Researchers unexpectedly discovered toxic airborne pollutants in Oklahoma. The image above depicts a field in Oklahoma. Credit: Shutterstock University of Colorado Boulder researchers made the first-ever airborne detection of Medium Chain Chlorinated Paraffins (MCCPs) in the Western Hemisphere. Sometimes, scientific research feels a lot like solving a mystery. Scientists head into the field with a clear goal and a solid hypothesis, but then the data reveals something surprising. That’s when the real detective work begins. This is exactly what happened to a team from the University of Colorado Boulder during a recent field study in rural Oklahoma. They were using a state-of-the-art instrument to track how tiny particles form and grow in the air. But instead of just collecting expected data, they uncovered something completely new: the first-ever airborne detection of Medium Chain Chlorinated Paraffins (MCCPs), a kind of toxic organic pollutant, in the Western Hemisphere. The teams findings were published in ACS Environmental Au. “It’s very exciting as a scientist to find something unexpected like this that we weren’t looking for,” said Daniel Katz, CU Boulder chemistry PhD student and lead author of the study. “We’re starting to learn more about this toxic, organic pollutant that we know is out there, and which we need to understand better.” MCCPs are currently under consideration for regulation by the Stockholm Convention, a global treaty to protect human health from long-standing and widespread chemicals. While the toxic pollutants have been measured in Antarctica and Asia, researchers haven’t been sure how to document them in the Western Hemisphere’s atmosphere until now. From Wastewater to Farmlands MCCPs are used in fluids for metal working and in the construction of PVC and textiles. They are often found in wastewater and as a result, can end up in biosolid fertilizer, also called sewage sludge, which is created when liquid is removed from wastewater in a treatment plant. In Oklahoma, researchers suspect the MCCPs they identified came from biosolid fertilizer in the fields near where they set up their instrument. “When sewage sludges are spread across the fields, those toxic compounds could be released into the air,” Katz said. “We can’t show directly that that’s happening, but we think it’s a reasonable way that they could be winding up in the air. Sewage sludge fertilizers have been shown to release similar compounds.” MCCPs little cousins, Short Chain Chlorinated Paraffins (SCCPs), are currently regulated by the Stockholm Convention, and since 2009, by the EPA here in the United States. Regulation came after studies found the toxic pollutants, which travel far and last a long time in the atmosphere, were harmful to human health. But researchers hypothesize that the regulation of SCCPs may have increased MCCPs in the environment. “We always have these unintended consequences of regulation, where you regulate something, and then there’s still a need for the products that those were in,” said Ellie Browne, CU Boulder chemistry professor, CIRES Fellow, and co-author of the study. “So they get replaced by something.” Measurement of aerosols led to a new and surprising discovery Using a nitrate chemical ionization mass spectrometer, which allows scientists to identify chemical compounds in the air, the team measured air at the agricultural site 24 hours a day for one month. As Katz cataloged the data, he documented the different isotopic patterns in the compounds. The compounds measured by the team had distinct patterns, and he noticed new patterns that he immediately identified as different from the known chemical compounds. With some additional research, he identified them as chlorinated paraffins found in MCCPs. Katz says the makeup of MCCPs are similar to PFAS, long-lasting toxic chemicals that break down slowly over time. Known as “forever chemicals,” their presence in soils recently led the Oklahoma Senate to ban biosolid fertilizer. Now that researchers know how to measure MCCPs, the next step might be to measure the pollutants at different times throughout the year to understand how levels change each season. Many unknowns surrounding MCCPs remain, and there’s much more to learn about their environmental impacts. “We identified them, but we still don’t know exactly what they do when they are in the atmosphere, and they need to be investigated further,” Katz said. “I think it’s important that we continue to have governmental agencies that are capable of evaluating the science and regulating these chemicals as necessary for public health and safety.” Reference: “Real-Time Measurements of Gas-Phase Medium-Chain Chlorinated Paraffins Reveal Daily Changes in Gas-Particle Partitioning Controlled by Ambient Temperature” by Daniel John Katz, Bri Dobson, Mitchell Alton, Harald Stark, Douglas R. Worsnop, Manjula R. Canagaratna and Eleanor C. Browne, 5 June 2025, ACS Environmental Au. DOI: 10.1021/acsenvironau.5c00038 Never miss a breakthrough: Join the SciTechDaily newsletter.

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]

“Is that concrete all around, or is it in my head?” asked Ian Hunter in “All the Young Dudes,” the song David Bowie wrote for Mott the Hoople in 1972. Concrete is all around us, and we haven’t quite wrapped our heads around it. It’s one of the indispensable materials of modernity; as we try to decarbonize the built environment, it’s part of the problem, and innovations in its composition may become part of the solution. Understanding its history more clearly, the Skyscraper Museum’s new exhibition in Manhattan implies, just might help us employ it better. Concrete is “the second most used substance in the world, after water,” the museum’s founder/director/curator Carol Willis told AN during a recent visit. For plasticity, versatility, and compressive strength, reinforced concrete is hard to beat, though its performance is more problematic when assessed by the metric of embodied and operational carbon, a consideration the exhibition acknowledges up front. In tall construction, concrete has become nearly hegemonic, yet its central role, contend Willis and co-curator Thomas Leslie, formerly of Foster + Partners and now a professor at the University of Illinois, Urbana-Champaign, is underrecognized by the public and by mainstream architectural history. The current exhibition aims to change that perception. The Skyscraper Museum in Lower Manhattan features an exhibition, The Modern Concrete Skyscraper, which examines the history of material choices in building tall towers. (Courtesy the Skyscraper Museum) The Modern Concrete Skyscraper examines the history of tall towers’ structural material choices, describing a transition from the early dominance of steel frames to the contemporary condition, in which most large buildings rely on concrete. This change did not happen instantly or for any single reason but through a combination of technical and economic factors, including innovations by various specialists, well-recognized and otherwise; the availability of high-quality limestone deposits near Chicago; and the differential development of materials industries in nations whose architecture grew prominent in recent decades. As supertalls reach ever higher—in the global race for official height rankings by the Council on Tall Buildings and Urban Habitat (CTBUH) and national, corporate, or professional bragging rights—concrete’s dominance may not be permanent in that sector, given the challenge of pumping the material beyond a certain height. (The 2,717-foot Burj Khalifa, formerly Burj Dubai, uses concrete up to 1,987 and steel above that point; Willis quotes SOM’s William Baker describing it as “the tallest steel building with a concrete foundation of 156 stories.”) For the moment, however, concrete is ahead of its chief competitors, steel and (on a smaller scale) timber. Regardless of possible promotional inferences, Willis said, “we did not work with the industry in any way for this exhibition.” “The invention of steel and the grid of steel and the skeleton frame is only the first chapter of the history of the skyscraper,” Willis explained. “The second chapter, and the one that we’re in now, is concrete. Surprisingly, no one had ever told that story of the skyscraper today with a continuous narrative.” The exhibition traces the use of concrete back to the ancient Roman combination of aggregate and pozzolana—the chemical formula for which was “largely lost with the fall of the Roman Empire,” though some Byzantine and medieval structures approximated it. From there, the show explores comparable materials’ revival in 18th-century England, the patenting of Portland cement by Leeds builder Joseph Aspdin in 1824, the proof-of-concept concrete house by François Coignet in 1856, and the pivotal development of rebar in the mid-19th century, with overdue attention to Ernest Ransome’s 1903 Ingalls Building in Cincinnati, then the world’s tallest concrete building at 15 stories and arguably the first concrete skyscraper. The exhibition includes a timeline that depicts concrete’s origins in Rome to its contemporary use in skyscraper construction. (Courtesy the Skyscraper Museum) Baker’s lectures, Willis reported, sometimes pose a deceptively simple question: “‘What is a skyscraper?’ In 1974, when the World Trade Center and Sears Tower are just finished, you would say it’s a very tall building that is built of steel, an office building in North America. But if you ask that same question today, the answer is: It’s a building that is mixed-use, constructed of concrete, and [located] in Asia or the Middle East.” The exhibition organizes the history of concrete towers by eras of engineering innovation, devoting special attention to the 19th- and early-20th-century “patent era” of Claude Allen Porter Turner (pioneer in flat-slab flooring and mushroom columns) and Henry Chandlee Turner (founder of Turner Construction), Ransome (who patented twisted-iron rebar), and François Hennebique (known for the re-inforced concrete system exemplified by Liverpool’s Royal Liver Building, the world’s tallest concrete office building when completed in 1911). In the postwar era, “concrete comes out onto the surface [as] both a structural material and aesthetic.” Brutalism, perhaps to some observers’ surprise, “does not figure very large in high-rise design,” Willis said, except for Paul Rudolph’s Tracey Towers in the Bronx. The exhibition, however, devotes considerable attention to the work of Pier Luigi Nervi, Bertrand Goldberg (particularly Marina City), and SOM’s Fazlur Khan, pioneer of the structural tube system in the 1960s and 1970s—followed by the postmodernist 1980s, when concrete could express either engineering values or ornamentation. The exhibition highlights a number of concrete towers, including Paul Rudolph’s Tracey Towers in the Bronx. (Courtesy the Skyscraper Museum) “In the ’90s, there were material advances in engineering analysis and computerization that helped to predict performance, and so buildings can get taller and taller,” Willis said. The current era, if one looks to CTBUH rankings, is dominated by the supertalls seen in Dubai, Shanghai, and Kuala Lumpur, after the Petronas Towers (1998) “took the title of world’s tallest building from North America for the first time and traumatized everybody about that.” The previous record holder, Chicago’s Sears (now Willis) Tower, comprised steel structural tubes on concrete caissons; with Petronas, headquarters of Malaysia’s national petroleum company of that name, a strong concrete industry was represented but a strong national steel industry was lacking, and as Willis frequently says, form follows finances. In any event, by the ’90s concrete was already becoming the standard material for supertalls, particularly on soft-soiled sites like Shanghai, where its water resistance and compressive strength are well suited to foundation construction. Its plasticity is also well suited to complex forms like the triangular Burj, Kuala Lumpur’s Merdeka 118, and (if eventually completed) the even taller Jeddah Tower, designed to “confuse the wind,” shed vortices, and manage wind forces. Posing the same question Louis Kahn asked about the intentions of a brick, Willis said, with concrete “the answer is: anything you want.” The exhibition is front-loaded with scholarly material, presenting eight succinct yet informative wall texts on the timeline of concrete construction. The explanatory material is accompanied by ample photographs as well as structural models on loan from SOM, Pelli Clarke & Partners, and other firms. Some materials are repurposed from the museum’s previous shows, particularly Supertall! (2011–12) and Sky High and the Logic of Luxury (2013–14). The models allow close examination of the Burj Khalifa, Petronas Towers, Jin Mao Tower, Merdeka 118, and others, including two unbuilt Chicago projects that would have exceeded 2,000 feet: the Miglin-Beitler Skyneedle (Cesar Pelli/Thornton Tomasetti) and 7 South Dearborn (SOM). The Burj, Willis noted, was all structure and no facade for a time: When its curtain-wall manufacturer, Schmidlin, went bankrupt in 2006, it “ended up going to 100 stories without having a stitch of glass on it,” temporarily becoming a “1:1 scale model of the structural system up to 100 stories.” Its prominence justifies its appearance here in two models, including one from RWDI’s wind-tunnel studies. Eero Saarinen’s only skyscraper, built for CBS in 1965 and also known as “Black Rock,” under construction in New York City. (Courtesy Eero Saarinen Collection, Manuscripts, and Archives, Yale University Library) The exhibition opened in March, with plans to stay up at least through October (Willis prefers to keep the date flexible), with accompanying lectures and panels to be announced on the museum’s website (skyscraper.org). Though the exhibition’s full textual and graphic content is available online, the physical models alone are worth a trip to the Battery Park City headquarters. Intriguing questions arise from the exhibition without easy answers, setting the table for lively discussion and debate. One is whether the patenting of innovations like Ransome bar and the Système Hennebique incentivized technological progress or hindered useful technology transfer. Willis speculated, “Did the fact that there were inventions and patents mean that competition was discouraged, that the competition was only in the realm of business, rather than advancing the material?” A critical question is whether research into the chemistry of concrete, including MIT’s 2023 report on the self-healing properties of Roman pozzolana and proliferating claims about “green concrete” using alternatives to Portland cement, can lead to new types of the material with improved durability and lower emissions footprints. This exhibition provides a firm foundation in concrete’s fascinating history, opening space for informed speculation about its future. Bill Millard is a regular contributor to AN.

Missing the big picture US science is being wrecked, and its leadership is fighting the last war Facing an extreme budget, the National Academies hosted an event that ignored it. John Timmer – Jun 4, 2025 6:00 pm | 16 Credit: JHVE Photo Credit: JHVE Photo Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more WASHINGTON, DC—The general outline of the Trump administration's proposed 2026 budget was released a few weeks back, and it included massive cuts for most agencies, including every one that funds scientific research. Late last week, those agencies began releasing details of what the cuts would mean for the actual projects and people they support. And the results are as bad as the initial budget had suggested: one-of-a-kind scientific experiment facilities and hardware retired, massive cuts in supported scientists, and entire areas of research halted. And this comes in an environment where previously funded grants are being terminated, funding is being held up for ideological screening, and universities have been subject to arbitrary funding freezes. Collectively, things are heading for damage to US science that will take decades to recover from. It's a radical break from the trajectory science had been on. That's the environment that the US's National Academies of Science found itself in yesterday while hosting the State of the Science event in Washington, DC. It was an obvious opportunity for the nation's leading scientific organization to warn the nation of the consequences of the path that the current administration has been traveling. Instead, the event largely ignored the present to worry about a future that may never exist. The proposed cuts The top-line budget numbers proposed earlier indicated things would be bad: nearly 40 percent taken off the National Institutes of Health's budget, the National Science Foundation down by over half. But now, many of the details of what those cuts mean are becoming apparent. NASA's budget includes sharp cuts for planetary science, which would be cut in half and then stay flat for the rest of the decade, with the Mars Sample Return mission canceled. All other science budgets, including Earth Science and Astrophysics, take similar hits; one astronomer posted a graphic showing how many present and future missions that would mean. Active missions that have returned unprecedented data, like Juno and New Horizons, would go, as would two Mars orbiters. As described by Science magazine's news team, "The plans would also kill off nearly every major science mission the agency has not yet begun to build." A chart prepared by astronomer Laura Lopez showing just how many astrophysics missions will be cancelled. Credit: Laura Lopez The National Science Foundation, which funds much of the US's fundamental research, is also set for brutal cuts. Biology, engineering, and education will all be slashed by over 70 percent; computer science, math and physical science, and social and behavioral science will all see cuts of over 60 percent. International programs will take an 80 percent cut. The funding rate of grant proposals is expected to drop from 26 percent to just 7 percent, meaning the vast majority of grants submitted to the NSF will be a waste of time. The number of people involved in NSF-funded activities will drop from over 300,000 to just 90,000. Almost every program to broaden participation in science will be eliminated. As for specifics, they're equally grim. The fleet of research ships will essentially become someone else's problem: "The FY 2026 Budget Request will enable partial support of some ships." We've been able to better pin down the nature and location of gravitational wave events as detectors in Japan and Italy joined the original two LIGO detectors; the NSF will reverse that progress by shutting one of the LIGOs. The NSF's contributions to detectors at the Large Hadron Collider will be cut by over half, and one of the two very large telescopes it was helping fund will be cancelled (say goodbye to the Thirty Meter Telescope). "Access to the telescopes at Kitt Peak and Cerro Tololo will be phased out," and the NSF will transfer the facilities to other organizations. The Department of Health and Human Services has been less detailed about the specific cuts its divisions will see, largely focusing on the overall numbers, which are down considerably. The NIH, which is facing a cut of over 40 percent, will be reorganized, with its 19 institutes pared down to just eight. This will result in some odd pairings, such as the dental and eye institutes ending up in the same place; genomics and biomedical imaging will likewise end up under the same roof. Other groups like the Centers for Disease Control and Prevention and the Food and Drug Administration will also face major cuts. Issues go well beyond the core science agencies, as well. In the Department of Energy, funding for wind, solar, and renewable grid integration has been zeroed out, essentially ending all programs in this area. Hydrogen and fuel cells face a similar fate. Collectively, these had gotten over $600 billion dollars in 2024's budget. Other areas of science at the DOE, such as high-energy physics, fusion, and biology, receive relatively minor cuts that are largely in line with the ones faced by administration priorities like fossil and nuclear energy. Will this happen? It goes without saying that this would amount to an abandonment of US scientific leadership at a time when most estimates of China's research spending show it approaching US-like levels of support. Not only would it eliminate many key facilities, instruments, and institutions that have helped make the US a scientific powerhouse, but it would also block the development of newer and additional ones. The harms are so widespread that even topics that the administration claims are priorities would see severe cuts. And the damage is likely to last for generations, as support is cut at every stage of the educational pipeline that prepares people for STEM careers. This includes careers in high-tech industries, which may require relocation overseas due to a combination of staffing concerns and heightened immigration controls. That said, we've been here before in the first Trump administration, when budgets were proposed with potentially catastrophic implications for US science. But Congress limited the damage and maintained reasonably consistent budgets for most agencies. Can we expect that to happen again? So far, the signs are not especially promising. The House has largely adopted the Trump administration's budget priorities, despite the fact that the budget they pass turns its back on decades of supposed concerns about deficit spending. While the Senate has yet to take up the budget, it has also been very pliant during the second Trump administration, approving grossly unqualified cabinet picks such as Robert F. Kennedy Jr. All of which would seem to call for the leadership of US science organizations to press the case for the importance of science funding to the US, and highlight the damage that these cuts would cause. But, if yesterday's National Academies event is anything to judge by, the leadership is not especially interested. Altered states As the nation's premier science organization, and one that performs lots of analyses for the government, the National Academies would seem to be in a position to have its concerns taken seriously by members of Congress. And, given that the present and future of science in the US is being set by policy choices, a meeting entitled the State of the Science would seem like the obvious place to address those concerns. If so, it was not obvious to Marcia McNutt, the president of the NAS, who gave the presentation. She made some oblique references to current problems, saying, that “We are embarking on a radical new experiment in what conditions promote science leadership, with the US being the treatment group, and China as the control," and acknowledged that "uncertainties over the science budgets for next year, coupled with cancellations of billions of dollars of already hard-won research grants, is causing an exodus of researchers." But her primary focus was on the trends that have been operative in science funding and policy leading up to but excluding the second Trump administration. McNutt suggested this was needed to look beyond the next four years. However, that ignores the obvious fact that US science will be fundamentally different if the Trump administration can follow through on its plans and policies; the trends that have been present for the last two decades will be irrelevant. She was also remarkably selective about her avoidance of discussing Trump administration priorities. After noting that faculty surveys have suggested they spend roughly 40 percent of their time handling regulatory requirements, she twice mentioned that the administration's anti-regulatory stance could be a net positive here (once calling it "an opportunity to help"). Yet she neglected to note that many of the abandoned regulations represent a retreat from science-driven policy. McNutt also acknowledged the problem of science losing the bipartisan support it has enjoyed, as trust in scientists among US conservatives has been on a downward trend. But she suggested it was scientists' responsibility to fix the problem, even though it's largely the product of one party deciding it can gain partisan advantage by raising doubts about scientific findings in fields like climate change and vaccine safety. The panel discussion that came after largely followed McNutt's lead in avoiding any mention of the current threats to science. The lone exception was Heather Wilson, president of the University of Texas at El Paso and a former Republican member of the House of Representatives and Secretary of the Air Force during the first Trump administration. Wilson took direct aim at Trump's cuts to funding for underrepresented groups, arguing, "Talent is evenly distributed, but opportunity is not." After arguing that "the moral authority of science depends on the pursuit of truth," she highlighted the cancellation of grants that had been used to study diseases that are more prevalent in some ethnic groups, saying "that's not woke science—that's genetics." Wilson was clearly the exception, however, as the rest of the panel largely avoided direct mention of either the damage already done to US science funding or the impending catastrophe on the horizon. We've asked the National Academies' leadership a number of questions about how it perceives its role at a time when US science is clearly under threat. As of this article's publication, however, we have not received a response. At yesterday's event, however, only one person showed a clear sense of what they thought that role should be—Wilson again, whose strongest words were directed at the National Academies themselves, which she said should "do what you've done since Lincoln was president," and stand up for the truth. John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 16 Comments

The joy of going camping is usually found in going off-grid for a few days and reconnecting with nature. However, having creature comforts like light and warmth, and even access to medical devices like a CPAP machine, make it worthwhile taking a portable power solution with you. That's where portable power stations come in. Think power banks, only bigger. Power stations come in a variety of power capacities and sizes, and that means that you can find a portable power station for every type of camping, no matter whether you're a backpacker, a car camper, or an RVer.  What is the best portable power station for camping right now?  We've tested dozens of portable power stations in a lab setting and have also done hands-on testing during camping trips and road trips. Based on both experiences, our pick for the best portable power station for camping overall is the Jackery Explorer 2000 Plus, thanks to its versatility and the amount of power it provides. As an avid camper myself, I've also included other portable power stations from brands like EcoFlow and Bluetti so you can improve your next camping experience. Sort by All The best portable power stations for camping in 2025 Show less View now at Amazon Jackery is a well-known brand in the power station space, and for good reason. Its versatile power stations consistently rank among our best products, thanks to the enormous power these devices provide and their flexibility in setup, especially in a camping scenario.Steve Conaway, the director of CNET Test Labs, at our sister site, has tested dozens of power stations and said the Jackery is one of his top picks. "The versatility of modularity is what makes this power station so impressive," Conaway said. "You can choose to take just the one unit for regular camping, but if you wanted a bigger setup to power a cabin, you could easily add on more units."Review: This portable battery station can power your home for 2 weeksAnd the great thing about this unit is that if you need more power storage capacity, you can add on the PackPlus E2000 Plus battery pack for an additional 2042.8Wh of electrical storage capacity to the system.Jackery has a long track record of building quality, durable, and long-lasting power stations -- which is exactly what you need if you are spending the big bucks on a power station.Remember that the more additions you add to this setup, the heavier it will be. On its own, it weighs 41.9 pounds but can reach well over 100 pounds with more units. Despite the weight, Reddit users note that the solar additions, in particular, have been useful in camping and outdoor situations.Jackery Explorer 2000 Plus specs: Watts/hr: 2042.8W | Continuous watts: 3000W | Surge watts: 6000W | Solar input (W): 1400 | Ports: 2 USB-A, 2 USB-C, 4 AC | Weight: 61.5 pounds Pros Clean, easy-to-read LCD display Expansion battery modules Solar panels are durable and highly efficient Wheels make moving it a lot easier Cons Expensive Jackery is a well-known brand in the power station space, and for good reason. Its versatile power stations consistently rank among our best products, thanks to the enormous power these devices provide and their flexibility in setup, especially in a camping scenario.Steve Conaway, the director of CNET Test Labs, at our sister site, has tested dozens of power stations and said the Jackery is one of his top picks. "The versatility of modularity is what makes this power station so impressive," Conaway said. "You can choose to take just the one unit for regular camping, but if you wanted a bigger setup to power a cabin, you could easily add on more units."Review: This portable battery station can power your home for 2 weeksAnd the great thing about this unit is that if you need more power storage capacity, you can add on the PackPlus E2000 Plus battery pack for an additional 2042.8Wh of electrical storage capacity to the system.Jackery has a long track record of building quality, durable, and long-lasting power stations -- which is exactly what you need if you are spending the big bucks on a power station.Remember that the more additions you add to this setup, the heavier it will be. On its own, it weighs 41.9 pounds but can reach well over 100 pounds with more units. Despite the weight, Reddit users note that the solar additions, in particular, have been useful in camping and outdoor situations.Jackery Explorer 2000 Plus specs: Watts/hr: 2042.8W | Continuous watts: 3000W | Surge watts: 6000W | Solar input (W): 1400 | Ports: 2 USB-A, 2 USB-C, 4 AC | Weight: 61.5 pounds Read More Show Expert Take Show less Show less Camping takes all sorts of forms, and there's a power station to suit everyone. For those who head outdoors in an RV or to a remote cabin, the EcoFlow Delta Pro Ultra (DPU) is a powerful option. EcoFlow debuted the Delta Pro Ultra at CES this year, and compared to the EcoFlow Delta Pro model, the Ultra has double the power and charges, a dedicated 4G LTE modem port to access the app in remote areas with weak Wi-Fi signals, and a 32-minute faster recharge time.ZDNET editor Maria Diaz went hands-on with this unit and called it the "Swiss Army Knife of home backup systems," and its impressive specs back that claim up. The single unit has a 6kWh capacity, 7200W output, and 5.6kW solar input, allowing it to run an entire RV or cabin, especially when stacked with other units for increased capacity.This great power packs a lot of weight,186.4 pounds, to be exact. However, it can be divided into two pieces: the inverter, the top portion, is 70 pounds, and the battery, the bottom portion, is 116 pounds. Diaz noted that her family experienced a power outage recently, and her husband was able to transport the battery part much more easily by separating the pieces.EcoFlow Delta Pro Ultra specs: Watts/hr. 7200W | Continuous watts: 6kWh | Surge watts: 10.8 kW | Solar input (W): 5.6kW | Ports: 2×USB-A, 2×USB-C (100W), 6×AC Output, 1×DC output | Weight: 186.4 pounds AC outputs 9 Total capacity 10 Expansion ready 10 USB ports 9 Max output 10 Pros Expandable to up to 90kWh Consumption insights in EcoFlow app Modular design Cons Expensive Heavy EcoFlow Delta Pro Ultra Best portable power station for RV camping 4.8 / 5 Score Camping takes all sorts of forms, and there's a power station to suit everyone. For those who head outdoors in an RV or to a remote cabin, the EcoFlow Delta Pro Ultra (DPU) is a powerful option. EcoFlow debuted the Delta Pro Ultra at CES this year, and compared to the EcoFlow Delta Pro model, the Ultra has double the power and charges, a dedicated 4G LTE modem port to access the app in remote areas with weak Wi-Fi signals, and a 32-minute faster recharge time.ZDNET editor Maria Diaz went hands-on with this unit and called it the "Swiss Army Knife of home backup systems," and its impressive specs back that claim up. The single unit has a 6kWh capacity, 7200W output, and 5.6kW solar input, allowing it to run an entire RV or cabin, especially when stacked with other units for increased capacity.This great power packs a lot of weight,186.4 pounds, to be exact. However, it can be divided into two pieces: the inverter, the top portion, is 70 pounds, and the battery, the bottom portion, is 116 pounds. Diaz noted that her family experienced a power outage recently, and her husband was able to transport the battery part much more easily by separating the pieces.EcoFlow Delta Pro Ultra specs: Watts/hr. 7200W | Continuous watts: 6kWh | Surge watts: 10.8 kW | Solar input (W): 5.6kW | Ports: 2×USB-A, 2×USB-C (100W), 6×AC Output, 1×DC output | Weight: 186.4 pounds Read More Show Expert Take Show less Show less Looking for something more compact for overnight camping or hiking? The EcoFlow River 2 Max 500 weighs just 13.1 pounds but has a battery capacity of 500Wh. In addition, you can recharge the unit using one of four methods: AC, solar, 12V in-car, or USB-C. If you choose AC, the unit can go from zero to 100% in an hour, which means you can leave charging to the last minute while camping.The company claims that one full charge of the River 2 Max can charge an iPhone 41 times, a drone 10 times, and an electric blanket eight times.ZDNET's Adrian Kingsley-Hughes tested this unit and called it "compact enough to be portable, big enough to be practical." "If you want to go totally off-grid, EcoFlow offers a 160W solar panel that can recharge the River 2 Max in about four hours," he wrote. "The panel is durable and waterproof to IP68, so it's the perfect adventure companion for the River 2 Max 500."Verified Amazon customers note that this compact unit has been helpful for everything from camping festivals to powering a CPAP machine in primitive areas.EcoFlow River 2 Max specs: Watts/hr: 500W | Continuous watts: 500W | Surge watts: 1000W | Solar input (W): 220W | Ports: 3 USB-A, 1 USB-C, 4 AC | Weight: 13.14 pounds Pros Compact and lightweight Durable build Inexpensive Cons More limited ports and power Looking for something more compact for overnight camping or hiking? The EcoFlow River 2 Max 500 weighs just 13.1 pounds but has a battery capacity of 500Wh. In addition, you can recharge the unit using one of four methods: AC, solar, 12V in-car, or USB-C. If you choose AC, the unit can go from zero to 100% in an hour, which means you can leave charging to the last minute while camping.The company claims that one full charge of the River 2 Max can charge an iPhone 41 times, a drone 10 times, and an electric blanket eight times.ZDNET's Adrian Kingsley-Hughes tested this unit and called it "compact enough to be portable, big enough to be practical." "If you want to go totally off-grid, EcoFlow offers a 160W solar panel that can recharge the River 2 Max in about four hours," he wrote. "The panel is durable and waterproof to IP68, so it's the perfect adventure companion for the River 2 Max 500."Verified Amazon customers note that this compact unit has been helpful for everything from camping festivals to powering a CPAP machine in primitive areas.EcoFlow River 2 Max specs: Watts/hr: 500W | Continuous watts: 500W | Surge watts: 1000W | Solar input (W): 220W | Ports: 3 USB-A, 1 USB-C, 4 AC | Weight: 13.14 pounds Read More Show Expert Take Show less Show less View now at Amazon Portable power stations can get pretty pricey, but this one from Bluetti currently retails at only $359 for Amazon Prime members, making it a great budget pick. Plus, it charges quickly, especially when utilizing its turbocharging feature. Kingsley-Hughes also tested this model and praised it for delivering enough power to energy-intensive devices during a road trip. "It has enough capacity to meet the needs of a small group for several days," he wrote, adding, "I've relied on the power station to charge my smartphone, cameras, drones, and laptops efficiently."In his testing, he also found that charging the station from a car's 12V outlet is particularly efficient for keeping the unit charged, as long as the battery is not drained too much.Verified customers praised the AC70 on Bluetti's website, with most of the reviewers saying they bought it for camping and were pleased with the experience of using it for this purpose. Bluetti AC70 specs: Watts/hr: 768W | Continuous watts: 1000W | Surge watts: 2000W | Solar input (W): 500W | Ports: 2 USB-A, 2 USB-C, 2 AC | Weight: 22.5 pounds Pros Turbocharge feature Affordable price Cons Some of the better features are only available by using the app Portable power stations can get pretty pricey, but this one from Bluetti currently retails at only $359 for Amazon Prime members, making it a great budget pick. Plus, it charges quickly, especially when utilizing its turbocharging feature. Kingsley-Hughes also tested this model and praised it for delivering enough power to energy-intensive devices during a road trip. "It has enough capacity to meet the needs of a small group for several days," he wrote, adding, "I've relied on the power station to charge my smartphone, cameras, drones, and laptops efficiently."In his testing, he also found that charging the station from a car's 12V outlet is particularly efficient for keeping the unit charged, as long as the battery is not drained too much.Verified customers praised the AC70 on Bluetti's website, with most of the reviewers saying they bought it for camping and were pleased with the experience of using it for this purpose. Bluetti AC70 specs: Watts/hr: 768W | Continuous watts: 1000W | Surge watts: 2000W | Solar input (W): 500W | Ports: 2 USB-A, 2 USB-C, 2 AC | Weight: 22.5 pounds Read More Show Expert Take Show less Show less What makes this portable power station so versatile for camping is the amount of power and port options. There's a 100W and 60W USB-C port on the front, along with four USB-A ports, so all your devices are covered. There is also a 12V car socket capable of outputting 120W of power and six AC outputs, each capable of 1500W or 2400W in a power surge.Kingsley-Hughes tested this unit and said in his review that the Anker 757 Powerhouse is "well thought out, not overly complicated, built with ergonomics in mind, and packs quite a lot of power." Review: Anker 757 PowerhouseAnker is a company that has been in the portable power market for many years, starting out with chargers and power banks, and then later making the leap to power stations. That long heritage is obvious when looking at the overall build quality of the Anker 757.Customer reviews note that adding portable solar panels allows for greater battery charge retention, especially while camping. Kingsley-Hughes said that while he wouldn't carry this 43.9- pound unit too far, the ergonomic handles distribute the weight well, so it's well built for moving from the garage to a truck or RV.Anker 757 Powerhouse specs: Watts/hr: 1229W | Continuous watts: 1500 | Surge watts: 2400 | Solar input (W): 600W | Ports: 4 USB-A, 2 USB-C, 6 AC | Weight: 43.9 pounds Pros Ergonomic design Lots of ports Large display Cons Solar charging could be better What makes this portable power station so versatile for camping is the amount of power and port options. There's a 100W and 60W USB-C port on the front, along with four USB-A ports, so all your devices are covered. There is also a 12V car socket capable of outputting 120W of power and six AC outputs, each capable of 1500W or 2400W in a power surge.Kingsley-Hughes tested this unit and said in his review that the Anker 757 Powerhouse is "well thought out, not overly complicated, built with ergonomics in mind, and packs quite a lot of power." Review: Anker 757 PowerhouseAnker is a company that has been in the portable power market for many years, starting out with chargers and power banks, and then later making the leap to power stations. That long heritage is obvious when looking at the overall build quality of the Anker 757.Customer reviews note that adding portable solar panels allows for greater battery charge retention, especially while camping. Kingsley-Hughes said that while he wouldn't carry this 43.9- pound unit too far, the ergonomic handles distribute the weight well, so it's well built for moving from the garage to a truck or RV.Anker 757 Powerhouse specs: Watts/hr: 1229W | Continuous watts: 1500 | Surge watts: 2400 | Solar input (W): 600W | Ports: 4 USB-A, 2 USB-C, 6 AC | Weight: 43.9 pounds Read More Show Expert Take Show less What is the best portable power station for camping? Based on our hands-on experience and in-lab testing, the Jackery Explorer 2000 Plus is the best portable power station for camping. Its modularity makes it a versatile option for all types of camping. Show more Which portable power station for camping is right for you? It depends on the type of camping you prefer before you choose which portable power station will fit your needs. Consider what devices you want to bring with you and keep powered and whether you will be staying in an RV or cabin vs. a tent. Choose this portable power station for camping... If you want... Jackery Explorer 2000 Plus The best overall option. It packs a lot of power at 3000 continuous watts, and its modularity makes it versatile for camping. EcoFlow Delta Pro Ultra A powerful portable power station best for RV camping. It can run an entire RV or cabin, especially when stacked with other units for increased capacity. EcoFlow River 2 Max 500A compact portable power station for camping. It weighs just 13.4 pounds and features 60 minute fast charging. Bluetti AC70 A budget-friendly portable power station for camping. This unit also has 2,000W surge capability and a turbocharging feature, which allows for super fast charging that can take it from flat to 80% in 45 minutes. Anker 757 Powerhouse  A versatile portable power station for camping with lots of ports. It also has an ergonomic build, making it easier to carry despite its weight. Show more Factors to consider when choosing the best portable power station for camping: Power stations are a significant investment, but they can ultimately upgrade your camping experience to allow for power off-grid. Before making our top picks, we considered several factors.Weight: Bigger isn't always better, especially when it comes to camping. Will the portable power station be wheeled down a paved trail, or will you be moving it from your vehicle to your camp? Do you want something you could carry in a backpack for a day? Battery capacity: If you plan to power an RV or bigger devices from your power station, you want as much battery capacity as you can afford, but for off-grid adventures, it's important to bear in mind that there's a penalty here in the form of weight.Cost: Some units cost several thousand dollars, while others cost a couple hundred. Plus, add-ons like battery packs and solar panels also increase the price.Charging: How do you plan on charging your power station? Are you mostly going to use AC power from an outlet, or do you want the independence of solar?Battery Chemistry: Lithium-ion (Li-ion) is the traditional battery technology, but the newer lithium iron phosphate batteries (LiFePO4) are safer and have a much longer lifespan. Show more How did we test these portable power stations for camping? Over the past few years, we've tested well over 100 different portable power stations to find out which are the best of the best. To do this efficiently, because it takes days to do properly, we've developed a comprehensive testing structure. This not only ensures that manufacturers aren't playing fast and loose with their spec sheet data but also checks whether the units are safe and reliable. Here's an overview of how we test portable power stations.Unboxing and visual inspectionCapacity testsLoad testingUPS capability testingThermal testsSafety testsReal-world usageFor more detailed information on how these tests are carried out, check out this post, where we explore the process more thoroughly.  Show more FAQs on portable power stations How long will a power station last while camping based on its watts? To figure this out, you're going to need to get a pencil and do some back of the envelope calculations.  You're going to need a couple of bits of information.First, you need to know what devices you are going to power. List them all, because forgetting that coffee pot or heated blanket could make the difference between the power station lasting all day, or giving up the ghost on you before the day is over.Specifically, you want to know how much power, in watts, each device draws. This information is usually found on a label on the device. For example, a heater might draw 1,000W, while a CPAP machine might draw 60W. This figure represents the maximum power consumption, and you will find that the power consumption of some devices, such as CPAP machines, fluctuates greatly, while for other devices, like the heater, the power consumption remains quite stable.Next, you need to know how long you plan on running your devices during a day, or between recharges of your power station. Your heater might run for two hours, while the CPAP machine could run for eight hours.Power station capacities are measured in watt-hours (Wh). A device drawing 1,000W running for one hour uses 1,000Wh. Therefore, the same device running for two hours will need 2,000Wh. Heaters are some of the most power-hungry devices that people find themselves needing to run.Similarly, a CPAP machine that uses 60W will consume 60Wh per hour, so running it for eight hours would consume 480Wh.Your total energy usage over 24 hours would then be 2,480Wh.Based on this, you might think that a 2,500Wh capacity power station would be sufficient. However, in reality, nothing is perfect, and there are energy losses in the system. The rule of thumb is to add 20% to your total and then round up to the next highest capacity available. So, you'd be looking at a power station with a capacity of around 3,000Wh to ensure you have enough stored power for the day. Show more How can I make my power station run longer? Simple: Find your biggest power draws and replace them with more energy efficient alternatives. For example, you might find that you can replace that 1,000W heater with a heated throw that only takes 100W to power. That quilt would run for 10 hours on the power that the heater would use in an hour!Another big power hog is incandescent lights. Swapping these out for LEDs will result in huge power savings and dramatically boost your power station's runtime.   Show more What is the difference between a power station and a power bank? The main difference between portable power stations and portable power banks is the amount of power and what they can charge. Power stations have AC outlets and allow you to charge more and bigger devices, including life-saving ones like a CPAP machine, a cooler, or a floodlight for the campsite while going off-grid.Power banks are much smaller and are best for charging devices like phones, headphones, and smartwatches.  Show more Other portable power stations we've tested Further ZDNET Tech Coverage Smartphones Smartwatches Tablets Laptops TVs Other Tech Resources ZDNET Recommends