movie on this list earns its high rank precisely because it does away with the tonal inconsistencies that plagued Piranha 3D and leans into what the French filmmaker does so well: slicked down and mean horror. Set in the middle of a Florida hurricane, Crawl stars Kaya Scodelario as competitive swimmer Haley and always-welcome character actor Barry Pepper as her father Dave, who get trapped in a flooding basement that’s menaced by alligators.
    Yet as grimy as Crawl can get, Aja also executes the strong character work in the script by Michael Rasmussen and Shawn Rasmussen. Dave and Haley are real people, not just gator-bait, making their peril feel all the more real, and their triumphs all the sweeter.
    6. PiranhaPiranha is the only entry on this list to get a seal of approval from Stephen Spielberg himself, who not only praised the movie, even as Universal Pictures planned to sue the production, but also got director Joe Dante to later helm Gremlins. It’s not hard to see why Piranha charmed Spielberg, a man who loves wacky comedy. Dante’s Looney Tunes approach is on full display in some of the movie’s best set pieces.
    But Piranha is special because it also comes from legendary screenwriter John Sayles, who infuses the story with social satire and cynicism that somehow blends with Dante’s approach. The result is a film about piranha developed by the U.S. military to kill the Vietnamese getting unleashed into an American river and making their way to a children’s summer camp, a horrifying idea that Dante turns into good clean fun.
    5. SlugsIf we’re talking about well-made movies, then Slugs belongs way below any of the movies on this list, somewhere around the killer earthworm picture Squirm. But if we’re thinking about pure enjoyable spectacle, it’s hard to top Slugs, a movie about, yes, flesh-eating slugs.
    Yes, it’s very funny to think about people getting terrorized by creatures that are famous for moving very, very slowly. But Spanish director Juan Piquer Simón, perhaps best known for his equally bugnuts giallo Pieces, pays as little attention to realism as he does to good taste. Slugs is filled with insane and ghastly sequences of killer slugs ending up in unlikely places, swarming the floor of someone’s bedroom or inside a fancy restaurant, and then devouring people, one methodical bite at a time.

    4. Deep Blue SeaWhen it comes to goofy ’90s CGI action, it’s hard to top Deep Blue Sea, directed by Renny Harlin and featuring sharks with genetically enhanced brains. Deep Blue Sea doesn’t have a strong sense of pacing, it lacks any sort of believable character development, and the effects looked terrible even in 1999. But it’s also the only movie on this list that features LL Cool J as a cool chef who recites a violent version of the 23rd Psalm and almost gets cooked alive in an oven by a genius-level shark.
    It’s scenes like the oven sequence that makes Deep Blue Sea such a delight, despite its many, many flaws. The movie tries to do the most at every turn, whether that’s clearly reediting the movie in postproduction so that LL Cool J’s chef becomes a central character, stealing the spotlight form intended star Saffron Burrows, or a ridiculous Samuel L. Jackson monologue with a delightfully unexpected climax.
    3. AlligatorIn many ways, Alligator feels like screenwriter John Sayles’ rejoinder to Piranha. If Joe Dante sanded down Piranha‘s sharp edges with his goofy humor, then Alligator is so filled with mean-spiritedness that no director could dilute it. Not that Lewis Teague, a solid action helmer who we’ll talk about again shortly, would do that.
    Alligator transports the old adage about gators in the sewers from New York to Chicago where the titular beast, the subject of experiments to increase its size, begins preying on the innocent. And on the not so innocent. Alligator shows no respect for the good or the bad, and the film is filled with scenes of people getting devoured, whether it’s a young boy who becomes a snack during a birthday party prank or an elderly mafioso who tries to abandon his family during the gator’s rampage.
    2. GrizzlyGrizzly stands as the greatest of the movies obviously ripping off Jaws precisely because it understands its limitations. It takes what it can from Spielberg’s masterpiece, including the general premise of an animal hunting in a tourist location, and ignores what it can’t pull off, namely three-dimensional characters. This clear-eyed understanding of everyone’s abilities makes Grizzly a lean, mean, and satisfying thriller.
    Directed by blaxploitation vet William Girdler and written by Harvey Flaxman and David Sheldon, Grizzly stars ’70s low-budget king Christopher George as a park ranger investigating unusually vicious bear attacks on campers. That’s not the richest concept in the world, but Girdler and co. execute their ideas with such precision, and George plays his character with just the right amount of machismo, that Grizzly manages to deliver on everything you want from an animal attack.

    1. CujoTo some modern readers, it might seem absurd to put Cujo on a list of Jaws knockoffs. After all, Stephen King is a franchise unto himself and he certainly doesn’t need another movie’s success to get a greenlight for any of his projects. But you have to remember that Cujo came out in 1983 and was just the third of his works to get adapted theatrically, which makes its Jaws connection more valid. After all, the main section of the film—in which momand her son Tadare trapped in their car and menaced by the titular St. Bernard—replicates the isolation on Quint’s fishing vessel, the Orca, better than any other film on this list.
    However, it’s not just director Lewis Teague’s ability to create tension that puts Cujo at the top. Writers Don Carlos Dunaway and Lauren Currier key into the complicated familial dynamics of King’s story, giving the characters surprising depth. It’s no wonder that Spielberg would cast Wallace as another overwhelmed mom for E.T. The Extraterrestrial the very next year, proving that he still has a soft spot for animal attack movies—even if none of them came close to matching the power of Jaws.
    #best #jaws #knockoffs #past #years
    The Best Jaws Knockoffs of the Past 50 Years
    To this day, Jaws remains the best example of Steven Spielberg‘s genius as a filmmaker. He somehow took a middling pulp novel about a killer shark and turned it into a thrilling adventure about masculinity and economic desperation. And to the surprise of no one, the massive success of Jaws spawned a lot of knockoffs, a glut of movies about animals terrorizing communities. None of these reach the majesty of Jaws, of course. But here’s the thing—none of them had to be Jaws. Sure, it’s nice that Spielberg’s film has impeccably designed set pieces and compelling characters, but that’s not the main reason people go to animal attack movies. We really just want to watch people get attacked. And eaten. With such standards duly lowered, let’s take a look at the best animal attack movies that came out in the past half-century since Jaws first scared us out of the water. Of course this list doesn’t cover every movie inspired by Jaws, and some can argue that these movies were less inspired by Jaws than other nature revolts features, such as Alfred Hitchcock‘s The Birds. But every one of these flicks owes a debt to Jaws, either in inspiration or simply getting people interested in movies about animals eating people. Those warning aside, lets make like drunken revelers on Amity Island and dive right in! 20. SharknadoSharknado almost doesn’t belong on this list because it’s less a movie and more of a meme, a precursor to Vines and TikTok trends. Yes, many fantastic movies have been made off of an incredibly high concept and a painfully low budget. Heck, that approach made Roger Corman’s career. But Sharknado‘s high concept—a tornado sweeps over the ocean and launches ravenous sharks into the mainland—comes with a self-satisfied smirk. Somehow, Sharknado managed to capture the imagination of the public, making it popular enough to launch five sequels. At the time, viewers defended it as a so bad it’s good-style movie like The Room. But today Sharknado‘s obvious attempts to be wacky are just bad, making the franchise one more embarrassing trend, ready to be forgotten. 19. OrcaFor a long time, Orca had a reputation for being the most obvious Jaws ripoff, and with good reason—Italian producer Dino De Laurentiis, who would go on to support Flash Gordon, Manhunter, and truly launch David Lynch‘s career with Blue Velvet, wanted his own version of the Spielberg hit. On paper he had all the right ingredients, including a great cast with Richard Harris and Charlotte Rampling, and another oceanic threat, this time a killer whale. Orca boasts some impressive underwater cinematography, something that even Jaws largely lacks. But that’s the one thing Orca does better than Jaws. Everything else—character-building, suspense and scare scenes, basic plotting and storytelling—is done in such a haphazard manner that Orca plays more like an early mockbuster from the Asylum production companythan it does a product from a future Hollywood player. 18. TentaclesAnother Italian cheapie riding off the success of Jaws, Tentacles at least manages to be fun in its ineptitude. A giant octopus feature, Tentacles is directed by Ovidio G. Assonitis, a man whose greatest claim to fame is that he annoyed first-time director James Cameron so much on Piranha II: The Spawning that he activated the future legend’s infamous refusal to compromise with studios and producers. Tentacles somehow has a pretty impressive cast, including John Huston, Shelly Winters, and Henry Fonda all picking up paychecks. None of them really do any hard work in Tentacles, but there’s something fun about watching these greats shake the the octopus limbs that are supposed to be attacking them, as if they’re in an Ed Wood picture. 17. Kingdom of the SpidersSpielberg famously couldn’t get his mechanical shark to work, a happy accident that he overcame with incredibly tense scenes that merely suggested the monster’s presence. For his arachnids on the forgotten movie Kingdom of the Spiders, director John “Bud” Cardos has an even more formative tool to make up for the lack of effects magic: William Shatner. Shatner plays Rack Hansen, a veterinarian who discovers that the overuse of pesticides has killed off smaller insects and forced the tarantula population to seek larger prey, including humans. These types of ecological messages are common among creature features of the late ’70s, and they usually clang with hollow self-righteousness. But in Kingdom of the Spiders, Shatner delivers his lines with such blown out conviction that we enjoy his bluster, even if we don’t quite buy it. 16. The MegThe idea of Jason Statham fighting a giant prehistoric shark is an idea so awesome, it’s shocking that his character from Spy didn’t already pitch it. And The Meg certainly does deliver when Statham’s character does commit to battle with the creature in the movie’s climax. The problem is that moment of absurd heroism comes only after a lot of long sappy nonsense. Join our mailing list Get the best of Den of Geek delivered right to your inbox! It’s hard to figure out who is to blame for The Meg‘s failure. Director Jon Turteltaub hails from well-remembered Disney classics Cool Runnings and National Treasure. But too often he forgets how to pace an adventure film and gives into his most saccharine instincts here. One of the many Chinese/Hollywood co-produced blockbusters of the 2010s, The Meg also suffers from trying to innocuously please too wide an audience. Whatever the source, The Meg only fleetingly delivers on the promise of big time peril, wasting too much time on thin character beats. 15. Lake PlacidI know already some people reading this are taking exception to Lake Placid‘s low ranking, complaining that this list isn’t showing enough respect to what they consider a zippy, irreverent take on a creature feature, one written by Ally McBeal creator David E. Kelley and co-starring Betty White. To those people, I can only say, “Please rewatch Lake Placid and then consider its ranking.” Lake Placid certainly has its fun moments, helped along by White as a kindly grandmother who keeps feeding a giant croc, Bill Pullman as a dumbfounded simple sheriff, and Oliver Platt as a rich adventurer. Their various one-liners are a pleasure to remember. But within the context of a movie stuffed with late ’90s irony, the constant snark gets tiresome, sapping out all the fun of a killer crocodile film. 14. Open WaterLike Sharknado, Open Water had its fans for a few years but has fallen in most moviegoers’ esteem. Unlike Sharknado, Open Water is a real movie, just one that can’t sustain its premise for its entire runtime. Writer and director Chris Kentis draws inspiration from a real-life story about a husband and wife who were accidentally abandoned in the middle of the ocean by their scuba excursion group. The same thing happens to the movie’s Susan Watkinsand Daniel Travis, who respond to their predicament by airing out their relationship grievances, even as sharks start to surround them. Kentis commits to the reality of the couple’s bleak situation, which sets Open Water apart from the thrill-a-minute movies that mostly make up this list. But even with some shocking set pieces, Open Water feels too much like being stuck in car with a couple who hates each other and not enough like a shark attack thriller. 13. Eaten AliveSpielberg’s artful execution of Jaws led many of the filmmakers who followed to attempt some semblance of character development and prestige, even if done without enthusiasm. Not so with Tobe Hooper, who followed up the genre-defining The Texas Chainsaw Massacre with Eaten Alive. Then again, Hooper draws just as much from Psycho as he does Jaws. Neville Brand plays Judd, the proprietor of a sleazy hotel on the bayou where slimy yokels do horrible things to one another. Amity Island, this is not. But when one of the visitors annoy Judd, he feeds them to the pet croc kept in the back. Eaten Alive is a nasty bit of work, but like most of Hooper’s oeuvre, it’s a lot of fun. 12. ProphecyDirected by John Frankenheimer of The Manchurian Candidate and Grand Prix fame, Prophecy is easily the best of the more high-minded animal attack movies that followed Jaws. This landlocked film, written by David Seltzer, stars Robert Foxworth as Dr. Robert Verne, a veterinarian hired by the EPA to investigate bear attacks against loggers on a mountain in Maine. Along with his wife Maggie, Verne finds himself thrown into a conflict between the mining company and the local Indigenous population who resist them. Prophecy drips with an American hippy mentality that reads as pretty conservative today, making its depictions of Native people, including the leader played by Italian American actor Armand Assante, pretty embarrassing. But there is a mutant bear on the loose and Frankenheimer knows how to stage an exciting sequence, which makes Prophecy a worthwhile watch. 11. Piranha 3DPiranha 3D begins with a denim-wearing fisherman named Matt, played by Richard Dreyfuss no less, falling into the water and immediately getting devoured by the titular flesh-eaters. This weird nod to Matt Hooper and Jaws instead of Joe Dante’s Piranha, the movie Piranha 3D is supposed to be remaking, is just one of the many oddities at play yhere. Screenwriters Pete Goldfinger and Josh Stolberg have some of the wacky energy and social satire of the original film, but director Alexandre Aja, a veteran of the French Extreme movement, includes so much nastiness in Piranha 3D that we’re not sure if we want to laugh or throw up. Still, there’s no denying the power of Piranha 3D‘s set pieces, including a shocking sequence in which the titular beasties attack an MTV/Girls Gone Wild Spring Break party and chaos ensues. Furthermore, Piranha 3D benefits from a strong cast, which includes Elizabeth Shue, Adam Scott, and Ving Rhames. 10. AnacondaWith its many scenes involving an animal attacking a ragtag group on a boat, Anaconda clearly owes a debt to Jaws. However, with its corny characters and shoddy late ’90s CGI, Anaconda feels today less like a Jaws knockoff and more like a forerunner to Sharknado and the boom of lazy Syfy and Redbox horror movies that followed. Whatever its influences and legacy, there’s no denying that Anaconda is, itself, a pretty fun movie. Giant snakes make for good movie monsters, and the special effects have become dated in a way that feels charming. Moreover, Anaconda boasts a enjoyably unlikely cast, including Eric Stoltz as a scientist, Owen Wilson and Ice Cube as members of a documentary crew, and Jon Voight as what might be the most unhinged character of his career, second only to his crossbow enthusiast from Megalopolis. 9. The ShallowsThe Shallows isn’t the highest-ranking shark attack movie on this list but it’s definitely the most frightening shark attack thriller since Jaws. That’s high praise, indeed, but The Shallows benefits from a lean and mean premise and clear direction by Jaume Collet-Serra, who has made some solid modern thrillers. The Shallows focuses almost entirely on med student Nancy Adams, who gets caught far from shore after the tide comes in and is hunted by a shark. A lot of the pleasure of The Shallows comes from seeing how Collet-Serra and screenwriter Anthony Jaswinski avoid the problems that plague many of the movies on this list. Adams is an incredibly competent character, and we pull for her even after the mistake that leaves her stranded. Moreover, The Shallows perfectly balances thrill sequences with character moments, making for one of the more well-rounded creature features of the past decade. 8. RazorbackJaws, of course, has a fantastic opening scene, a thrilling sequence in which the shark kills a drunken skinny dipper. Of the movies on this list, only Razorback comes close to matching the original’s power, and it does so because director Russell Mulcahy, who would make Highlander next, goes for glossy absurdity. In the Razorback‘s first three minutes, a hulking wild boar smashes through the rural home of an elderly man in the Australian outback, carrying away his young grandson. Over the sounds of a synth score, the old man stumbles away from his now-burning house, screaming up into the sky. Sadly, the rest of Razorback cannot top that moment. Mulcahy directs the picture with lots of glossy style, while retaining the grit of the Australian New Wave movement. But budget restrictions keep the titular beast from really looking as cool as one would hope, and the movie’s loud, crazy tone can’t rely on Jaws-like power of suggestion. 7. CrawlAlexandre Aja’s second movie on this list earns its high rank precisely because it does away with the tonal inconsistencies that plagued Piranha 3D and leans into what the French filmmaker does so well: slicked down and mean horror. Set in the middle of a Florida hurricane, Crawl stars Kaya Scodelario as competitive swimmer Haley and always-welcome character actor Barry Pepper as her father Dave, who get trapped in a flooding basement that’s menaced by alligators. Yet as grimy as Crawl can get, Aja also executes the strong character work in the script by Michael Rasmussen and Shawn Rasmussen. Dave and Haley are real people, not just gator-bait, making their peril feel all the more real, and their triumphs all the sweeter. 6. PiranhaPiranha is the only entry on this list to get a seal of approval from Stephen Spielberg himself, who not only praised the movie, even as Universal Pictures planned to sue the production, but also got director Joe Dante to later helm Gremlins. It’s not hard to see why Piranha charmed Spielberg, a man who loves wacky comedy. Dante’s Looney Tunes approach is on full display in some of the movie’s best set pieces. But Piranha is special because it also comes from legendary screenwriter John Sayles, who infuses the story with social satire and cynicism that somehow blends with Dante’s approach. The result is a film about piranha developed by the U.S. military to kill the Vietnamese getting unleashed into an American river and making their way to a children’s summer camp, a horrifying idea that Dante turns into good clean fun. 5. SlugsIf we’re talking about well-made movies, then Slugs belongs way below any of the movies on this list, somewhere around the killer earthworm picture Squirm. But if we’re thinking about pure enjoyable spectacle, it’s hard to top Slugs, a movie about, yes, flesh-eating slugs. Yes, it’s very funny to think about people getting terrorized by creatures that are famous for moving very, very slowly. But Spanish director Juan Piquer Simón, perhaps best known for his equally bugnuts giallo Pieces, pays as little attention to realism as he does to good taste. Slugs is filled with insane and ghastly sequences of killer slugs ending up in unlikely places, swarming the floor of someone’s bedroom or inside a fancy restaurant, and then devouring people, one methodical bite at a time. 4. Deep Blue SeaWhen it comes to goofy ’90s CGI action, it’s hard to top Deep Blue Sea, directed by Renny Harlin and featuring sharks with genetically enhanced brains. Deep Blue Sea doesn’t have a strong sense of pacing, it lacks any sort of believable character development, and the effects looked terrible even in 1999. But it’s also the only movie on this list that features LL Cool J as a cool chef who recites a violent version of the 23rd Psalm and almost gets cooked alive in an oven by a genius-level shark. It’s scenes like the oven sequence that makes Deep Blue Sea such a delight, despite its many, many flaws. The movie tries to do the most at every turn, whether that’s clearly reediting the movie in postproduction so that LL Cool J’s chef becomes a central character, stealing the spotlight form intended star Saffron Burrows, or a ridiculous Samuel L. Jackson monologue with a delightfully unexpected climax. 3. AlligatorIn many ways, Alligator feels like screenwriter John Sayles’ rejoinder to Piranha. If Joe Dante sanded down Piranha‘s sharp edges with his goofy humor, then Alligator is so filled with mean-spiritedness that no director could dilute it. Not that Lewis Teague, a solid action helmer who we’ll talk about again shortly, would do that. Alligator transports the old adage about gators in the sewers from New York to Chicago where the titular beast, the subject of experiments to increase its size, begins preying on the innocent. And on the not so innocent. Alligator shows no respect for the good or the bad, and the film is filled with scenes of people getting devoured, whether it’s a young boy who becomes a snack during a birthday party prank or an elderly mafioso who tries to abandon his family during the gator’s rampage. 2. GrizzlyGrizzly stands as the greatest of the movies obviously ripping off Jaws precisely because it understands its limitations. It takes what it can from Spielberg’s masterpiece, including the general premise of an animal hunting in a tourist location, and ignores what it can’t pull off, namely three-dimensional characters. This clear-eyed understanding of everyone’s abilities makes Grizzly a lean, mean, and satisfying thriller. Directed by blaxploitation vet William Girdler and written by Harvey Flaxman and David Sheldon, Grizzly stars ’70s low-budget king Christopher George as a park ranger investigating unusually vicious bear attacks on campers. That’s not the richest concept in the world, but Girdler and co. execute their ideas with such precision, and George plays his character with just the right amount of machismo, that Grizzly manages to deliver on everything you want from an animal attack. 1. CujoTo some modern readers, it might seem absurd to put Cujo on a list of Jaws knockoffs. After all, Stephen King is a franchise unto himself and he certainly doesn’t need another movie’s success to get a greenlight for any of his projects. But you have to remember that Cujo came out in 1983 and was just the third of his works to get adapted theatrically, which makes its Jaws connection more valid. After all, the main section of the film—in which momand her son Tadare trapped in their car and menaced by the titular St. Bernard—replicates the isolation on Quint’s fishing vessel, the Orca, better than any other film on this list. However, it’s not just director Lewis Teague’s ability to create tension that puts Cujo at the top. Writers Don Carlos Dunaway and Lauren Currier key into the complicated familial dynamics of King’s story, giving the characters surprising depth. It’s no wonder that Spielberg would cast Wallace as another overwhelmed mom for E.T. The Extraterrestrial the very next year, proving that he still has a soft spot for animal attack movies—even if none of them came close to matching the power of Jaws. #best #jaws #knockoffs #past #years
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    The Best Jaws Knockoffs of the Past 50 Years
    To this day, Jaws remains the best example of Steven Spielberg‘s genius as a filmmaker. He somehow took a middling pulp novel about a killer shark and turned it into a thrilling adventure about masculinity and economic desperation. And to the surprise of no one, the massive success of Jaws spawned a lot of knockoffs, a glut of movies about animals terrorizing communities. None of these reach the majesty of Jaws, of course. But here’s the thing—none of them had to be Jaws. Sure, it’s nice that Spielberg’s film has impeccably designed set pieces and compelling characters, but that’s not the main reason people go to animal attack movies. We really just want to watch people get attacked. And eaten. With such standards duly lowered, let’s take a look at the best animal attack movies that came out in the past half-century since Jaws first scared us out of the water. Of course this list doesn’t cover every movie inspired by Jaws ( for example Godzilla Minus One, which devotes its middle act to a wonderful Jaws riff), and some can argue that these movies were less inspired by Jaws than other nature revolts features, such as Alfred Hitchcock‘s The Birds. But every one of these flicks owes a debt to Jaws, either in inspiration or simply getting people interested in movies about animals eating people. Those warning aside, lets make like drunken revelers on Amity Island and dive right in! 20. Sharknado (2013) Sharknado almost doesn’t belong on this list because it’s less a movie and more of a meme, a precursor to Vines and TikTok trends. Yes, many fantastic movies have been made off of an incredibly high concept and a painfully low budget. Heck, that approach made Roger Corman’s career. But Sharknado‘s high concept—a tornado sweeps over the ocean and launches ravenous sharks into the mainland—comes with a self-satisfied smirk. Somehow, Sharknado managed to capture the imagination of the public, making it popular enough to launch five sequels. At the time, viewers defended it as a so bad it’s good-style movie like The Room. But today Sharknado‘s obvious attempts to be wacky are just bad, making the franchise one more embarrassing trend, ready to be forgotten. 19. Orca (1977) For a long time, Orca had a reputation for being the most obvious Jaws ripoff, and with good reason—Italian producer Dino De Laurentiis, who would go on to support Flash Gordon, Manhunter, and truly launch David Lynch‘s career with Blue Velvet, wanted his own version of the Spielberg hit. On paper he had all the right ingredients, including a great cast with Richard Harris and Charlotte Rampling, and another oceanic threat, this time a killer whale. Orca boasts some impressive underwater cinematography, something that even Jaws largely lacks. But that’s the one thing Orca does better than Jaws. Everything else—character-building, suspense and scare scenes, basic plotting and storytelling—is done in such a haphazard manner that Orca plays more like an early mockbuster from the Asylum production company (makers of Sharknado) than it does a product from a future Hollywood player. 18. Tentacles (1977) Another Italian cheapie riding off the success of Jaws, Tentacles at least manages to be fun in its ineptitude. A giant octopus feature, Tentacles is directed by Ovidio G. Assonitis, a man whose greatest claim to fame is that he annoyed first-time director James Cameron so much on Piranha II: The Spawning that he activated the future legend’s infamous refusal to compromise with studios and producers. Tentacles somehow has a pretty impressive cast, including John Huston, Shelly Winters, and Henry Fonda all picking up paychecks. None of them really do any hard work in Tentacles, but there’s something fun about watching these greats shake the the octopus limbs that are supposed to be attacking them, as if they’re in an Ed Wood picture. 17. Kingdom of the Spiders (1977) Spielberg famously couldn’t get his mechanical shark to work, a happy accident that he overcame with incredibly tense scenes that merely suggested the monster’s presence. For his arachnids on the forgotten movie Kingdom of the Spiders, director John “Bud” Cardos has an even more formative tool to make up for the lack of effects magic: William Shatner. Shatner plays Rack Hansen, a veterinarian who discovers that the overuse of pesticides has killed off smaller insects and forced the tarantula population to seek larger prey, including humans. These types of ecological messages are common among creature features of the late ’70s, and they usually clang with hollow self-righteousness. But in Kingdom of the Spiders, Shatner delivers his lines with such blown out conviction that we enjoy his bluster, even if we don’t quite buy it. 16. The Meg (2018) The idea of Jason Statham fighting a giant prehistoric shark is an idea so awesome, it’s shocking that his character from Spy didn’t already pitch it. And The Meg certainly does deliver when Statham’s character does commit to battle with the creature in the movie’s climax. The problem is that moment of absurd heroism comes only after a lot of long sappy nonsense. Join our mailing list Get the best of Den of Geek delivered right to your inbox! It’s hard to figure out who is to blame for The Meg‘s failure. Director Jon Turteltaub hails from well-remembered Disney classics Cool Runnings and National Treasure. But too often he forgets how to pace an adventure film and gives into his most saccharine instincts here. One of the many Chinese/Hollywood co-produced blockbusters of the 2010s, The Meg also suffers from trying to innocuously please too wide an audience. Whatever the source, The Meg only fleetingly delivers on the promise of big time peril, wasting too much time on thin character beats. 15. Lake Placid (1999) I know already some people reading this are taking exception to Lake Placid‘s low ranking, complaining that this list isn’t showing enough respect to what they consider a zippy, irreverent take on a creature feature, one written by Ally McBeal creator David E. Kelley and co-starring Betty White. To those people, I can only say, “Please rewatch Lake Placid and then consider its ranking.” Lake Placid certainly has its fun moments, helped along by White as a kindly grandmother who keeps feeding a giant croc, Bill Pullman as a dumbfounded simple sheriff, and Oliver Platt as a rich adventurer. Their various one-liners are a pleasure to remember. But within the context of a movie stuffed with late ’90s irony, the constant snark gets tiresome, sapping out all the fun of a killer crocodile film. 14. Open Water (2003) Like Sharknado, Open Water had its fans for a few years but has fallen in most moviegoers’ esteem. Unlike Sharknado, Open Water is a real movie, just one that can’t sustain its premise for its entire runtime. Writer and director Chris Kentis draws inspiration from a real-life story about a husband and wife who were accidentally abandoned in the middle of the ocean by their scuba excursion group. The same thing happens to the movie’s Susan Watkins (Blanchard Ryan) and Daniel Travis (Daniel Kintner), who respond to their predicament by airing out their relationship grievances, even as sharks start to surround them. Kentis commits to the reality of the couple’s bleak situation, which sets Open Water apart from the thrill-a-minute movies that mostly make up this list. But even with some shocking set pieces, Open Water feels too much like being stuck in car with a couple who hates each other and not enough like a shark attack thriller. 13. Eaten Alive (1976) Spielberg’s artful execution of Jaws led many of the filmmakers who followed to attempt some semblance of character development and prestige, even if done without enthusiasm (see: Orca). Not so with Tobe Hooper, who followed up the genre-defining The Texas Chainsaw Massacre with Eaten Alive. Then again, Hooper draws just as much from Psycho as he does Jaws. Neville Brand plays Judd, the proprietor of a sleazy hotel on the bayou where slimy yokels do horrible things to one another. Amity Island, this is not. But when one of the visitors annoy Judd, he feeds them to the pet croc kept in the back. Eaten Alive is a nasty bit of work, but like most of Hooper’s oeuvre, it’s a lot of fun. 12. Prophecy (1979) Directed by John Frankenheimer of The Manchurian Candidate and Grand Prix fame, Prophecy is easily the best of the more high-minded animal attack movies that followed Jaws. This landlocked film, written by David Seltzer, stars Robert Foxworth as Dr. Robert Verne, a veterinarian hired by the EPA to investigate bear attacks against loggers on a mountain in Maine. Along with his wife Maggie (Talia Shire), Verne finds himself thrown into a conflict between the mining company and the local Indigenous population who resist them. Prophecy drips with an American hippy mentality that reads as pretty conservative today (“your body, your choice” one of Maggie’s friends tells her… to urge her against getting an abortion), making its depictions of Native people, including the leader played by Italian American actor Armand Assante, pretty embarrassing. But there is a mutant bear on the loose and Frankenheimer knows how to stage an exciting sequence, which makes Prophecy a worthwhile watch. 11. Piranha 3D (2010) Piranha 3D begins with a denim-wearing fisherman named Matt, played by Richard Dreyfuss no less, falling into the water and immediately getting devoured by the titular flesh-eaters. This weird nod to Matt Hooper and Jaws instead of Joe Dante’s Piranha, the movie Piranha 3D is supposed to be remaking, is just one of the many oddities at play yhere. Screenwriters Pete Goldfinger and Josh Stolberg have some of the wacky energy and social satire of the original film, but director Alexandre Aja, a veteran of the French Extreme movement, includes so much nastiness in Piranha 3D that we’re not sure if we want to laugh or throw up. Still, there’s no denying the power of Piranha 3D‘s set pieces, including a shocking sequence in which the titular beasties attack an MTV/Girls Gone Wild Spring Break party and chaos ensues. Furthermore, Piranha 3D benefits from a strong cast, which includes Elizabeth Shue, Adam Scott, and Ving Rhames. 10. Anaconda (1997) With its many scenes involving an animal attacking a ragtag group on a boat, Anaconda clearly owes a debt to Jaws. However, with its corny characters and shoddy late ’90s CGI, Anaconda feels today less like a Jaws knockoff and more like a forerunner to Sharknado and the boom of lazy Syfy and Redbox horror movies that followed. Whatever its influences and legacy, there’s no denying that Anaconda is, itself, a pretty fun movie. Giant snakes make for good movie monsters, and the special effects have become dated in a way that feels charming. Moreover, Anaconda boasts a enjoyably unlikely cast, including Eric Stoltz as a scientist, Owen Wilson and Ice Cube as members of a documentary crew, and Jon Voight as what might be the most unhinged character of his career, second only to his crossbow enthusiast from Megalopolis. 9. The Shallows (2016) The Shallows isn’t the highest-ranking shark attack movie on this list but it’s definitely the most frightening shark attack thriller since Jaws. That’s high praise, indeed, but The Shallows benefits from a lean and mean premise and clear direction by Jaume Collet-Serra, who has made some solid modern thrillers. The Shallows focuses almost entirely on med student Nancy Adams (Blake Lively), who gets caught far from shore after the tide comes in and is hunted by a shark. A lot of the pleasure of The Shallows comes from seeing how Collet-Serra and screenwriter Anthony Jaswinski avoid the problems that plague many of the movies on this list. Adams is an incredibly competent character, and we pull for her even after the mistake that leaves her stranded. Moreover, The Shallows perfectly balances thrill sequences with character moments, making for one of the more well-rounded creature features of the past decade. 8. Razorback (1984) Jaws, of course, has a fantastic opening scene, a thrilling sequence in which the shark kills a drunken skinny dipper. Of the movies on this list, only Razorback comes close to matching the original’s power, and it does so because director Russell Mulcahy, who would make Highlander next, goes for glossy absurdity. In the Razorback‘s first three minutes, a hulking wild boar smashes through the rural home of an elderly man in the Australian outback, carrying away his young grandson. Over the sounds of a synth score, the old man stumbles away from his now-burning house, screaming up into the sky. Sadly, the rest of Razorback cannot top that moment. Mulcahy directs the picture with lots of glossy style, while retaining the grit of the Australian New Wave movement. But budget restrictions keep the titular beast from really looking as cool as one would hope, and the movie’s loud, crazy tone can’t rely on Jaws-like power of suggestion. 7. Crawl (2019) Alexandre Aja’s second movie on this list earns its high rank precisely because it does away with the tonal inconsistencies that plagued Piranha 3D and leans into what the French filmmaker does so well: slicked down and mean horror. Set in the middle of a Florida hurricane, Crawl stars Kaya Scodelario as competitive swimmer Haley and always-welcome character actor Barry Pepper as her father Dave, who get trapped in a flooding basement that’s menaced by alligators. Yet as grimy as Crawl can get, Aja also executes the strong character work in the script by Michael Rasmussen and Shawn Rasmussen. Dave and Haley are real people, not just gator-bait, making their peril feel all the more real, and their triumphs all the sweeter. 6. Piranha (1978) Piranha is the only entry on this list to get a seal of approval from Stephen Spielberg himself, who not only praised the movie, even as Universal Pictures planned to sue the production, but also got director Joe Dante to later helm Gremlins. It’s not hard to see why Piranha charmed Spielberg, a man who loves wacky comedy. Dante’s Looney Tunes approach is on full display in some of the movie’s best set pieces. But Piranha is special because it also comes from legendary screenwriter John Sayles, who infuses the story with social satire and cynicism that somehow blends with Dante’s approach. The result is a film about piranha developed by the U.S. military to kill the Vietnamese getting unleashed into an American river and making their way to a children’s summer camp, a horrifying idea that Dante turns into good clean fun. 5. Slugs (1988) If we’re talking about well-made movies, then Slugs belongs way below any of the movies on this list, somewhere around the killer earthworm picture Squirm. But if we’re thinking about pure enjoyable spectacle, it’s hard to top Slugs, a movie about, yes, flesh-eating slugs. Yes, it’s very funny to think about people getting terrorized by creatures that are famous for moving very, very slowly. But Spanish director Juan Piquer Simón, perhaps best known for his equally bugnuts giallo Pieces (1982), pays as little attention to realism as he does to good taste. Slugs is filled with insane and ghastly sequences of killer slugs ending up in unlikely places, swarming the floor of someone’s bedroom or inside a fancy restaurant, and then devouring people, one methodical bite at a time. 4. Deep Blue Sea (1999) When it comes to goofy ’90s CGI action, it’s hard to top Deep Blue Sea, directed by Renny Harlin and featuring sharks with genetically enhanced brains. Deep Blue Sea doesn’t have a strong sense of pacing, it lacks any sort of believable character development, and the effects looked terrible even in 1999. But it’s also the only movie on this list that features LL Cool J as a cool chef who recites a violent version of the 23rd Psalm and almost gets cooked alive in an oven by a genius-level shark. It’s scenes like the oven sequence that makes Deep Blue Sea such a delight, despite its many, many flaws. The movie tries to do the most at every turn, whether that’s clearly reediting the movie in postproduction so that LL Cool J’s chef becomes a central character, stealing the spotlight form intended star Saffron Burrows, or a ridiculous Samuel L. Jackson monologue with a delightfully unexpected climax. 3. Alligator (1980) In many ways, Alligator feels like screenwriter John Sayles’ rejoinder to Piranha. If Joe Dante sanded down Piranha‘s sharp edges with his goofy humor, then Alligator is so filled with mean-spiritedness that no director could dilute it. Not that Lewis Teague, a solid action helmer who we’ll talk about again shortly, would do that. Alligator transports the old adage about gators in the sewers from New York to Chicago where the titular beast, the subject of experiments to increase its size, begins preying on the innocent. And on the not so innocent. Alligator shows no respect for the good or the bad, and the film is filled with scenes of people getting devoured, whether it’s a young boy who becomes a snack during a birthday party prank or an elderly mafioso who tries to abandon his family during the gator’s rampage. 2. Grizzly (1976) Grizzly stands as the greatest of the movies obviously ripping off Jaws precisely because it understands its limitations. It takes what it can from Spielberg’s masterpiece, including the general premise of an animal hunting in a tourist location, and ignores what it can’t pull off, namely three-dimensional characters. This clear-eyed understanding of everyone’s abilities makes Grizzly a lean, mean, and satisfying thriller. Directed by blaxploitation vet William Girdler and written by Harvey Flaxman and David Sheldon, Grizzly stars ’70s low-budget king Christopher George as a park ranger investigating unusually vicious bear attacks on campers. That’s not the richest concept in the world, but Girdler and co. execute their ideas with such precision, and George plays his character with just the right amount of machismo, that Grizzly manages to deliver on everything you want from an animal attack. 1. Cujo (1983) To some modern readers, it might seem absurd to put Cujo on a list of Jaws knockoffs. After all, Stephen King is a franchise unto himself and he certainly doesn’t need another movie’s success to get a greenlight for any of his projects. But you have to remember that Cujo came out in 1983 and was just the third of his works to get adapted theatrically, which makes its Jaws connection more valid. After all, the main section of the film—in which mom (Dee Wallace) and her son Tad (Danny Pintauro) are trapped in their car and menaced by the titular St. Bernard—replicates the isolation on Quint’s fishing vessel, the Orca, better than any other film on this list. However, it’s not just director Lewis Teague’s ability to create tension that puts Cujo at the top. Writers Don Carlos Dunaway and Lauren Currier key into the complicated familial dynamics of King’s story, giving the characters surprising depth. It’s no wonder that Spielberg would cast Wallace as another overwhelmed mom for E.T. The Extraterrestrial the very next year, proving that he still has a soft spot for animal attack movies—even if none of them came close to matching the power of Jaws.
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  • Eight standout interior spaces earn 2025 AIA Interior Architecture Awards

    The American Institute of Architects has unveiled the winners of its 2025 Interior Architecture Award. A total of eight projects were honored this year, with winners ranging from a prototype for 3D-printed concrete homes to an early learning center.The awards come shortly after the AIA also honored the best in contemporary architecture at the 2025 AIA Architecture Awards and the best in small-scale architecture at the AIA Small Project Award. This week has also seen the best housing design honored at the AIA Housing Award, the best in sustainable architecture honored at the AIA COTE Top Ten Award, and the best in urban planning honored at the AIA Regional & Urban Design Award. You can follow our ongoing coverage of the series here.The complete list of 2025 Interior Architecture Award winners can be viewed below:House Zero, Austin, TXLake|Flato Architects
    #eight #standout #interior #spaces #earn
    Eight standout interior spaces earn 2025 AIA Interior Architecture Awards
    The American Institute of Architects has unveiled the winners of its 2025 Interior Architecture Award. A total of eight projects were honored this year, with winners ranging from a prototype for 3D-printed concrete homes to an early learning center.The awards come shortly after the AIA also honored the best in contemporary architecture at the 2025 AIA Architecture Awards and the best in small-scale architecture at the AIA Small Project Award. This week has also seen the best housing design honored at the AIA Housing Award, the best in sustainable architecture honored at the AIA COTE Top Ten Award, and the best in urban planning honored at the AIA Regional & Urban Design Award. You can follow our ongoing coverage of the series here.The complete list of 2025 Interior Architecture Award winners can be viewed below:House Zero, Austin, TXLake|Flato Architects #eight #standout #interior #spaces #earn
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    Eight standout interior spaces earn 2025 AIA Interior Architecture Awards
    The American Institute of Architects has unveiled the winners of its 2025 Interior Architecture Award. A total of eight projects were honored this year, with winners ranging from a prototype for 3D-printed concrete homes to an early learning center.The awards come shortly after the AIA also honored the best in contemporary architecture at the 2025 AIA Architecture Awards and the best in small-scale architecture at the AIA Small Project Award. This week has also seen the best housing design honored at the AIA Housing Award, the best in sustainable architecture honored at the AIA COTE Top Ten Award, and the best in urban planning honored at the AIA Regional & Urban Design Award. You can follow our ongoing coverage of the series here.The complete list of 2025 Interior Architecture Award winners can be viewed below:House Zero, Austin, TXLake|Flato Architects
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  • Star Trek: Strange New Worlds’ third season falls short of its second

    This is a spoiler-free preview of the first five episodes of season three.
    Star Trek: Strange New Worlds ended its second season with arguably the single strongest run of any streaming-era Trek. The show was made with such confidence in all departments that if there were flaws, you weren’t interested in looking for them. Since then, it’s gone from being the best modern Trek, to being the only modern Trek. Unfortunately, at the moment it needs to be the standard bearer for the show, it’s become noticeably weaker and less consistent. 
    As usual, I’ve seen the first five episodes, but can’t reveal specifics about what I’ve seen. I can say plenty of the things that made Strange New Worlds the best modern-day live-action Trek remain in place. It’s a show that’s happy for you to spend time with its characters as they hang out, and almost all of them are deeply charming. This is, after all, a show that uses as motif the image of the crew in Pike’s quarters as the captain cooks for his crew.
    Its format, with standalone adventures blended with serialized character drama, means it can offer something new every week. Think back to the first season, when “Memento Mori,” a tense action thriller with the Gorn, was immediately followed by “Spock Amock,” a goofy, starbase-set body-swap romantic comedy of manners centered around Spock. Strange New Worlds is the first Trek in a long while to realize audiences don’t just want a ceaseless slog of stern-faced, angry grimdark. And if they want that, they can go watch Picard and Section 31.
    Marni Grossman/Paramount+
    But, as much as those things are SNW’s greatest strength, it’s a delicate balance to ensure the series doesn’t lurch too far either way. And, it pains me to say this, the show spends the first five episodes of its third season going too far in both directions. No specifics, but one episode I’m sure was on the same writers room whiteboard wishlist as last season’s musical episode. What was clearly intended as a chance for everyone to get out of their usual roles and have fun falls flat. Because the episode can never get past the sense it’s too delighted in its own silliness to properly function.
    Marni Grossman/Paramount+
    At the other end of the scale, we get sprints toward the eye-gouging grimdark that blighted those other series. Sure, the series has gone to dark places before, but previously with more of a sense of deftness, rather than just going for the viscerally-upsetting gore. A cynic might suggest that, as Paramount’s other Trek projects ended, franchise-overseer Alex Kurtzman — who has pushed the franchise into “grittier” territory whenever he can — had more time to spend in the SNW writers’ room.
    Much as I’ve enjoyed the series’ soapier elements, the continuing plotlines take up an ever bigger part of each episode’s runtime so far. Consequently, the story of the week gets less service, making them feel weaker and less coherent. One episode pivots two thirds of the way in to act as a low-key sequel to an episode from season two. But since we’ve only got ten minutes left, it feels thrown in as an afterthought, or to resolve a thread the creative team felt they were obliged to deal with.
    In fact, this and the recently-finished run of Doctor Who suffered from the same problem that blights so many streaming-era shows, which is the limited episode order. Rather than producing TV on the scale broadcast networks were able to — yearly runs of 22-, 24- or 26 episodes, a lot ofgenre shows get less than half that. The result is that each episode has to be More Important Than The Last One in a way that’s exhausting for a viewer.
    But Strange New Worlds can’t solve all the economic issues with the streaming model on its own. My hope is that, much like in its first season, the weaker episodes are all in its front half to soften us up for the moments of quality that followed toward its conclusion.
    ASIDE: Shortly before publication, Paramount announced Strange New Worlds would end in its fifth season, which would be cut from ten episodes to six. It's not surprising — given the equally-brilliant Lower Decks was also axed after passing the same milestone — but it is disappointing. My only hope is that the series doesn't spend that final run awkwardly killing off the series' young ensemble one by one in order to replace them with the entire original series' roster as to make it "line up." Please, let them be their own things. This article originally appeared on Engadget at
    #star #trek #strange #new #worlds
    Star Trek: Strange New Worlds’ third season falls short of its second
    This is a spoiler-free preview of the first five episodes of season three. Star Trek: Strange New Worlds ended its second season with arguably the single strongest run of any streaming-era Trek. The show was made with such confidence in all departments that if there were flaws, you weren’t interested in looking for them. Since then, it’s gone from being the best modern Trek, to being the only modern Trek. Unfortunately, at the moment it needs to be the standard bearer for the show, it’s become noticeably weaker and less consistent.  As usual, I’ve seen the first five episodes, but can’t reveal specifics about what I’ve seen. I can say plenty of the things that made Strange New Worlds the best modern-day live-action Trek remain in place. It’s a show that’s happy for you to spend time with its characters as they hang out, and almost all of them are deeply charming. This is, after all, a show that uses as motif the image of the crew in Pike’s quarters as the captain cooks for his crew. Its format, with standalone adventures blended with serialized character drama, means it can offer something new every week. Think back to the first season, when “Memento Mori,” a tense action thriller with the Gorn, was immediately followed by “Spock Amock,” a goofy, starbase-set body-swap romantic comedy of manners centered around Spock. Strange New Worlds is the first Trek in a long while to realize audiences don’t just want a ceaseless slog of stern-faced, angry grimdark. And if they want that, they can go watch Picard and Section 31. Marni Grossman/Paramount+ But, as much as those things are SNW’s greatest strength, it’s a delicate balance to ensure the series doesn’t lurch too far either way. And, it pains me to say this, the show spends the first five episodes of its third season going too far in both directions. No specifics, but one episode I’m sure was on the same writers room whiteboard wishlist as last season’s musical episode. What was clearly intended as a chance for everyone to get out of their usual roles and have fun falls flat. Because the episode can never get past the sense it’s too delighted in its own silliness to properly function. Marni Grossman/Paramount+ At the other end of the scale, we get sprints toward the eye-gouging grimdark that blighted those other series. Sure, the series has gone to dark places before, but previously with more of a sense of deftness, rather than just going for the viscerally-upsetting gore. A cynic might suggest that, as Paramount’s other Trek projects ended, franchise-overseer Alex Kurtzman — who has pushed the franchise into “grittier” territory whenever he can — had more time to spend in the SNW writers’ room. Much as I’ve enjoyed the series’ soapier elements, the continuing plotlines take up an ever bigger part of each episode’s runtime so far. Consequently, the story of the week gets less service, making them feel weaker and less coherent. One episode pivots two thirds of the way in to act as a low-key sequel to an episode from season two. But since we’ve only got ten minutes left, it feels thrown in as an afterthought, or to resolve a thread the creative team felt they were obliged to deal with. In fact, this and the recently-finished run of Doctor Who suffered from the same problem that blights so many streaming-era shows, which is the limited episode order. Rather than producing TV on the scale broadcast networks were able to — yearly runs of 22-, 24- or 26 episodes, a lot ofgenre shows get less than half that. The result is that each episode has to be More Important Than The Last One in a way that’s exhausting for a viewer. But Strange New Worlds can’t solve all the economic issues with the streaming model on its own. My hope is that, much like in its first season, the weaker episodes are all in its front half to soften us up for the moments of quality that followed toward its conclusion. ASIDE: Shortly before publication, Paramount announced Strange New Worlds would end in its fifth season, which would be cut from ten episodes to six. It's not surprising — given the equally-brilliant Lower Decks was also axed after passing the same milestone — but it is disappointing. My only hope is that the series doesn't spend that final run awkwardly killing off the series' young ensemble one by one in order to replace them with the entire original series' roster as to make it "line up." Please, let them be their own things. This article originally appeared on Engadget at #star #trek #strange #new #worlds
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    Star Trek: Strange New Worlds’ third season falls short of its second
    This is a spoiler-free preview of the first five episodes of season three. Star Trek: Strange New Worlds ended its second season with arguably the single strongest run of any streaming-era Trek. The show was made with such confidence in all departments that if there were flaws, you weren’t interested in looking for them. Since then, it’s gone from being the best modern Trek, to being the only modern Trek. Unfortunately, at the moment it needs to be the standard bearer for the show, it’s become noticeably weaker and less consistent.  As usual, I’ve seen the first five episodes, but can’t reveal specifics about what I’ve seen. I can say plenty of the things that made Strange New Worlds the best modern-day live-action Trek remain in place. It’s a show that’s happy for you to spend time with its characters as they hang out, and almost all of them are deeply charming. This is, after all, a show that uses as motif the image of the crew in Pike’s quarters as the captain cooks for his crew. Its format, with standalone adventures blended with serialized character drama, means it can offer something new every week. Think back to the first season, when “Memento Mori,” a tense action thriller with the Gorn, was immediately followed by “Spock Amock,” a goofy, starbase-set body-swap romantic comedy of manners centered around Spock. Strange New Worlds is the first Trek in a long while to realize audiences don’t just want a ceaseless slog of stern-faced, angry grimdark. And if they want that, they can go watch Picard and Section 31. Marni Grossman/Paramount+ But, as much as those things are SNW’s greatest strength, it’s a delicate balance to ensure the series doesn’t lurch too far either way. And, it pains me to say this, the show spends the first five episodes of its third season going too far in both directions (although, mercifully, not at the same time). No specifics, but one episode I’m sure was on the same writers room whiteboard wishlist as last season’s musical episode. What was clearly intended as a chance for everyone to get out of their usual roles and have fun falls flat. Because the episode can never get past the sense it’s too delighted in its own silliness to properly function. Marni Grossman/Paramount+ At the other end of the scale, we get sprints toward the eye-gouging grimdark that blighted those other series. Sure, the series has gone to dark places before, but previously with more of a sense of deftness, rather than just going for the viscerally-upsetting gore. A cynic might suggest that, as Paramount’s other Trek projects ended, franchise-overseer Alex Kurtzman — who has pushed the franchise into “grittier” territory whenever he can — had more time to spend in the SNW writers’ room. Much as I’ve enjoyed the series’ soapier elements, the continuing plotlines take up an ever bigger part of each episode’s runtime so far. Consequently, the story of the week gets less service, making them feel weaker and less coherent. One episode pivots two thirds of the way in to act as a low-key sequel to an episode from season two. But since we’ve only got ten minutes left, it feels thrown in as an afterthought, or to resolve a thread the creative team felt they were obliged to deal with (they didn’t). In fact, this and the recently-finished run of Doctor Who suffered from the same problem that blights so many streaming-era shows, which is the limited episode order. Rather than producing TV on the scale broadcast networks were able to — yearly runs of 22-, 24- or 26 episodes, a lot of (expensive) genre shows get less than half that. The result is that each episode has to be More Important Than The Last One in a way that’s exhausting for a viewer. But Strange New Worlds can’t solve all the economic issues with the streaming model on its own. My hope is that, much like in its first season, the weaker episodes are all in its front half to soften us up for the moments of quality that followed toward its conclusion. ASIDE: Shortly before publication, Paramount announced Strange New Worlds would end in its fifth season, which would be cut from ten episodes to six. It's not surprising — given the equally-brilliant Lower Decks was also axed after passing the same milestone — but it is disappointing. My only hope is that the series doesn't spend that final run awkwardly killing off the series' young ensemble one by one in order to replace them with the entire original series' roster as to make it "line up." Please, let them be their own things. This article originally appeared on Engadget at https://www.engadget.com/entertainment/tv-movies/star-trek-strange-new-worlds-third-season-falls-short-of-its-second-020030139.html?src=rss
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  • Splitgate 2 Dev Says He's Tired Of Playing Call Of Duty And Wants Titanfall 3 While Wearing A 'Make FPS Great Again' Hat: 'I’m Not Here To Apologize'

    1047 Games cofounder Ian Proulx took the stage at Summer Game Fest on Friday to promote his new game Splitgate 2 by calling out the current state of online shooters. Eschewing the marketing speak of most of his peers at the glossy showcase, he said he wants Titanfall 3 to come out and called his new game’s surprise battle royale mode “fucking awesome” while wearing a “Make FPS Great Again” hat. Suggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases

    Share SubtitlesOffEnglishview videoSuggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases

    Share SubtitlesOffEnglishSplitgate 2 is a free-to-play arena-style shooter where players deploy portals to mess with physics and the fabric of reality to outwit their opponents. “I grew up playing Halo and I’m tired of playing the same Call of Duty every year and I wish we could have Titanfall 3,” Proulx said on stage alongside host Geoff Keighley. He added that the new battle roayle mode aims to combine the old-school arena shooter sensibility with a mechanic to portal to other worlds. Out today on console and PC after a beta last month, 1047 revealed that the new mode is going live alongside the rest of the game. The subtext of Proulx’s pitch channeling President Trump’s slogan was clear: while EA cancels games and Activision leans into predictable cash-grabs, the underdog team at 1047 is shaking things up with a game by gamers for gamers. Meanwhile, the riff on “Make America Great Again” took place shortly after a clash between Los Angeles residents and law enforcement over ICE raids in the city’s garment district only blocks from where Keighley’s Summer Game Fest Play Days industry event takes place this weekend. Trump has ordered the immigration agency to arrest a record number of people every day for deportation even as ICE detention centers are criticized for overcrowding and lack of food. The original Splitgate launched in early access in 2019 and spiked in popularity. The party didn’t last, however, and by 2022, the studio abandoned the game to work on a new project. Last year it revealed that new project was actually just Splitgate 2. .
    #splitgate #dev #says #he039s #tired
    Splitgate 2 Dev Says He's Tired Of Playing Call Of Duty And Wants Titanfall 3 While Wearing A 'Make FPS Great Again' Hat: 'I’m Not Here To Apologize'
    1047 Games cofounder Ian Proulx took the stage at Summer Game Fest on Friday to promote his new game Splitgate 2 by calling out the current state of online shooters. Eschewing the marketing speak of most of his peers at the glossy showcase, he said he wants Titanfall 3 to come out and called his new game’s surprise battle royale mode “fucking awesome” while wearing a “Make FPS Great Again” hat. Suggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases Share SubtitlesOffEnglishview videoSuggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases Share SubtitlesOffEnglishSplitgate 2 is a free-to-play arena-style shooter where players deploy portals to mess with physics and the fabric of reality to outwit their opponents. “I grew up playing Halo and I’m tired of playing the same Call of Duty every year and I wish we could have Titanfall 3,” Proulx said on stage alongside host Geoff Keighley. He added that the new battle roayle mode aims to combine the old-school arena shooter sensibility with a mechanic to portal to other worlds. Out today on console and PC after a beta last month, 1047 revealed that the new mode is going live alongside the rest of the game. The subtext of Proulx’s pitch channeling President Trump’s slogan was clear: while EA cancels games and Activision leans into predictable cash-grabs, the underdog team at 1047 is shaking things up with a game by gamers for gamers. Meanwhile, the riff on “Make America Great Again” took place shortly after a clash between Los Angeles residents and law enforcement over ICE raids in the city’s garment district only blocks from where Keighley’s Summer Game Fest Play Days industry event takes place this weekend. Trump has ordered the immigration agency to arrest a record number of people every day for deportation even as ICE detention centers are criticized for overcrowding and lack of food. The original Splitgate launched in early access in 2019 and spiked in popularity. The party didn’t last, however, and by 2022, the studio abandoned the game to work on a new project. Last year it revealed that new project was actually just Splitgate 2. . #splitgate #dev #says #he039s #tired
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    Splitgate 2 Dev Says He's Tired Of Playing Call Of Duty And Wants Titanfall 3 While Wearing A 'Make FPS Great Again' Hat: 'I’m Not Here To Apologize'
    1047 Games cofounder Ian Proulx took the stage at Summer Game Fest on Friday to promote his new game Splitgate 2 by calling out the current state of online shooters. Eschewing the marketing speak of most of his peers at the glossy showcase, he said he wants Titanfall 3 to come out and called his new game’s surprise battle royale mode “fucking awesome” while wearing a “Make FPS Great Again” hat. Suggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases Share SubtitlesOffEnglishview videoSuggested ReadingThe Week In Games: A Star Wars Classic Returns & More New Releases Share SubtitlesOffEnglishSplitgate 2 is a free-to-play arena-style shooter where players deploy portals to mess with physics and the fabric of reality to outwit their opponents. “I grew up playing Halo and I’m tired of playing the same Call of Duty every year and I wish we could have Titanfall 3,” Proulx said on stage alongside host Geoff Keighley. He added that the new battle roayle mode aims to combine the old-school arena shooter sensibility with a mechanic to portal to other worlds. Out today on console and PC after a beta last month, 1047 revealed that the new mode is going live alongside the rest of the game. The subtext of Proulx’s pitch channeling President Trump’s slogan was clear: while EA cancels games and Activision leans into predictable cash-grabs, the underdog team at 1047 is shaking things up with a game by gamers for gamers. Meanwhile, the riff on “Make America Great Again” took place shortly after a clash between Los Angeles residents and law enforcement over ICE raids in the city’s garment district only blocks from where Keighley’s Summer Game Fest Play Days industry event takes place this weekend. Trump has ordered the immigration agency to arrest a record number of people every day for deportation even as ICE detention centers are criticized for overcrowding and lack of food. The original Splitgate launched in early access in 2019 and spiked in popularity. The party didn’t last, however, and by 2022, the studio abandoned the game to work on a new project. Last year it revealed that new project was actually just Splitgate 2. .
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  • I had a claustrophobic meltdown after getting stuck in a glitch

    The nightmare was real, the situation was not.Revenge of the Savage Planet, an adventure spread across a number of distant — and quite savage! — planets, invites nonlinear exploration. To complete its missions and discover all of its secrets, you must leap into an unknown where the otherworldly flora, fauna, and even the inorganic material are primed to kill you. So, shortly after assembling an underwater scooter that allowed my robot sidekick to whisk me through the depths of alien oceans, I descended into a series of caverns under the Zenithian Rift to see what was going on down there. The specters of death I encountered below weren’t even designed to haunt me.In Raccoon Logic’s sequel to Journey to the Savage Planet, players are tasked with scanning every object in every nook and cranny to assemble an exhaustive log of materials located on each planet. At first, the task is a walk in thepark: find a tree, scan a tree. Find a slobbering beastie, scan a slobbering beastie. But a counter on the map charting your scannables becomes the most daunting subtask — can I really find every single micro scannable? I found myself longing after completing the core missions. To really 100% this, there was even more reason to venture into the most uninviting spaces, including a dark underwater cave on Zenithian Rift that absolutely did not look like it contained any scannable items. But I couldn’t not go in there.It took about two seconds for me to realize… I had made a horrible mistake. While the cave was easily accessible from the water, there were no enemy or collectible breadcrumbs to suggest this was a place the folks at Raccoon Logic intended for me to. I was lured in by curiosity, but the joy of discovery in Revenge of the Savage Planet got the best of me. Now I was stuck. I had stumbled into a graphical anomaly, an in-game black hole that had an entrance but no apparent exit. In Revenge of the Savage Planet, you can’t beam back to starting locations on the fly or off yourself in order to respawn from your last save. In a clever but likely divisive design choice, the game forces you to navigate to transporters spread across the worlds in order to beam off to your next desired location, which forces traversal and new encounters. But it meant that while bumbling around in the dark, hoping to find a way out of my watery grave, I couldn’t simply die and move on. I was actually trapped, and in a scenario I haven’t experienced in quite some time, feeling IRL like I was actually trapped.I already don’t do well with underwater levels out of an intense fear of drowning. Luckily for me, most games will throw me the lifeline of a visual countdown to illustrate oxygen levels, ensuringI surface in time andI don’t hyperventilate over the stress of surfacing in time. Revenge of the Savage Planet doesn’t need that because there’s no punishment for enjoying the waters; you’re already in a spacesuit and the challenges you encounter via underwater scooter require a bunch of time-intensive back and forth. Doing it all on limited air would simply not be fun. But that meant, stuck in this tight underwater cave, I would never die. I was in limbo. Or maybe I was in hell.I spent far too long searching for a route out. Streaks of light bled in from a theoretical escape that I could never reach — any time I thought I was close, I bumped into a new rock and found myself jetting in the opposite direction. Not since I watched The Rescue, the riveting-yet-terrifying documentary about the team of divers who squeezed through cave passageways to free 12 trapped Thai soccer players, had my apparent claustrophobia had its way with my nerves. I can’t quite explain why I pushed myself over the edge to find an in-game solution to this unintentional challenge, except to say that I really wanted to do a good job at Revenge of the Savage Planet.Most glitches are considered errors by programmers, annoyances by players, and occasionally shortcuts for the speedrunner crowd. Revenge of the Savage Planet’s death cave might fall into the first two categories, but it’s a harrowing experience I ultimately appreciated, a unique screw up that could only happen in a game. I have never felt truly trapped in a film, despite the best efforts of 3D stereoscopic effects and 4DX rumble seats. After finally rebooting Revenge of the Savage Planet, I had to give myself a few minutes to let my heart rate die down before I grabbed the controller. But I got right back to it. Sure, this was a glitch, but in a game where exploration is everything, leaping into a true unknown — one that the creators of the game clearly didn’t intend me to find — was its own form of success.Revenge of the Savage Planet is currently available for PC, Playstation, and Xbox, and it’s currently on Game Pass.See More:
    #had #claustrophobic #meltdown #after #getting
    I had a claustrophobic meltdown after getting stuck in a glitch
    The nightmare was real, the situation was not.Revenge of the Savage Planet, an adventure spread across a number of distant — and quite savage! — planets, invites nonlinear exploration. To complete its missions and discover all of its secrets, you must leap into an unknown where the otherworldly flora, fauna, and even the inorganic material are primed to kill you. So, shortly after assembling an underwater scooter that allowed my robot sidekick to whisk me through the depths of alien oceans, I descended into a series of caverns under the Zenithian Rift to see what was going on down there. The specters of death I encountered below weren’t even designed to haunt me.In Raccoon Logic’s sequel to Journey to the Savage Planet, players are tasked with scanning every object in every nook and cranny to assemble an exhaustive log of materials located on each planet. At first, the task is a walk in thepark: find a tree, scan a tree. Find a slobbering beastie, scan a slobbering beastie. But a counter on the map charting your scannables becomes the most daunting subtask — can I really find every single micro scannable? I found myself longing after completing the core missions. To really 100% this, there was even more reason to venture into the most uninviting spaces, including a dark underwater cave on Zenithian Rift that absolutely did not look like it contained any scannable items. But I couldn’t not go in there.It took about two seconds for me to realize… I had made a horrible mistake. While the cave was easily accessible from the water, there were no enemy or collectible breadcrumbs to suggest this was a place the folks at Raccoon Logic intended for me to. I was lured in by curiosity, but the joy of discovery in Revenge of the Savage Planet got the best of me. Now I was stuck. I had stumbled into a graphical anomaly, an in-game black hole that had an entrance but no apparent exit. In Revenge of the Savage Planet, you can’t beam back to starting locations on the fly or off yourself in order to respawn from your last save. In a clever but likely divisive design choice, the game forces you to navigate to transporters spread across the worlds in order to beam off to your next desired location, which forces traversal and new encounters. But it meant that while bumbling around in the dark, hoping to find a way out of my watery grave, I couldn’t simply die and move on. I was actually trapped, and in a scenario I haven’t experienced in quite some time, feeling IRL like I was actually trapped.I already don’t do well with underwater levels out of an intense fear of drowning. Luckily for me, most games will throw me the lifeline of a visual countdown to illustrate oxygen levels, ensuringI surface in time andI don’t hyperventilate over the stress of surfacing in time. Revenge of the Savage Planet doesn’t need that because there’s no punishment for enjoying the waters; you’re already in a spacesuit and the challenges you encounter via underwater scooter require a bunch of time-intensive back and forth. Doing it all on limited air would simply not be fun. But that meant, stuck in this tight underwater cave, I would never die. I was in limbo. Or maybe I was in hell.I spent far too long searching for a route out. Streaks of light bled in from a theoretical escape that I could never reach — any time I thought I was close, I bumped into a new rock and found myself jetting in the opposite direction. Not since I watched The Rescue, the riveting-yet-terrifying documentary about the team of divers who squeezed through cave passageways to free 12 trapped Thai soccer players, had my apparent claustrophobia had its way with my nerves. I can’t quite explain why I pushed myself over the edge to find an in-game solution to this unintentional challenge, except to say that I really wanted to do a good job at Revenge of the Savage Planet.Most glitches are considered errors by programmers, annoyances by players, and occasionally shortcuts for the speedrunner crowd. Revenge of the Savage Planet’s death cave might fall into the first two categories, but it’s a harrowing experience I ultimately appreciated, a unique screw up that could only happen in a game. I have never felt truly trapped in a film, despite the best efforts of 3D stereoscopic effects and 4DX rumble seats. After finally rebooting Revenge of the Savage Planet, I had to give myself a few minutes to let my heart rate die down before I grabbed the controller. But I got right back to it. Sure, this was a glitch, but in a game where exploration is everything, leaping into a true unknown — one that the creators of the game clearly didn’t intend me to find — was its own form of success.Revenge of the Savage Planet is currently available for PC, Playstation, and Xbox, and it’s currently on Game Pass.See More: #had #claustrophobic #meltdown #after #getting
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    I had a claustrophobic meltdown after getting stuck in a glitch
    The nightmare was real, the situation was not.Revenge of the Savage Planet, an adventure spread across a number of distant — and quite savage! — planets, invites nonlinear exploration. To complete its missions and discover all of its secrets, you must leap into an unknown where the otherworldly flora, fauna, and even the inorganic material are primed to kill you. So, shortly after assembling an underwater scooter that allowed my robot sidekick to whisk me through the depths of alien oceans, I descended into a series of caverns under the Zenithian Rift to see what was going on down there. The specters of death I encountered below weren’t even designed to haunt me.In Raccoon Logic’s sequel to Journey to the Savage Planet, players are tasked with scanning every object in every nook and cranny to assemble an exhaustive log of materials located on each planet. At first, the task is a walk in the (overgrown killer) park: find a tree, scan a tree. Find a slobbering beastie, scan a slobbering beastie. But a counter on the map charting your scannables becomes the most daunting subtask — can I really find every single micro scannable? I found myself longing after completing the core missions. To really 100% this, there was even more reason to venture into the most uninviting spaces, including a dark underwater cave on Zenithian Rift that absolutely did not look like it contained any scannable items. But I couldn’t not go in there.It took about two seconds for me to realize… I had made a horrible mistake. While the cave was easily accessible from the water, there were no enemy or collectible breadcrumbs to suggest this was a place the folks at Raccoon Logic intended for me to. I was lured in by curiosity, but the joy of discovery in Revenge of the Savage Planet got the best of me. Now I was stuck. I had stumbled into a graphical anomaly, an in-game black hole that had an entrance but no apparent exit. In Revenge of the Savage Planet, you can’t beam back to starting locations on the fly or off yourself in order to respawn from your last save. In a clever but likely divisive design choice, the game forces you to navigate to transporters spread across the worlds in order to beam off to your next desired location, which forces traversal and new encounters. But it meant that while bumbling around in the dark, hoping to find a way out of my watery grave, I couldn’t simply die and move on. I was actually trapped, and in a scenario I haven’t experienced in quite some time, feeling IRL like I was actually trapped.I already don’t do well with underwater levels out of an intense fear of drowning. Luckily for me, most games will throw me the lifeline of a visual countdown to illustrate oxygen levels, ensuring (1) I surface in time and (2) I don’t hyperventilate over the stress of surfacing in time. Revenge of the Savage Planet doesn’t need that because there’s no punishment for enjoying the waters; you’re already in a spacesuit and the challenges you encounter via underwater scooter require a bunch of time-intensive back and forth. Doing it all on limited air would simply not be fun. But that meant, stuck in this tight underwater cave, I would never die. I was in limbo. Or maybe I was in hell.I spent far too long searching for a route out. Streaks of light bled in from a theoretical escape that I could never reach — any time I thought I was close, I bumped into a new rock and found myself jetting in the opposite direction. Not since I watched The Rescue, the riveting-yet-terrifying documentary about the team of divers who squeezed through cave passageways to free 12 trapped Thai soccer players, had my apparent claustrophobia had its way with my nerves. I can’t quite explain why I pushed myself over the edge to find an in-game solution to this unintentional challenge, except to say that I really wanted to do a good job at Revenge of the Savage Planet.Most glitches are considered errors by programmers, annoyances by players, and occasionally shortcuts for the speedrunner crowd. Revenge of the Savage Planet’s death cave might fall into the first two categories, but it’s a harrowing experience I ultimately appreciated, a unique screw up that could only happen in a game. I have never felt truly trapped in a film, despite the best efforts of 3D stereoscopic effects and 4DX rumble seats. After finally rebooting Revenge of the Savage Planet, I had to give myself a few minutes to let my heart rate die down before I grabbed the controller. But I got right back to it. Sure, this was a glitch, but in a game where exploration is everything, leaping into a true unknown — one that the creators of the game clearly didn’t intend me to find — was its own form of success.Revenge of the Savage Planet is currently available for PC, Playstation, and Xbox, and it’s currently on Game Pass.See More:
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