Faster, Please! — The Podcast

James Pethokoukis
  • 4.7 (11)
  • Technology
  • Updated Weekly

Welcome to Faster, Please! — The Podcast. Several times a month, host Jim Pethokoukis will feature a lively conversation with a fascinating and provocative guest about how to make the world a better place by accelerating scientific discovery, technological innovation, and economic growth. fasterplease.substack.com

  1. 5d ago

    An update on AI’s economic impact: My interview with Scott Strand of Google’s AI & Economy program

    My guest this episode is Scott Strand. Scott is Head of Strategy, Operations, and Special Projects at Google, where he founded the Google AI Economy program as well as Google ATLAS. Recently, Scott co-authored two papers, “Mapping Gemini’s Usage in the Economy” and “AI in Science: Early Insights.” Today’s conversation will discuss these two papers, diving into the role AI could play in benefiting society through everyday life, scientific progress, and long-term economic growth. In this episode: * Is AI a general purpose technology? (0:40) * Gemini’s usage in the economy (4:20) * What will it add up to? (9:44) * AI and entry level jobs (15:34) * AI beyond the workplace (19:13) * AI and the future of science (22:15) Faster Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On the visible impact of AI… I think you could dig the deepest hole you can think of, and it would be hard to find the impact unless you were really, really pushing for it. Look, there are the basic stats that everyone can see right now. Unemployment rates are at 4.1 percent or something like that, on trend with more or less where they’ve been. In the data that we’ve looked at, it’s not consistent with the story of AI creating either widespread—certainly not widespread—unemployment or even unemployment in specific pockets. On AI’s usage… One is that, with past technological innovations, routine tasks are the things that get automated first—the things that are repeatable, where you do them over and over in the same way. That is not what we saw in our data. We saw that most AI usage focuses on non-routine tasks. The types of things like creative design, hypothesis testing, doing something that’s a little bit out of the ordinary from your job description. Those make up about a third of the tasks in the average American worker’s job basket. It represents about 65 percent of their AI usage. So they’re really over-indexing on using AI for this type of work. And that poses an interesting challenge to the routine task intensity model, where you expect every wave of technological innovation to automate the repetitive stuff. But that’s not quite what we see happening. The other thing that really surprised us was the amount of blue-collar and manual occupational usage in the data. We came in honestly just expecting to see not very much. That’s certainly what our peer laboratories found. But we saw a pretty significant amount. We see auto technicians using our models to diagnose engine wear and tear, electricians using it to sketch out wiring diagrams and inspect what might be going on. On micro vs. macro impact… So, in a micro sense, the productivity benefits are very real and observable. As to when they start to show up in the macro, I don’t know. I think it’s gonna require a lot of things. It’s going to require teaching people to use these tools to their maximum potential. It’s gonna require reorganizing businesses around it. When they first introduced electricity, they needed to retool entire factory floors in order to make electricity available throughout the factory, and only then were they really able to make full use of it. So I think we’re probably gonna see something similar with AI. On AI’s effect on entry-level jobs… We found in our data that a lot of the usage was people in high-expertise roles using it for lower-expertise tasks, the types of tasks that entry-level workers often take on. And obviously this is concerning. We can’t confirm or evaluate whether or not it’s dampening entry-level hiring, but I think this is something that we need to look at really closely going forward. One thing that I find to be a useful frame for thinking about this is David Autor’s expertise framework, where, if you think about the expertise requirements for a given job, they sit on a distribution curve across the number of tasks. Some technologies automate away the low-expertise requirements related to that role, which raises the average expertise level required for that job. This is kind of what happened with accountants when spreadsheets were released. You didn’t really need to have people doing tables of numbers anymore; the computer took care of that. But that freed up a lot of time for accountants to specialize in tax strategy and things of that nature. On AI’s impact outside the office… It’s hugely significant. Eighty-six percent of AI interactions are happening outside of work. And we see people using it for really valuable things, things like seeking professional services, navigating legal questions, discussing how to engage with government and civic services. That actually overindexes by 20 times relative to the amount of time people spend there. And about half of that interaction with AI happens on nights and weekends when government offices are closed. So it raises a really interesting idea that AI may be helping to extend civil society in some way and help people get more out of their governments, whether that’s benefits or just clearing up questions on fines, et cetera. I mean, I’m a parent, I’m a really busy parent, and so I just think of tired parents sitting at the kitchen table at 10 at night, trying to figure out how to fix a broken dishwasher or translate some zoning notice from the city into something that they can do and act on. AI is really providing real value there with a real dollar figure attached to it. But it doesn’t get measured. On AI in science… We found that scientists were getting a lot of productivity gains out of this. They’re saving about seven hours per week, which they’re mostly just reinvesting back in more research, which is huge. So it’s not all good news. What’s happening is that scientists are able to generate a lot more hypotheses, which is great, but now there’s a backlog of hypotheses to test, and the bottlenecks on research are starting to shift downstream to things like physical experimentation and clinical validation. So, yeah, lots of exciting stuff, but still lots of work to do. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  2. Sep 24

    📈 How economic growth can defeat authoritarianism: My interview with Dalibor Rohac, author of ‘Unshackled’

    On this episode of Faster Please!—The Podcast, I am joined by Dalibor Rohac. Dalibor is the director of global research at GLOBSEC and a longtime senior research fellow in international relations at the University of Buckingham. Recently, he wrote the book Unshackled, which focuses on how economic power is inseparable from geopolitical strength. In our conversation, Dalibor and I discuss his new book and what growing strains within the Western alliance could mean for its economic and geopolitical future. We also talk about Europe’s defense posture and its struggle to remain competitive in the global technology race, as well as why trade within the Western alliance is critical to maintaining long-term Western prosperity. In this episode: * What defines the West (0:43) * The changing West (6:04) * The disappearing secret ingredient (12:54) * A change in nationalism? (18:25) * European regulation (22:56) * Europe’s economic future (26:10) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But for now here are some of the many highlights from the chat: On defining the West… For me, the West is not defined geographically, it’s not defined in ethnic terms, it’s not defined in cultural terms. It’s defined through adherence to a certain set of institutions that people like Acemoglu and Robinson would call inclusive economic and political institutions, and different scholars would have different names for them. But I think we see as meaningful the distinction between autocracy and liberal democracy, between free markets and state capitalism or a planned economy. And I think countries that do have those sorts of institutions that have enabled the rise of the West—places like the UK and the United States—and the opening up of our political systems, they can be in Asia. There’s Japan, there’s South Korea, there’s Australia, and I think they are very much part of the West as much as we are here in Europe or in the United States. On the potential of a changing West… I think we can deal with troubled democracy in Hungary or democratic backsliding in Turkey. Turkey would be one of those cases where there has been a significant shift away from the Western alliance and away from democracy. But if we see a similar shift sustain itself in the United States, I think the world will be in a lot more trouble, even relative to the status quo. On the West’s trajectory… I see all these controls that you’re looking at blinking in the wrong direction. And I think there is some urgency with which we have to create intellectual, political coalitions to defend some of these things. We might need to learn things, relearn things the hard way, but I very much hope that it won’t be necessary and that people will understand what is at stake. I think the most immediate pressure point is the federal budget. If you are spending more on financing your debt than on the Department of Defense, you’re placing yourself in a very poor position to fight a major conflict. On Europe’s diverging defense mindset… A place like Poland, which has been spending consistently between 3.5 and 5 percent of GDP on defense, which has a dynamically growing economy that has now joined the G20 group of most advanced industrial nations of the world, which surpassed Japan in per capita GDP last year. Unfortunately, the further west you go, I think the more complacency you see. I was recently at a conference in Austria, beautiful place, lots of young German-speaking people, both from Austria and Germany, and I had the sense that people wanted to be left in their illusions. Much of the rhetoric reminded me of the stuff you would hear at conferences 10 years ago about multilateralism and just getting along and solving the climate issue and preserving the advances of the welfare state. There just wasn’t the same sort of urgency that you hear when you go further east. On Europe’s position in the global technology race… That sense that we have to facilitate the diffusion of new technologies if we don’t want to be left at the periphery of the global economy is getting stronger. I think people understand that Europe is not going to have its own frontier AI model and will instead remain reliant on American technology. The transatlantic relationship is not in a good place, but there is no real constituency in Europe for aligning with China when it comes to technology and tech governance. The lack of separation between Chinese corporations and the Chinese state makes people uneasy, irrespective of their politics. On the West’s retreat from trade… The American turn away from trade and efforts at trade liberalization has coincided with an inward turn in Europe. The EU has found it increasingly difficult to get trade deals done, whether with Canada or, more recently, Mercosur. When it comes to trade, though, I think we may be starting to see a reversal in Europe. And when it comes to domestic reforms, the dire international situation could serve as a catalyst for change at the European level. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  3. Sep 17

    ✨ Why verification is AI's real bottleneck: My interview with economist Christian Catalini

    On this episode of Faster Please!—The Podcast, I am joined by Christian Catalini. Christian is a research scientist and the founder of the MIT Cryptoeconomics Lab. Recently, Christian co-authored “Some Simple Economics of AGI” In our conversation, we focus on the AI bottleneck of verification, rising safety concerns, and how to address and solve these problems while maintaining growth and the US advantage over China. In this episode: * Red light or green light? (0:37) * AI risk and safety (8:07) * The bottleneck: verification (15:28) * Markets and AI safety (22:48) * AI labs and regulations (26:17) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some of the many highlights from the chat: ✨ On slowing AI industry growth… Definitely not a red light for the entire space. I think that would be a very bad idea. That said, concerns have been raised by the labs themselves. So I think the next natural step is to send some real evaluators in and see what’s actually going on. We’ve seen a report from METR. I think they’re a talented team, but they have a very particular bias and a very particular type of expertise in this. I would love to see traditional security engineers and cyber experts looking at what happened inside OpenAI, what is happening inside Anthropic. Is there something we should be concerned about? Or are these companies just racing and potentially being a little bit reckless with their deployments? ✨ On catastrophic AI risk… Could someone, on the bio side, use the information from an LLM to create something more dangerous than attempts that have been happening over the last few decades, where people were just ill-informed? They got 80 percent of the way. Could they get to 100 percent of the way and hurt a substantial number of people? Yes. Would it be a pandemic? I think that’s the big stretch. Once you do those massive jumps, I think that’s where we’re in the land of science fiction. And honestly, it’s harmful because we keep anthropomorphizing these agents when there are very benign explanations for what they’re doing. In fact, it’s the training that the labs are doing with reinforcement learning that’s leading exactly to the outcomes you’re seeing. ✨ On the verification bottleneck… The act of verification is the actual bottleneck. Because with AI, you can just throw compute at anything that’s been measured and therefore can be automated. But if you can’t trust the output, if there are important unmeasured dimensions of that problem that the AI doesn’t have access to, well, then you’re in trouble. I think companies today, including the labs—and maybe this is why we’re seeing the security incidents—have this temptation to keep advancing and rapidly progressing, potentially not doing all the proper verification. ✨ On regulating AI… I don’t think we need to come up with draconian, very tight regulatory bodies for mature markets, right? Airlines, financial services—how long did it take us to fine-tune that regulation so that we got it right? Decades. And in fact, it’s still a work in progress. I think here we need to be thoughtful. I think we can start with better measurement. Let’s surface the evidence. Let’s have neutral evaluators and inspectors. Again, we have METR, but we need probably 10 different organizations with very different philosophies, different skill sets, that can go in and provide us a neutral third-party assessment. By the way, neutrality also means funding. If the funding for these institutions comes from the labs, well, I don’t know what to make of it, right? Maybe academia has a role to play. I’m not sure, but we really urgently need better measurement. ✨On the labs’ role in AI safety… The antitrust concerns don’t really apply in the format of safety. Of course, if you’re timing model releases and sort of handicapping the industry in different ways, that could be an antitrust concern. But I think many have said this very eloquently over the last few days. Yes, the labs are in full control. If they don’t believe their products are safe to ship, they don’t even need to coordinate, right? In a sense, each one of them can look at their own evidence and make their own risk-based decisions. ✨ On who can benefit from AI growth… The obvious one, of course, is NVIDIA, right? They control the hardware, and so they benefit from more intelligence being used across the economy. But take Meta. I mean, Meta is developing AI that they can put to work into every other line of business. Same with Google. Google doesn’t need to be a frontier lab, right? They can take great AI and apply it to their products and be a lot more effective. Financial services—you have the likes of Stripe and Ramp. What they’re doing is taking the models and making financial services better. So that’s a much more positive view of the future, one where we’re not completely disempowered by this massive supercorporation, but also one where human dignity and the contribution of humans to labor, I think, will be strongly preserved. Faster Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  4. Sep 9

    ✨ My interview with economist Tyler Cowen on the Age of AI (and more)

    On this episode of Faster Please!—The Podcast, I am joined (again) by Tyler Cowen. Tyler is an economics professor at George Mason University and co-founder of the economics blog Marginal Revolution. He is an opinion writer for The Free Press and the author of several books, including The Great Stagnation, Average Is Over, and Stubborn Attachments. During our conversation, Tyler and I discuss AI risk, the extent to which public pushback could slow AI progress and economic growth, different forecasts for AI development and where Tyler stands, and what the technology could mean long term for the American economy. In This Episode: * The Effect of AI Industry Pushback (0:41) * Different AI perspectives (7:37) * The Fear of AI (12:37) * Economic Growth: (17:32) * The Future of Jobs (23:06) * AI on a Global Stage (26:50) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some of the many highlights from the chat: ✨ On potential catastrophic harms from AI… They love to talk in extreme parables of Skynet going live or a bioterror attack where all humans die. But, you know, in the short run, the intermediate term, what share prices should we expect to go down? What variables should we expect to change? Give me a number for what cybersecurity costs will be next year and by what percentage that will go up. There was another estimate I saw. It said cybersecurity insurance costs will double over a five-year time period. This was from experts in the sector. Again, I’m not endorsing that number, but it’s a number, and it puts it in perspective. It’s terrible if those costs double. But again, it’s not an insane scenario that we can’t live with. ✨ On whether AI fears lead to heavy regulation or a pause… The discourse will be ugly and stupid no matter what your point of view, even if you favor a lot more regulation. But it’s very hard to stop fundamental new technologies. There’s also Chinese open source. There’s a national security imperative here. I just think it’s going to happen. It will pain me every day to see the debates and some of the laws that probably end up getting passed, but I just don’t see how it gets stopped. You know, for better or worse—I would say for better. But there’s not a coherent path for telling a story of how this ends. ✨ On how much AI company executives are to blame for the public AI backlash… I don’t know if the word “blame” is the right word here. I think a lot of the PR has not shown enough equanimity, and the people who are motivated to work on this are precisely the same people who think it will have very extreme effects. And those companies have gotten a lot done at a truly incredible pace, even by American or tech-world standards. So the notion that they have semi-religious views of what this all means is a very San Francisco kind of thing. Like, do I blame people in the 1960s who thought that LSD was creating a new world, a new way of living, a new way of life? Well, sort of—but that’s what we are. You know, we’re a little nutty in the head as a country, and this is California, and then it’s San Francisco. So we also need to embrace that nuttiness at the same time. I think that’s the bigger picture I try to keep in mind when maintaining my own equanimity. ✨ On roadblocks to economic growth from AI… The thing (AI) being smarter is not the problem. The things are already very smart. The real issue is, if you're in a mid-size to large organization, reorganizing your systems—HR, finance, whatever, all the things they do at AEI—not just for people on an individual basis to use, say, ChatGPT to augment their labor, but actually building the whole system around AI in a way that's reliable and coherent and everyone there knows how to work with. That's very, very, very hard and slow. And if I saw more progress on that, then I would really think the rates of productivity growth will be much higher soon. ✨ On AI and job displacement… In any foreseeable future, we can achieve full employment if we don’t screw up other policies. Just think of the number of jobs that will be available testing the new ideas that AIs come up with, most of all in the biomedical field. Think of all the new jobs that will be available gathering and processing data for the AIs. It wouldn’t shock me if, in some distant future, that was like a third of the whole labor force—the way today, you know, services are some very high percent of the labor force, something that people in the Industrial Revolution never would have imagined. ✨ On how China thinks about AI and the national security implication… I don't think we understand it. I'm not sure they understand themselves. But it seems to me, as a non-Christian society, they don't have that much of a Book of Revelation scenario, so they don't really have doomers. They do think it's an important technology. I strongly suspect they're afraid it could displace the CCP, and they're much more worried about it in a way that we are not. Those are my hypotheses. I stress the word “hypotheses,” but that would be my best guess. Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. On sale everywhere by James Pethokoukis: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  5. Aug 26

    🚀 The New Space Age meets the Age of AI: My interview with Phil Metzger

    Thanks in large part to the massive drop in the cost of getting a pound or kilogram of stuff into orbit and beyond, many of the boldest Space Age dreams are now possible. The business of space makes economic sense like never before. And here comes the AI Revolution to really give the sector a boost. Today, on Faster Please!—The Podcast, I am joined by Phil Metzger. Phil is a professor of planetary science at the University of Central Florida and director of its Stephen W. Hawking Center for Microgravity Research and Education. Before joining UCF, Phil spent nearly 30 years at NASA, where he worked as a senior research physicist. (I also highly recommend his X account.) In this episode, we talk about why AI has made the economics of space work by providing a “killer app,” what the first off-world industries might look like, what obstacles we still have to overcome to make them viable, and what the long-term future holds. In This Episode: * The economics of space (0:49) * Industries launching in space (7:36) * Cutting space expenses (11:31) * How do we start? (16:55) * Dealing with lunar dust (22:31) * What does the future hold? (29:31) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On orbital and lunar manufacturing… We have a lot of work to do. But it isn’t gonna require any new physics. It’s just gonna be industrial engineering, aerospace engineering, civil engineering on the moon, and a straightforward effort to do it. And so we’ve got to spend the effort building these technologies. But there are already companies getting ready to build commercial space stations in low Earth orbit. There are companies getting ready to start launching data centers in space. I believe that once that begins to expand and grow, the economics of space in every sector of the space industry will be pulled upward by the huge economic value of AI. On how the case for AI is the case for space… We were hoping that Mars settlement would drag up the entire in-space industry. I ran models on Mars settlement, and I believe it’s very doable. But the new thing now is AI. AI swept in like a storm two, three years ago. Suddenly everybody woke up and realized, “No, this is the killer app for space.” Elon immediately started talking about “Mars is gonna have to wait a couple years because we’re gonna do the moon right away.” And it’s all because of AI. So AI has changed our whole assessment of the business case for space. On the economics of orbital data centers… The amount of throughput of spacecraft hardware will be so gigantic that there will be this huge motive to shorten the supply chains and move more industry closer to the launch pads. And then the workforce we’re gonna need is gonna grow gigantically. Maybe we’ll do AI and robotics, but there will be an opportunity for huge growth in the labor force. So I think governments, universities, everybody in industry and in finance needs to get ready for this tidal wave that’s about to sweep through. … So in Elon’s mind, the issue is the demand for AI will keep growing, and it’ll grow so fast that you can’t build the data centers fast enough and you can’t launch them off the earth fast enough. It’ll be a logistics problem and a supply chain problem. [Musk] hasn’t said this, but I will add, it will be an atmospheric protection issue. If you start launching too fast, then it does cause some cumulative damage to the atmosphere. The atmosphere will heal pretty quickly, so it’s not long-term damage from rocket launch. But I believe there will be political pushback when people see gigantic rockets launching every hour, hour after hour, 365 days a year, from 50 launch sites around the world. So Elon’s idea was we’re gonna have to build these AI systems on the moon using lunar resources, and we don’t need to launch them off the moon with rockets because the moon doesn’t have an atmosphere. We can just shoot them off the moon with a railgun. They call it a mass driver in that context. On lowering launch costs… We’re expecting launch costs to go from—right now they’re like $1,500 or $2,000 per kilogram to low Earth orbit—we’re expecting it to go down to like $35 per kilogram in 30 years, and that’s a conservative estimate. On the future of humanity in space… Most people don’t know this, but there are at least 150 planet-sized objects in our solar system. Most of them are dwarf planets far away. But the moons are amazing worlds, and pretty soon we’re going to have buildings being constructed. We’ll have architects designing buildings for the environment of Titan. I can’t imagine what beautiful architecture will be developed. Once we’ve got an abundance of robotics driven by AI, then we’re not gonna be doing things on the cheap. We won’t have to. And so we’ll be able to make beautiful cities on all these worlds. We’ll be bringing beautification to all these planetary bodies throughout the solar system. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  6. Aug 18

    🏁 The Great AI Race as a clash over compute: my interview with analyst Ryan Fedasiuk

    My fellow pro-growth/progress/abundance Up Wingers in America and around the world: The AI race between America and China isn’t just about whose AI models are at the frontier or get adopted most widely. Today on Faster, Please! — The Podcast, I am joined by Ryan Fedasiuk, a fellow at AEI and the author of the Substack Choosing Victory, where he focuses on US-China relations, technology, and national power. He’s also an adjunct assistant professor at Georgetown University. Recently, Fedasiuk has written about the US-China AI race, and while much of the debate has focused on the models themselves, Fedasiuk is focused on the role of compute in shaping the global balance of power, which is also the subject of a new report, Voltcraft: Industrial Competition in the Age of AI. We discuss the speed at which AI capabilities are improving, the dimensions of the US-China AI race, and why Fedasiuk thinks compute will be central to that competition. We also discuss a global US strategy and, as AI abilities increase, what role the American government could play in ensuring safety. In This Episode: * How Fast Is AI Moving? (0:54) * The US-China AI Race (7:08) * The Future of the AI Industry (12:42) * The Compute Race (17:04) * Expanding US AI Infrastructure Abroad (22:05) * Geopolitics and National Security (25:10) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On the pace of AI progress… At least according to definitions circa the late 2010s, we’re living through what I would describe as a fast takeoff. We have, as far as I am concerned, artificial general intelligence capable of meeting the performance of human beings or exceeding it at most tasks. And I think that things are only likely to improve from here. On the US-China AI race… We are obviously living through this uncertainty. When Mythos was unveiled on April 6, I think it sent a real tremor through the Chinese national security apparatus and kind of a moment of, “What is this? What do the Americans have? What is this system capable of achieving? When can we produce our own?” On why compute is critical… The fact is that to make the most out of frontier AI and to run it at scale, you still need tons of devices that turn electricity into tokens. You still need tons of compute. And really, I think the name of the game is going to be who can build and install computational power around the world. On why America needs to export its compute… If compute is the substrate of the global intelligence economy, we want to make sure that it’s US-designed compute that other countries are choosing to buy and install rather than compute manufactured in China. On who should get access to American compute… If we can expect the developer ecosystem in Singapore is going to take off like wildfire and start building and using a lot of AI applications, maybe we want to make sure that Singaporeans are building on American compute ASAP before China’s compute becomes a viable alternative that could serve that market. Maybe we want to make sure that that market is served even before certain constituencies in Des Moines. On government intervention in frontier AI labs… I think that we are already seeing some shadow of this, even if it isn’t declared. I think we will likely see a continued molding and merging of private sector capability with the resources and infrastructure of the national security enterprise. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  7. Aug 6

    💧⚡🖥️ A deep-dive on data centers: My interview with AI researcher Andy Masley

    My fellow pro-growth/progress/abundance Up Wingers in America and around the world: With the massive buildout of data centers has come an equally massive backlash. They’ve been blamed for higher electricity bills, taking up too much water, and pushing out farmland. All this has led to a public outcry and efforts against their construction. But how much of the criticism is warranted? Has one of America’s fastest-growing industries become a political scapegoat? Today on Faster, Please!—The Podcast, I am joined by Andy Masley, an independent writer supported by Coefficient Giving who deep dives into AI research. Recently, he has focused on data centers at his great newsletter and separating facts from myths surrounding them. We discuss what the evidence actually says about data centers’ impact on water, land, and electricity prices—and where Andy thinks people get the facts wrong. We also discuss AI art, Waymo, and America’s willingness to embrace technological change. In This Episode: * AI Art as Curation (0:37) * Waymo and Technological Disruption (4:43) * The Case for Data Centers (9:14) * Water and Land (15:41) * Data Centers and Electricity (21:41) * The Data Center Backlash (28:50) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On AI Art… As you see someone using Midjourney to create images that you are actually much more interested in, and find more subtle or pleasant than the kinds of AI-generated images most people are typically exposed to on their timelines, it can really open people up and make them realize that these tools are much more powerful than they might expect. On Waymo Entering Cities… While there are many industries that I might worry about completely disrupting, the number of deaths caused by driving, and the difficulty people face getting around very dense cities, are such important problems that I am willing to hand the robots this one before we march forward elsewhere. On this issue, I am entirely gung ho: “Let the Waymos have it.” On misconceptions about data centers… If you somehow hid the words “data center” but included all the other information and asked, “Would you accept these specific trade-offs in your community, such as using a certain amount of water and land, in exchange for this amount of tax revenue?” I think that, in most places, with a few exceptions, people would say yes. On the “lack” of land… This has really blown up in the past few months in a way I really didn’t expect. Willie Nelson actually just posted this thing that got like a hundred thousand likes on Twitter about, “Don’t give them an inch of our farmland.” My basic finding is that data centers themselves, the physical buildings, will take up something like one-fifteenth of the land that we currently dedicate to Christmas trees in America, which isn’t nothing, but it’s also incredibly small. On data centers driving up electricity prices… Electricity markets are very complicated and don’t always work in a simple, you increase demand, and the price just immediately goes up for everyone. That’s not really how it works. They have had to slightly raise household electricity prices because of the data center. They’ve reported data centers as being one of several causes, but that’s usually not a significant percentage. On the growing data center backlash It’s hard not to feel like a lot of the anti-data center stuff is also this collective, “I can find this deep meaning in this local struggle against these people who I perceive to be bad.” The general idea that we can all band together as this ragtag team of everyday people and prevent this thing from destroying our local community is a very compelling narrative to people, regardless of the actual specific harms that are expected. I do think general anti-tech sentiment is definitely playing into this. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

  8. Jul 30

    📈 The business of AI: My interview with technology analyst and investor Azeem Azhar

    My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Artificial intelligence is expected to transform the economy, but what about the AI industry itself? Companies across the AI supply chain are now valued in the trillions of dollars. But do the data and current demand justify such lofty expectations, or are investors getting ahead of reality? And when will the AI economy finally begin to live up to the hype? Today on Faster, Please!—The Podcast, I am joined by Azeem Azhar, a Digital Fellow at Stanford’s Digital Economy Lab, the founder of Exponential View, a research platform focused on helping leaders understand emerging technologies and their impact on society. He is also the author of The Exponential Age and the co-author of The State of the AI Economy, one of the first serious attempts to measure the size and trajectory of the AI economy from the demand side and know what customers are actually paying for. We discuss where the AI economy stands today, why businesses are still struggling to realize AI’s full potential, who stands to capture the greatest gains from the technology, and the roles different countries could play in the “AI Race” between the United States and China. In This Episode: * The AI Economy (0:44) * AI’s Return on Investment (6:40) * Will AI Bring an Entrepreneurial Wave? (12:41) * When AI Hits the Bottom Line (17:53) * Who Wins the AI Economy? (23:48) * Europe in the AI Race (30:20) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On AI’s creation of abundance… It may look like abundance when you’re on the other side before the inflection, but when you’re in it, it really looks like a day-to-day grind where you still have to fight for the things that you care about. The notion of abundance in general, I think, defies the realities of physics. You always need energy to get something done. On why AI adoption has been slower than expected… Companies are going through the similar type of process that Paul David describes around electrification, which is that you can put the light bulbs in the workshop—that is the copilot. But to move to the moving assembly line requires a lot more work and a lot more expertise. On AI’s challenge for businesses… No business was ever about, “Can we summarize an email quicker than before?” The question is: At what point do AI tools meaningfully come in to make those decisions happen more effectively—either at higher quality, at lower cost, or at higher speed? On why AI may not lead to immediate job losses… Companies realize that there was so much tacit knowledge in their workforce that they just let walk out the door. I think CEOs will start to want to understand: What are we losing when we cut an entire function for an LLM? On whether we know who will win the AI race… If you’d asked me two years ago, the winner was OpenAI, and Anthropic was really just playing around doing God knows what. So I don’t think we necessarily know who the biggest winners are. Does Anthropic or OpenAI have a significant role to play in several years time? I’m absolutely sure that will be the case. That doesn’t preclude there being other, bigger winners. On Europe’s AI opportunity… There’s things that states can do, even if they’re smaller states like the UK, because they can clear paths, they can help vertical integration, they can get access to the best specific talent. And this is not all about large language models. It’s also about models that can stimulate physics or models that can discover new materials. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

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4.7
out of 5
11 Ratings

About

Welcome to Faster, Please! — The Podcast. Several times a month, host Jim Pethokoukis will feature a lively conversation with a fascinating and provocative guest about how to make the world a better place by accelerating scientific discovery, technological innovation, and economic growth. fasterplease.substack.com

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