Plain English with Derek Thompson - ChatGPT, Obesity Drugs, Exoplanet Images, and Medical Miracles: The Most Amazing Breakthroughs of 2022

Episode Date: December 13, 2022

Derek talks to economist and writer Eli Dourado about the most exciting scientific and technological discoveries of the year, from the AI toys that everybody seems to be playing with to lesser-known breakthroughs in bioscience, clean energy hardware, and precise atomic manipulation. Due to the holidays, we will be skipping our Friday episode this week. However, we’ll be back next Tuesday to revisit one of our favorite interviews from the past year as we inch closer to 2023. Host: Derek Thompson Guest: Eli Dourado Producer: Devon Manze Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Peace! We're out of here. Today's episode is one of my favorites of the year. Last week, I published an article in The Atlantic about the 10 greatest, coolest breakthroughs of 2022. That is, what were the most interesting and important discoveries or inventions in the last year across any scientific domain? Bioscience, clean energy, vaccinology, nanotechnology, AI. What was Apex Mountain for humankind? I've said before on this show that I think there is a negativity bias.

in news, which results in this list being a surprise for me and for many listeners. I think it's sneaky weird that this list is a surprise, that the most important breakthroughs of the year typically come as a shock because the news media is significantly more efficient at surfacing, and its readers are more efficient at sharing, news that makes us afraid or outrage, rather than news that makes us curious or even hopeful. For example, I'm I'm not sure that most people know we are in a golden age of obesity therapies. Until very, very recently, most reasonable doctors did not prescribe medications or pills or injectables for weight loss.

Like the term weight loss pill was very rightly a pejorative. But in just the last two years, there's been an extraordinary revolution in weight loss medication thanks to a happy accident. In the 2010s, patients on the diabetes medication somaglactlyde noticed something interesting. They were losing a ton of weight. And so the parent company, Novo Nordus, looked into this and they realized that the side effect of this diabetes medication wasn't a fluke. The diabetes medication seemed to mimic naturally occurring hormones in the body that regulated

the release of insulin and slowed down how fast patients' stomachs emptied. This year, the FDA approved injectable somaglotide for weight loss under a new name. Weigovie. And this is not the only weight loss medication now in the pipeline. A similar weight loss medication called Terseptide showed an average 20% reduction in patient's body weight in the latest clinical trial. There is another medication that Amgen is currently experimenting with. It's called AMG-133.

And in phase two trials, patients on the highest dose lost more than 14% of the patient. their body weight in less than three months. So this could be the dawn of a new age. Roughly 40% of Americans are technically obese, and we know that obesity can, in many cases, increase someone's risk of heart disease, high blood pressure. And for men, as we've just heard on a recent show, it seems correlated with declining sperm count as well. So this is a breakthrough worth celebrating. And also because every discovery can have positive and negative implications. I think it's a breakthrough worth watching as well. Another revolution that I think will maybe one day become synonymous with the 2020s

is the incredible blowout in generative AI tools. You've got image generating apps like stable diffusion, Dolly 2. These turn text prompts into lush illustrations. You can say something like, you know, show me a podcast host on Venus, smoking a cigarette and a style of Van Gogh, and it will produce something astonishingly beautiful, weird, inspiring. There are also large language models, such as chat GPT, which can answer complex questions, spit out bespoke Wikipedia articles and seconds, write song lyrics, and even conjure many essays. The results are quite uncanny and quite mind-blowing. So, for example, I was inspired by a few tweets that I saw that got Chat GPT to write poetry and religious verse, and I gave Chat GPT a cheeky little prompt. I said,

write a biblical verse in the style of the King James Bible about a Manhattan finance bro throwing up on his friends after having too many fireball shots. And in approximately eight seconds, This is what the AI wrote in response. And it came to pass that the finance bro, having imbibed too heavily of the fiery liquid, did vomit upon his companions. And great was a displeasure of the friends, for they were covered in the sick of their companion.

And the finance bro did wail and gnash his teeth, for he knew that he had transgressed and brought shame upon himself. Thus saith the Lord, quote, finance bro. And with this, the friends did forgive their companion, for they too had known the temptations of the flesh and the perils of excess. Like, that is amazing. I don't know what this thing is yet. I don't know if it will ultimately evolve into being a mere toy, if it will replace

me, if it will replace Google search, if it will merely be a second mind for the creative class, or if it heralds the end of the world. Whatever it is, it is a rather extraordinary feat of technology. And I think in time, we may consider it the most important breakthrough of the year. At last, today's guest is a return guest, Eli Dorado. He is an economist and a researcher and a writer who has his pulse on the frontier of invention and science as much as anybody else I know, especially across all the different domains that I wanted to touch on, bioscience, AI, hardware.

He is our guide to the future for the next 45 minutes. And if you have half as much fun listening to Eli as I had talking to him, I think you are in for a treat. I'm Derek Thompson. This is plain English. Hey, everybody, Derek here. The conversation you're about to listen to is about the most exciting and important scientific and technological breakthroughs of 2022.

And it was recorded just days before U.S. government scientists made a breakthrough in nuclear fusion. Fusion reactions are different from fission. That's what typical nuclear power has been. It emits no carbon, produces no long-lived radioactive waste. It's an extraordinary technology that could give us limitless zero-carbon power if we can scale it, if we can get it cheaper, if we can get it widely available. It's a thrilling, thrilling breakthrough that clearly would have made this podcast

if the news had broken a week earlier, six months earlier, 11 months earlier. Trust me, we're going to have many more episodes about this awesome breakthrough with nuclear fusion, just not this one. Okay, please enjoy. Eli Dorado, welcome back to the podcast. Thanks for having me on, Derek.

I am more excited to do this episode than I've been in a long time. I honestly find a lot of bad news interesting, And so I write about it a lot, and I podcast about it a lot. You know, alone time is up. Sperm counts are down. Bad news, bad news. But we're getting close to the holiday season,

and I really wanted to do an episode that doesn't make me want to self-eject from the planet. And I made a promise to myself this year that I would take time in December to research and break down what I considered the most interesting and important science and technological breakthroughs of the year. I just published this big piece in the Atlantic, breaking down my top 10, in the open, just before welcoming you on, I talked a little bit about my fascination with large language models like chat, GPT.

I want to save that for the end. What I want to talk about with you, because last time we had you on the show, you gave us this incredible tour of the scientific and technological frontier. I want you to walk with me through some of these incredible science and tech breakthroughs of 2022.

So let's start with science. Let's start with the cosmos. in July, NASA's James Webb Telescope sent back its first images of light from across the universe. And with just extraordinary clarity, this showed off these nebula that looked like neon soap bubbles and cragly red mountaintops. And one of them looked like a little sort of luminescent shrimp that was floating in a black soup. I mean, just amazing, amazing images that go back as far as 13 billion years ago. Okay, so they're clearly cool. Why are they important beyond just being cool? Well, there's so many reasons. So I think that you can do it in radio astronomy is a bunch of

different things, right? You can, you can learn more about sort of physics, right? Like the high, really high energy, large scale stuff in the universe, right? You can't do it in a lab on Earth, right? It's just, it can't be contained like that. And so the James Webb Space Telescope is going to be doing all kinds of experiments that take advantage of that, of that sort of the cosmos as like a physics laboratory. Right. And then the other thing that it's going to do a lot of is looking more locally at a lot of stuff we haven't really looked at before. So I'm really interested in actually looking at planets that are close by. So, like, you know, yes, the space, the James Webb can look very deep into the cosmos, but it can also look more closely to stuff that's only like, you know, 10 light years away or something like that.

And you can actually start to study the atmospheres of these planets that are nearby. And that could potentially tell us, you know, are there, is, is life common or is it not common in the cosmos, right? Like, I'm really curious about that question. Radio astronomy has already told us that interstellar space has organic molecules, right? Hundreds of organic molecules, including, like, amino acids, including amino acids that, like, we have in our bodies. Like, that exists in interstellar space. And we know that because, you know, we've had past measurements, right, from radio telescopes.

Every time we get a new, new instrument, a new, either a step change in, in sort of resolution or a new frequency that we get access to, we discover something new about the universe. I am most fascinated by the possibility of seeing into the moments, relatively the moments, the million years after the Big Bang, to learn more about the ultimate existential question. How did it all begin? Where did time and space and matter begin? What were the conditions of the universe 13 billion years ago?

How were they different than the conditions now? Was the universe ruled by a different set of laws? Can we learn maybe what those laws were by looking really, really closely at these different snapshots of 13 billion years ago? That's the most interest me. Just tell me a little bit more about what we could learn from these exoplanets that you're describing. So, like, we use our telescope to stare whatever, 5, 10 million, 5, 10 light years away from

Earth. You call this a shortish distance, but to me it seems relatively. long, now that you nor I are likely to ever go there. But we're looking into these atmospheres, maybe we're getting the view of these planets that in my mind, I think that it's a little bit similar to in like a Star Wars or Star Trek movie. When they show the planet sort of coming up, you start to see its color and the state of its atmosphere. What could we learn about these planets? Yeah, so different molecules in the atmosphere are going to emit different spectra. right and you could conceivably learn that there are you know molecules in the atmosphere that are you know

on earth or at least in earthlike environments are telltale signatures of life right so we could we could we could sort of maybe form hypotheses that um that some planets may have at least bacterial life on them uh from from looking at at at these atmospheres and I think the other question is about sort of the interaction of magnetospheres and stellar winds and so on. So Earth is fortunate to have a have a magnetosphere that keeps our atmosphere from having been blown away over the last billion years or so, right? So without that sort of the polarity of the Earth, right, the North Pole, the South Pole, the magnets, magnetic fields that arise from them, our atmosphere would have been blown away

by the solar wind. And so if you study exoplanets, we could sort of get an idea of like, how common is that? How common is it for an atmosphere to build up on a rocky planet? And if you ever did find a star system that had

a bunch of magnetic field, a bunch of planets with magnetic fields and all of them had atmospheres in them and, you know, what would be they might have interesting signatures and so on. That could be a sign of a terraforming civilization, right? You know, you could have, you could find, you know, like if I found, like, improbably that, like,

you know, have some base rate, infer some base rate from your other observations, if you found improbably that one star system had a bunch of planets that had atmospheres and magnetospheres, that would be a sign of something interesting that we would want to go check out. I would say so.

Yeah, that sounds pretty thrilling. All right, let's move to the next breakthrough that I want to talk about, which is a breakthrough around the disease, multiple sclerosis. There was a study done by a team of scientists that looked a large group of military service members, and it concluded there was very strong evidence

that the Epstein-Barr virus, EBV, which is best known for causing mononucleosis, might be a leading cause of MS, multiple sclerosis. Infection with EBV raised the odds of developing MS by a factor of 30. Now, many, many people get EBV. Many people contract this virus. Only a tiny minority of them seem to develop multiple sclerosis later in life. But it suggests that multiple sclerosis is like long EBV, maybe, the same way that we understand there to be COVID, which lots of people get, and then a small minority of them get long COVID,

the long virus. Eli, what do you think is the most, or what are the most significant implications of this discovery? For a long time, we've, you know, multiple sclerosis is a autoimmune disease, right? And there are a lot of autoimmune disease, and we kind of don't understand how they work, right? That sort of the autoimmune, I would even say it's an autoimmune hypothesis, right? That it's our body just sort of like fighting itself. But if multiple sclerosis is caused by EBV, it raises the possibility that maybe a lot of the diseases that we think of as autoimmune, maybe they are, maybe the etiology actually is pathological, they're pathogenic diseases. Which just, just for clarity, pathogenic disease means it's a disease that comes from

a bacteria or virus. Exactly. It lingers in our system for a while, the same way that we're familiar with the concept of long COVID. You know, people get COVID, it lingers for a while. And then it causes a range of things like, you know, brain fog or some kind of muscle weakness that we don't necessarily, it might be a little bit different from the immediate effects of COVID, but we consider it a part of long COVID. So maybe there's a bunch of diseases that have specific names like multilsclerosis,

but they're actually just long viruses or long bacteria. Exactly. Or maybe even not long. Maybe it's just, we don't know, we just have never found a pathogen, right? Like we like it could be just, it could be the non-long version of some virus as well. And so like, yeah, yeah, I think a, you know, a promising avenue would be for anybody that has a mystery disease or a disease where we don't, uh, you know, we don't know the cause.

Like, we should be like screening their blood and their other bodily fluids for, and just like, genetic sequence everything you find, right? If we, if we could genetic sequence everything we find in all of these patients, um, that might lead us to some more discoveries of, well, actually these, this thing that we thought was autoimmune was,

you know, it's like, becoming clear, right? There's another pathogen that causes it. So I think we're not at the end of sort of the sort of figuring out the role of pathogens. To me, it's like, all right, there's lots of research on treating MS, dealing with MS, which results in nerve damage, which disrupts sort of communication between the brain and the body. There's certain ways that you can think about treating a disease like that, whether it's

the treatments work on the immune system or the treatments do something about nerve communication. But with this knowledge, it might be the case that the clearest thing to do is to get vaccinologists to work on a vaccine against Epstein-Barr virus, which up to now was like, I don't know, kind of important to do.

Mononucleosis is a nuisance, but multil sclerosis is much more of a problem than mono. So this has clarified the cost of EBV on the human population, such that it might profitably redirect a lot of investment toward eradicating EBV from the human population. Is that right? Yeah, that's 100% right. You know, it's interesting, like, with MS,

there's all kinds of ideas of, like, how you could treat it, right? Like, people are saying, like, oh, I had MS and I, you know, ate a bunch of vegetables and, you know, and sort of changed my diet in some way and that held to get better. And, like, we still, like, that may or may not be true. We don't have a good way of evaluating that because we don't fully understand the causes. But if it is a virus and, of course, what you eat

affects your immune system, some of these stories start to make sense in a way that could be made consistent with sort of like scientific observation as well. I want to move on to another discovery that has a little bit of tie-in with the pandemic. And that is that we are very clearly in a golden age of vaccine research and maybe also vaccine production. There were a range of breakthroughs in the world of vaccines in the last

year. There was a record, one of the most successful trials for any vaccine in malaria came out this year in September. Oxford University scientists developed this malaria vaccine. Small trial, 450 children in Burkina Faso. But I found that three days, doses of the vaccine plus a booster shot was up to 80% effective at preventing infection. I mean, that is remarkable because malaria kills around 40,000 people every year, many of them children. It's not caused by a virus. It's caused by a plasmodium, which has so far been very difficult to vaccinate.

But these scientists from Oxford seem to have some success in coming up with a, uh, a, uh, a successful vaccine candidate. Another really interesting breakthrough in vaccines this year came against the flu. There was an experimental flu vaccine that was found to be protective against all known types of flu in animals. Now, I think every year, we get a flu shot, and that flu shot is bespoke to the kind of flu that is circulating. And the influenza virus family has 20 lineages, and a bunch of strains under all those

lineages, so we have to change the flu recipe every single year. If this vaccine worked, it would essentially lower the mortality ceiling of every kind of flu that we could possibly get in all the years to come, which would make a Spanish flu epidemic extremely unlikely. So those are some of the vaccine breakthroughs that we had this year. Eli, which of them do you consider most interesting, most important? Well, I think, you know, malaria is just such a huge case. killer and all of the sort of the tropics. It's incredibly important that we've made that advance. I think one thing that we're learning is that, you know, not all antibodies are the same, right?

You can have two different people who are exposed to the same disease and they're going to, like, their bodies might make slightly different antibodies in response to that virus or the bacterium or whatever it is. And so one of the things we're learning is you can target better and worse antibodies, right? And so being able to design a vaccine that generates an immune response, an antibody, that attacks like a conserved part of the virus, right? A part of the virus that doesn't mutate very, very much. you know, that is that is just like, that's a playbook that we can do over and over again.

There's not that many families of viruses, you know, in the world that infect humans. And we could do it potentially on all of them, right? Like, this is, like, we're getting to the point where viral infection might not be a thing that we have to live with in the next, you know, say two decades, right? Like, like, and people are talking about we could get rid of the common cold, right? And I think there's all kinds of questions about, you know, do we need occasional viral insults to our immune system to, like, keep our immune system sort of active, right?

I think, I think that's the kind of question that we're going to be facing because we have so many tools being developed that make us able to be, make more effective vaccines. That's great. Yeah, I think, you know, even if we don't fully eradicate viruses, I think what's interesting about this particular flu vaccine is that, and all the articles that I read, but very careful to point this out, this does not make it so that you cannot catch the 2023 flu or the 2024 flu or the 2025 flu, which, by the way, are almost certainly going to be different strains. Rather, it makes all of those strains significantly less. lethal. So something like the Spanish flu, the Spanish flu pandemic would be basically impossible if we could do something like this for the influenza family, for plasmodia like malaria,

for coronavirus as a family, not just this novel coronavirus, but for the family. It would mean with these sort of like family level mortality lowering, you know, pan vaccines that yes, people might in this future that I'm sketching out, they might still get sick, but we would turn everything into the common cold or something like it, right? No coronavirus would kill 10% of people over 80. No influenza would kill 100,000, 200,000 people a year, or in the cases of 1920, millions of people throughout the world. Everything would be a little bit more moderate. Is that future also something that could come into focus? I mean, yeah, it's very plausible.

But I think it would be shocking to me if people didn't go after even the common cold. Right. Like, you know, think about, you know, how much during sort of cold and flu season, like, people just missing work and stuff, like the economic cost of that, I would be surprised if nobody goes after it. Right. People are going to want protection, I think. Well, I don't know. People didn't want protection from COVID, right, in the vaccine. So maybe they won't want vaccines for everything. Half of the adults over 45 of particular, yeah, political ideology in this country, we weren't particularly eager. But yeah, the rest of the country was relatively eager. And people around the world were decently eager. Yes, exactly. What can you help me understand? Because, you know, before I go, like, way out over my skis and get way too excited about the future of ending all the viruses, like, um, Obviously, there's all sorts of scenarios in which we might be in a kind of, you know, they talk about like AI summers and AI winters. There's periods where the technology sprints forward and the period where the technology doesn't. It's possible that right now we're in a bit of a vaccinology summer. And in a few years, you might be in a vaccinology winter and realize, wow, it's actually really, really difficult to invent all of these, you know, pan-coronoviruses and pan influenza viruses. What would you say we learned in the pandemic that is responsible for this. summer that we're experiencing in anti-viral vaccinology.

I think it's mainly that we can go faster than the sort of the state of the art was before. You know, I wrote a piece at the beginning of the pandemic on how, you know, what we could do to accelerate vaccine approvals. And, you know, I thought we should just, you know, once somebody, a credible company had a candidate, we should let people try it, right? If they, you know, you need data one way or the other. You need to have guinea pigs.

If people want to do informed consent and like get a jab of an MRNA vaccine that's unproven, like they should have been allowed to. That was, that was my argument because I was worried that it was going to take years. The sort of the, it was very common before COVID to have a vaccine take 25 years to, to like be fully developed, go through all the trials. on, you know, 25 years might have been on the high side, but it was never, never under a year, right? And I thought we needed to just accelerate the whole process. Now, we did, you know, we unfortunately, you know, we kept the clinical trial requirement,

but somehow we made it through a lot faster, you know, it helps that a lot of the people who, got the vaccine, were exposed, you know, naturally. We didn't have challenge trials for the most part, but we just had an epidemic raging, right? A pandemic raging. And that enabled us to go faster. But even without that, I think we can, there's a lot of time that we can cut off the development cycle. And so, so anyway, so I think it's, I don't think it is like a summer, winter kind of thing. I think it's, it's here to stay that we're going to have a lot of progress. And there's just so many tools coming down the pike in in biology like the the labs are getting so advanced they're able to do so many interesting things that it would be it would be surprising if uh there was a slowdown right

the the big obstacle is like what can you get approved and what you know what can make it all the way through the clinical trials and and and and and two consumers um but you know the the scientists in the labs they're like wizards man um they're they're doing they're doing so much much exciting stuff. I'm glad you ended on that. The fact that the science is moving very, very quickly, we need to find a way for policy to move quickly, too. I have a piece in the magazine that comes out, I think the day this podcast comes out called the Eureka Theory of Progress is wrong. And I tell a story of Operation Warp Speed and exactly how it worked. And I say, what would it

mean to have an Operation Warp Speed for some other biological crisis that we recognize? Let's say Operation Warp Speed for Cancer. What would that mean? Well, in one hand, it would mean spending more money on research, right? Operation Warp Speed said, here's a bunch of money we're willing to spend on any of the pharmaceutical companies that come out with the vaccine in MRNA or attenuated, et cetera. We're going to spend money directly on the production of the material. But also it turned what you described as this 10 to 30-year obstacle course for new vaccines into a glide path.

It's like, we're going to make this possible in six months. So what would it mean to do that for cancer? And I talked to Heidi Williams at Stanford and the Institute for Progress, about this amazing paper she co-authored about how since the war in cancer was declared, 1971, Richard Nixon, the U.S. has way more late-stage cancer treatment pills and almost no cancer prevention medicine. So a ton of pills you can take when you're on stage three, stage four, but not a lot of cancer prevention. Why? Well, one answer, she said, is the cancer prevention clinical trials take forever, right? Because if you take a, you know, a lung cancer prevention

pill at 20, you might not know until you're 60 if it's actually prevented, you know, your lung cancer, 70, 80. And she said, you know, we have a solution for heart disease. We have surrogate endpoints, which is a wonky term for, we have short term proxies. You take a pill. We say, is your cholesterol going down? Is your blood pressure going down? And we're going to infer that if it is, this will prevent a heart disease later. If we could find a way to develop these short-term proxies for cancer prevention and clinical trials, we could have short clinical trials for multi-decade cancer prevention medicines, which would mean an explosion of cancer prevention therapies.

You wouldn't even need any kind of revolution on the invention side. Scientists could keep doing exactly what they're doing, and we could like 10x the number of cancer prevention pills that Americans can take. And so going through that little bit of research may be really optimistic that the scientists are doing incredible work, and we need to learn from Operation Warp Speed, how to get little innovations on the policy side to make this world abundant in anti-cancer therapies.

Let's move on to clean energy. You have taught me a lot about geothermal energy, which basically means drilling deep into the ground to use the Earth's heat. Pretty much it's geothermal-heated water for power. And geothermal is such a cool energy source because it's more consistent than wind or solar.

The middle of the Earth is always hot in a way that the wind isn't always blowing. And it doesn't have the waste concerns of nuclear. But the problem is that there's some parts of the world that are fantastic for geothermal, like Iceland. And there's other parts of the world that are not good for geothermal because it takes so long and so hard to dig

to that part of the Earth's crust that has the geothermal heated water. You told me about a solution to this problem. Tell me about that solution. Yeah, of course. So in my day job, I spent a lot of time looking at technologies and diving deep into them. And geothermal is one of those. And I got so excited about this particular solution that I actually ended up investing personally.

So this is a company called Quays. They're a spin out of MIT. and they took something out of the fusion lab. So fusion to sort of feed the fusion reaction, scientists have this tool called a gyrotron that produces millimeter wave energy. And what Quays is doing is they say, okay. Can you just like I'm in sixth grade,

what is millimeter wave energy? Millimeter wave energy is like radio energy. So like light is a radioelectric energy, right? It's photons, right? Photons, so visible light is in the 400 to 700 nanometer wavelength range, right? And so imagine photons, instead of being in that spectrum, they're just moving in the millimeter sort of range of a spectrum, right? So that's really it's light that's been, the wavelength has been, is longer than light, right?

It's photons, though. It's exactly the same as same particle, right? And so what they've figured out is, you know, you can drill mechanically very well until, you know, through the sedimentary rock and so on. But at some point, you hit basement rock. And if you take a gyrochon at the surface and point it down into the ground and have like sort of a corrugated steel tube that sort of guides the waves down, what you can do is produce a concentration of millimeter wave energy at the bottom of the hole that vaporizes the granite. and you know just completely destroys it the ashes like sort of you have to you have to think about like how do you circulate a gas there to pull the ash out

but you vaporize granite you you melt the side of the hole so that it becomes like a liner so it becomes 10 times stronger than the surrounding rock that you know that helps with normally when you drill you have to do some sort of casing to preserve well integrity make sure there's no leaks and so on. So this liner is like automatically formed and you can just go and go and go

deeper and deeper. Is this kind of like, and this is just because I finished Andorra a couple days ago, it's kind of like a tiny death star, but used for good, right? It's like it uses you know, right? Like the death star it's directed energy, yeah. It's just directed energy. It destroys

a town, destroys a planet. In this case, we're not trying to destroy a town, thankfully. We're trying to destroy a very concentrated bit of granite that is deep in the ground, but it is really, really hard, and it's otherwise very difficult to drill through, given the temperatures and the pressure of being that far underground,

you shoot it with this sort of super fancy special laser. It totally obliterates it and gets us clean access to actual geothermal power. That's right. So technically it's not a laser, but it's an energy, it's a concentrated like energy ray, right, that you create using this wave guide.

And yes, it vaporized. It basically makes it much cheaper to, you know, when it comes to fruition, right? It's going to be much cheaper to drill very, very deep. Right? I mean, Quays is talking about we could drill like up to 20 kilometers of depth with this kind of thing, which is deep enough to get to the temperatures you need to produce geothermal

literally anywhere on the planet. So let's get excited about this, and then let's come back down to Earth on this. In the excitement category, it's like, okay, we're used to energy being geographically specific. Like, windy places are good for wind power, and sunny places are good for solar power. And there's parts of the world that are kind of hard to see

just from walking around, like Texas and Saudi Arabia, that underground, it turns out they're incredible for their oil resources, and so they're energy rich. But all of the planet is over the core the planet. By definition, that's how a sphere works. And so if we had some technology for drilling really, really deeply into the planet, it could turn any patch of land into a piece, a territory that is as valuable for geothermal as like the Texas or Saudi Arabia lands are for oil. Like that's, that's incredible to think about. Like, you wave the magic wand over the world, and it's all Saudi

Arabia for oil, except the oil is an oil and it has no carbon emissions. Like, that's- Anybody can be Iceland, right? Anyone can be Iceland. And so, and Iceland is like the world leader in energy production per capita, and they have, you know, they have aluminum production on the island, like way out of proportion to their population size. They're like, I think, the top per capita producer of aluminum. I mean, it's just because that's an energy, electricity-intensive industry,

and they have such cheap energy availability. So, yes, anybody can be Iceland. So anyway, so we're making the entire planet Iceland. everyone's Iceland. There's abundant energy. There's abundant electricity. It opens up all these incredible venues for new things we can do that take a lot of energy, whether it's the desalalization of water or just running a perfectly electric economy. All right, that's the vision. That's all very cool. Back to reality. What are the bottlenecks, right? This technology isn't everywhere. Like, technically, it's almost nowhere right now. It's very nascent. So what are the clear bottlenecks to making

something like this cheap and available and scaled? So with Quays specifically, they're still developing this tool that will allow them to drill very deep. So they're doing lab tests, they're doing field tests, but it's still under development. With the industry more generally, I think that the biggest challenge is that for near-term deployment, the best resources overlap significantly with federal land. So it's just most of the in the US, most of the, the, the, sort of the shallowest geothermal resources happen to be in the western half of the United States, of which the federal government owns a huge chunk of. And so if you want to sort of get started, and I believe that this is an industry that will be characterized by, very much by learning by doing. Right. You're going to have to, you're going to, you're going to, the more we deploy geothermal energy, the more the cost is going to come down. And so you've got to start somewhere. And that somewhere, ideally, you're going to have to, you're going to, you're going to, you're going to, you're going to be going to be going to. And so you're going to start somewhere. And that somewhere, you're going to. And that somewhere, would be, would happen to be on federal land. But it's just such a challenge to get, you know, these wells permitted on federal land,

which is kind of crazy because it's the same equipment, you know, for the mechanical drilling. It's the same equipment as you're using in oil and gas, right? So it's in same workforce, same techniques, et cetera. And you can get an oil and gas well approved in about two weeks on federal land. And it takes like two years to do geothermal. So there are scientific bottlenecks here. We need to figure out how to get this super fancy laser that isn't actually a laser to work. And there's also policy bottlenecks. We need better laws in this country that allow us to innovate in places where geothermal is, where the, the,

the fruit is lowest hanging when it comes to figuring out exactly how to get this technology off the ground. And that requires regulatory changes. Exactly. Yeah. I, I, I, And I do, I am optimistic that, like, the administration hears us on this and that, you know, they want to do something about it. We'll see. We've saved the best for last, at least according to me. I am really, really excited about chat GPT. I have loved playing around with this toy. The economist Larry Summers went about as far as one can possibly go when it comes to the potential of this technology when he said the chat GPT is a breakthrough on par with electricity. I am prepared to defend why I am. I think this technology is so cool and with continued exponential growth could be so revolutionary. Tell me one thing that impresses you

about chat GPT and what leaves you cold about this technology. Yeah, so I was using it last night to just collaboratively write bedtime stories with my kids. So I was like, sit down with my kids, be like, okay, let's prompt chat GPT. What do you want a story about? you know,

you know, one of them wants to be a princess, one of them wants to be a knight. They really like Minecraft. We can say, okay, they're in Minecraft, in the Minecraft world. And we can just, like, get a story written for us on the spot, right? It's like, it's like sort of like unlimited content production, right? It's just, you know, on demand.

So I think it is really exciting. Technically, it's a huge breakthrough. By the way, chat GPT is not yet. which is on the verge of release and just another step forward. So it's just going to get even better, you know, in the coming months, I think. Yeah, the thing that it doesn't leave me cold, but the place where I think a lot of people are overstating the importance is that some of the content can be a little bland, right? it is taking sort of the entire English language corpus that it's using for training, and it's sort of like averaging over it, right?

Unless you're sort of like a prompting wizard, right? It's hard to get it to say anything interesting. And so it is not a replacement for, you know, the writers that we read online at the Atlantic, such as Derek Thompson, who say something, you know, interesting and unexpected. in every article, right? Whereas, you know, like, I think, I think it, so chat, CheapT, as far as I can tell, like, can't do that. Like, I, you know, I try to prompt it for like, you know, give me a shocking twist at the end of the story, but also make sure that there's foreshadowed kind of earlier in a non-obvious way. And it just doesn't have a concept of, of a lot of that. So, so, yeah, I think it will be,

I think it will do amazing things. And I think, I think on the, on the, on, the imaging side as well. It's like incredible, incredible capabilities being developed. And by the way, I mean, the thing that I think is going to shock people in the next, in the coming, like, you know, weeks or months on the imaging side is people are going to learn about model distillation. Right. You can distill these imaging models into, you start with a big model and then use that to train a smaller model that can generate an image in like under a second on your laptop. without needing to use a server. Step back. Yeah, tell me the full story of that. Just, like, create a full example

of what you're talking about. Yeah, so right now, you can download, like, the Stable Diffusion model on your laptop and use it to generate an image. Stable Diffusion, for people listening, right, is one of these texts to image generators. So you enter a text like Derek talking to Eli

on an exoplanet using cups and strings in the style of Dali, and it will, like, weirdly enough, do this in like a matter of seconds. It'll be like pretty good. It'll be, you know, so for stable diffusion,

at least on my laptop, it's like 30 seconds or more to generate one image, right? And then, okay, then I have to fix the prompt, right? And I, and I, so I adjust the prompt based on the results.

And then maybe I want to adjust it again. So it is like, feels like very laggy and back and forth that you have to do this. So with a distance, Dillb model, you can get on the same hardware, you can get a result in like under a second. So I can enter a prompt, press enter, immediately see the image that I want or that I thought I wanted, adjust the prompt, hit enter, another second goes by, like, I see the image again.

And so just for like going back and forth with this model, and then maybe at the end, once I find the prompt I want, I go back to the full model and do the bigger, the bigger model for the final render or whatever. But I think this is going to be a tool that right now, for like for chat GPT, for instance, you're doing this on open AI's servers. Right. And I think that model distillation is going to allow us to do a lot of these generative stuff on local hardware on our, on our just like consumer grade laptops. So I think it's going to be really exciting. Larry Semmer has called it like a caddy for creative work. which I thought was actually a pretty good metaphor.

Like, the caddy is not considered the talent, right? But still, it can be essential, not only to have someone carry the clubs, but to advise on which club to use, to think about exactly how do I hit this? What do we think is the pitch? I actually don't even play golf. I don't know why I'm elaborating on this metaphor,

but I assume that's what people use caddies to do. I've seen enough movies of golf. I see, that's already how I use chat GPT. You know, Noah Smith had the metaphor of sandwiching. You have an idea for a prompt. I prompt chat GPT. It sends me back an answer. I edit the answer.

That's actually what I put in my article. And so much of writing are these little micro questions that occur to me as I'm writing a longer piece. Like if I'm writing something about, you know, generative pre-trained transformers, I say, wait, what exactly is that? And I ask GPT, what is this technology? give me a metaphor to explain GPT to a ninth grader, it will do that.

Now, it might not be A plus, it might be C plus, but then I get the prompt and I can edit it back into something that I consider appropriate. You said there was another breakthrough in AI that makes you even more excited about this AI summer that we're in. And I think it's important to be clear

that this year was all about generative AI, but last year, two years ago, it was about, was it Alpha Fold? Yeah, Alpha Fold, the AI at Google. Protein folding. Protein folding, right, the ability to anticipate the precise structure of any protein in the world and the incredible frontiers that that opened up in the future of proteomics. So it's every year AI is showing like a little different part of its body to say like, you know, this is what I'm capable of. Tell me why you're so interested in this other frontier inside of the AI family called precise atom manipulation. What

the hell is that? Yeah, sure. So I think, to give a little background, I think about AI and sort of a two by two matrix, right, or two dimensions. And so one of them is, is it superhuman performance or is it subhuman performance, right? So, so, so like protein folding, like it's definitely superhuman performance. We can't do that at all, right? Whereas like GPT chat or chat GPT, like, it's subhuman performance in the sense. It's like, it's not as good as Derek Thompson at writing. But and then and then also like the dimension the other dimension is like economically useful or not, right? And so so like we so we have chess AIs that are superhuman performance but not economically useful

Not not in a significant way whereas you know something like writing or art potentially could be useful even if it's subhuman performance because like you said it's like a catty So I'm really interested in in sort of like the the economically useful and superhuman performance quadrant of that, and I think protein folding is one of them. And I think maybe this sort of atom manipulation is another one.

So one of the technologies that could be the most revolutionary for humanity is productive nanotechnology, the ability to actually start designing things by placing seeing atoms exactly where we want them to be, right? In molecules and creating, designing things from the ground up at the atomic scale,

we could basically create, you know, the theorists behind this say like, stuff with almost magical properties. Give me an example. Like, you could have a room filled with nanobots that when you kind of make a motion to sit down, a couch forms under you. Right? So, like, I mean, like, that is just, it's just wild, right? You could have, um, I did a calculation that some of the motors that people have designed,

um, that you could take like the Tesla model S plaid motor and you could do that amount of power output in the size of 12 grains of sand. Right? Like, this is what you can do. I mean, it's, it's like hearing about these possibilities, it's almost like hearing, about like the size of the universe or hearing about like string theory. It's just like it's so incomprehensible. It's like I guess. Exactly. Wow. Yeah. Yeah. So so so this is like you know I think it is like kind of magical.

Like some of the theorists are hand wavy at times. Right. And I and I would always say like, you know, like okay like take it take it with some grain of salt. But it does seem to follow from like totally standard chemistry and physics that this is possible. And so what this team did with AI is not quite that, but they're working on sort of being able to manipulate individual atoms. And if you think about like moving an atom like with like tiny tweezers or like a little stylus, right, that you're like poking it, right? There's going to be all kinds of quantum effects if you're on the tip because you're

you're operating at such a small scale that it's very hard to predict all the forces and the movements that are going to happen. And so what they are doing in this is they developed an AI that, like, shows them how to move the tip and how to poke atoms around and move them around.

So this is not yet creating molecules with atoms. So these are, to anybody who knows, like, they're not covalent bonds. So you're not making molecules. You're moving individual atoms around on top of a crystal, which is something that we have done before, but just it was very hard.

So you have, there's a famous historical example of a team at IBM that had some, I believe it was xenon atoms, and they spelled out the word IBM with just like xenon atoms on a crystal surface. Right?

And so that's more like what, what they're doing in this example, but hey, you got to start somewhere. And I think, you know, being able to actually design stuff and

engineer stuff at the atomic level with that level of precision. That could be the biggest game changer of all for humanity. What sort of thing about that is it sounds like AI and machine learning is being used in this case as a tool that

unlocks the key to an entire new kingdom that is nanotechnology. We do not have in our own mammalian corporeal bodies the ability to enter this world. This world is only accessible by developing machine learning technologies that allow us to do extremely precise, quasi-magical things with atoms. But once we unlock that

door with AI, what's beyond that door is unimaginably awesome. And it's not like disappearing into the metaverse. It's new things that we could build in the physical world that are totally mind-blowing. As you were talking, I will say, at this point, chat GBT seems like pathetic. It's like this compared to this, it's like some 1600s technology. But that said, this is one of the reasons why I find chat GBT is so thrilling for my work. I just asked chat GBT. I just typed in precise atom manipulation. And it gave me a little definition. And then I entered the abstract of the paper that you sent me about this. And it did a pretty good job summarizing the abstract. And then I said, what are some of the coolest and most interesting

implications of atomic scale manipulation for the future of technology? And it says precise atom manipulation could enable the creation of ultra-efficient energy storage materials, more powerful computer processors, and highly sensitive medical diagnostic tools. So I said, what kind of highly sensitive medical diagnostic tools made with this technology, atomic scale manufacturing do for people. And it says, detect very low levels of various biomarkers in a person's blood or bodily fluids, allow for early detection of diseases such as cancer, et cetera, et cetera, right? So now I'm thinking, oh, right, another aspect of this precise atom manipulation you're talking about might be not just to create new products in the physical world around us, but to create new

products within us that teach us about what's going on in our bodies. So I would like to make a plug both for your technology and for my love affair for chat GPT, this is a little bit, Ashter Tellers calls it, a dumb genie, right? It's not that creative, it's not that interesting. But there's a lot of questions that we dumb people have that also aren't that interesting. And it's really nice to have this sort of bespoke Wikipedia genie at our fingertips that can just explain these kind of questions to us. So I find your example magical.

and I also found this lesser capability of chat GPT magical in this case. And it's still getting better, right? That's the thing to remember is that it's just going to keep improving. So, yeah, I do agree that it's like a significant breakthrough. Eli, Dorado, thank you very, very much. I think we'll just have you on every single year to walk us through the most interesting things happening in science and tech, because this is always one of my favorite pods to do. Thank you very much, man.

Happy holidays, and I'll see you soon. Yeah, you too. Thank you for listening. Plain English is produced by Devin Manzi. If you like the show, please go to Apple Podcasts or Spotify, give us a five-star rating, leave a review, and don't forget to check out our TikTok at Plain English underscore. That's at Plain English underscore on TikTok.