Is Sovereign AI Possible? We Ask Ryan Wain of the Tony Blair Institute

Can AI Create Materials That Never Existed?

CuspAI was co-founded by Max Welling, a pioneer of modern AI. But instead of building chatbots, he's creating and harnessing AI to discover new materials for everything from carbon capture to water purification, plastic alternatives, and more efficient batteries. If this works, it could change everything. But can it? And if so, when? This week, we’re talking science, scale, and when CuspAI will be able to deliver with company co-founder Max Welling. Before talking to Max, hosts Autria Godfrey, Stephen Horn, and Laila Rizvi discuss why AI-powered material creation is so exciting… and why it needs to be addressed with little skepticism. Autria kicks off the interview by asking Max Welling about CuspAI’s plans for 2026. He explains that they’re currently building their platform, and that 2026 will be a time when CuspAI will work with customers to actually design new materials, synthesize them, and put them into the real world. In 2026, they also plan to connect to high throughput self-driving lab experimental facilities to increase the speed of experimentation. Max unpacks how the process works, starting with a customer describing the real world material that they need, to AI agent assessment to see whether anything already exists that can fit the task, to generating entirely new materials that never existed before. They typically generate “hundreds of thousands to millions of those,” which are first tested by a digital twin consisting of very cheap property predictors that quickly assess whether the material could exist in this world, followed by sophisticated molecular dynamic simulations to assess their actual properties in high accuracy. Laila and Max discuss the process of verification in materials science, and Max lays out some of the difficulties that lay between moving from simulation into the real world. Autria asks where their first successes will come. Max predicts that it will be in the semiconductor space, partly because of partners like Hyundai that have the need and the capability to manufacture the new materials at scale. Max explains how semiconductor lithography has gotten to a point where they’re creating the smallest structures possible that are the size of a few atoms, and in order to make that happen they really need new materials. “We are now creating chips that grow in the third dimension, so they become sort of taller.” Stephen brings the conversation around to scalability, the importance of finding partners that can power that growth, and whether that scale can even happen in Europe. Max makes a distinction between making materials at scale and scaling up a company, but says that Europe has the right companies for both. Laila raises the issue of commercial demand versus public good, and Autria asks about the pressure around using AI for the betterment of humanity. Max’s answer: “For me, the only reason I do this is because I do want to make a positive net impact… And I think the same goes for all our employees.” As always, we end with our lightning round questions. Autria asks where people will draw the line with AI, and Max says “We don't want AI to invade our privacy. We don't want AI to be used for mass surveillance. We don't want AI to get us addicted. We don't want AI to manipulate our opinions.” Laila asks Max for something that's widely accepted in his field that he disagrees with. He says that AI superintelligence replacing humans might be a little overhyped at this point. And Stephen asks Max what will happen in 18 months that people aren't talking about now? Max’s answer: “That we can design materials that feel quite exotic right now, with properties that you could not imagine, and it could completely change the world, and hopefully for the better. That's what we are shooting for.” What do you think? Will CuspAI be able to deliver on their promises in 2026? Will AI help us create new materials that benefit humankind in less than a year? Or will it take them longer? Tell us in the comments.

Will AI Help You Live 50 More Years? Immunologist Derya Unutmaz Weighs In

If you survive the next five years, says immunologist Derya Unutmaz, MD, you will live for the next 50 thanks to what AI can accomplish in medical research. But is AI really a silver bullet that solves humanity's most difficult problems? Or does that kind of thinking get us into trouble? Professor Unutmaz is an NIH funded immunologist, with 35 years of published research and more than 100 papers, and a professor at the Jackson Laboratory. But when it comes to what he calls the bio singularity – the moment when the convergence of AI and biotechnology radically transforms human biology – he’s ahead of most of his fellow scientists and researchers. He’s also ahead of most predictions about AGI and SGI, or super general intelligence, by at least a couple of years. But what if he’s right? “In the US alone,” Dr. Unutmaz tells hosts Autria Godfrey, Stephen Horn, and Laila Rizvi, “there are 12 million misdiagnoses every year. Only about 70% of the diseases are diagnosed correctly by medical professionals. And about 700,000 people die or…become sick because of misdiagnoses, okay?... with AI, if you could improve that by 10%, you are saving hundreds of thousands of lives.” For Derya, AI means the totality of artificial intelligence, including LLMs, agentic systems, world models, and more. He likens the different areas of AI to how the human brain works, with different areas managing different tasks. He even likens his own scientific training to the way AI models are trained. He explains that there are multiple levels of Artificial General Intelligence, where general means that you can generalize knowledge. “So for example, if you learn something on one topic, we can somehow generalize that information to learn something completely different, or understand something completely different.” According to Derya, we’re already at AGI Level One, where a system is as good as the top 1% of humanity. He thinks there will eventually be three or four levels of AGI. Dr. Unutmaz says that when Demis Hassabis is describing AGI, he really means ASI, or Artificial Super Intelligence, which is better than human. Derya says that “the Einstein test” – where we train an AI models on pre-1911 knowledge and ask it to recreate the General Theory of Relativity – is unfair, because only a few people in the history of humanity have been capable of such incredible insight. He also thinks we’ll reach a point where most jobs that depend on using a “computer, or your intelligence, or your experiences or expertise could be eventually replaced by AI.” In fact, he says, “I’m a scientist…and I can tell you that current AI models like GPT-5.2 PRO [are] simply better than me.” Derya says we are going to have to rethink the whole fabric of society and the impact of AI will be extremely disruptive. Whether he is right or not about the timeframe for AGI or the bio singularity, Stephen, Laila and Autria agree that the disruption from AI is here, now, and not enough people are addressing it. Do you think AI will cure disease within a decade, or that it's just a dangerous thing for a scientist to claim? Tell us in the comments. CHAPTERS: 00:00 - Will AI Cure All Disease Within 10 Years? 00:55 - AI, Disease and Bio Singularity with Immunologist Derya Unutmaz 01:21 - Why So Much Hype and Uncertainty Around AI and Science? 03:06 - We Can’t Leave This to the Scientists… or the Tech Bros 03:55 - If You Survive the Next 5 Years, Will AI Help You Live 50 More? 04:20 - Tech and AI Capabilities Doubling Every Few Months 07:31 - What is AGI? 08:44 - Are We Prepared for the Biggest Transformation in History? 10:48 - Is AI Hitting a Wall? Is the Einstein Test Fair? 13:58 - I’m a Scientist, and GPT-5.2 PRO Is Better Than Me 15:29 - Will There Always Be a Place for Humans In Science? 18:17 - Is It Unethical for Doctors and Scientists Not To Use AI? 24:55 - Aging Can Be Reversed Says Dr. Derya Unutmaz 25:26 - Is There Any Point in Publishing Scientific Papers Now?

Wikipedia, Media Bias and AI with Jimmy Wales

As AI gets more capable, will it make public information more trustworthy, or less? Does news media have to be biased to be financially successful? Is AI a threat to Wikipedia or will we always be reliant to the human component when it comes to seeking trustworthy information? These are timely questions about AI, information, technology and trust that affect us all – which is why Stephen Horn, Autria Godfrey and Laila Rizvi are interviewing the founder of Wikipedia, Jimmy Wales. We start with a discussion of trust about where we get our information, and how to build trust amidst the changing economics of news media and AI. With Wikipedia celebrating its 25th Anniversary, Autria asks Jimmy how they overcame the public’s initial distrust and what he thinks about the current cynicism towards AI. He admits that “There is, you know, a cycle that happens…when the quality is low and something's very new, then people obviously are skeptical and quite reasonably so.” Laila asks if we’re close to AI superintelligence, and Jimmy explains that he’s a tech geek but not an expert in AI. The people he listens to, his friends Gary Marcus and Demis Hassabis, think we need some fundamental breakthroughs before that. Of course, he says, they may be wrong and things are moving pretty quickly. “It’s a classic sort of thing in tech, it’s an old saying: People tend to overestimate the short run and underestimate the long run.” The conversation turns to the value of neutrality and unbiased information. Laila suggests that people are happy with the ease of the answers they get from AI or social media and don’t have the luxury of researching every issue. Jimmy offers an “imperfect” analogy to junk food, saying “Junk food’s easy. Tastes really good right now… So I don't buy [crisps]. I don't like to have them around because… I actually do have a higher order sort of brain.” Stephen points out that the media world seems to be moving beyond providing multiple perspectives on an issue, and that there is no business model for neutrality. Jimmy disagrees, citing Wikipedia’s popularity, which is higher than the top 10 newspapers combined, and suggests that, when it comes to neutrality and fighting bias, “We have to fight for it.” In our rapid fire segment, Autria asks where people will finally draw the line when it comes to AI. Jimmy cites OpenClaw and his feeling that people will draw the line between using AI to get things done and the improper use of personal information by that AI. Laila asks Jimmy what's something that's universally accepted in his field that he disagrees with? His answer: “That news media has to be biased to be financially successful,” although he admits, “I'm a minority viewpoint there.” Finally, Stephen asks what Jimmy sees in the future that we’re not talking about today? Jimmy says we’re focused a lot about AI in LLMs, but there are other things going on like advances in biology, drug discovery, driverless cars and other positive, transformative developments that deserve more attention. “I think there's a lot more that's going to come that's going to be really pretty amazing.” CHAPTERS: 00:00 - Introduction 01:00 - Is Trust in Ai, Tech and Media in Short Supply? 04:10 - Early Skepticism about Wikipedia and AI 05:34 - When and Where To Use LLMs and AI 06:40 - Jimmy Wales on AI: Pretty Terrible at Facts but Kind of Creative 07:17 - Can AI Work With the Right Framework? 10:04 - Will AI Replace Wikipedia? 13:22 - The Seven Rules of Trust - Neutrality and Bias 15:18 - People Tend to Trust Individuals Over Abstract Entities 16:22 - Echo Chambers, Convenience and Trust 20:43 - Media Literacy and the Economics Of Trust 22:23 - Is There a Media Business Model for Neutrality? 24:19 - Drawing the Line Between Personal Info and Getting Things Done 25:14 - News Media Doesn’t Have to Be Biased to Be Financially Successful 25:38 - Bright Future for AI in Biology, Drug Discovery, Driverless Cars, More 27:11 - Can AI and Wikipedia Coexist?

Is Sovereign AI Possible? We Ask Ryan Wain of the Tony Blair Institute

NOTE: This episode was recorded before the recent conflict involving Iran began. The US and China control over 90 percent of the world's AI computing power. In practice, that means most countries rely on American or Chinese firms, chips, and rules to access the most advanced systems ever built. Some call it partnership. Others call it dependency. Our guest today, Ryan Wain, the Senior Director of the Tony Blair Institute for Global Change, advises governments on how to navigate this. His answer? Stop trying to compete. In fact, he calls self-sufficiency a "vanity project." But here's the question: if you're not one of the two countries holding the keys, what leverage do you actually have? And if you are America or China, should you share this power at all? Hosts Autria Godfrey and Laila Rizvi start off with the TBI report which argues that AI self-sovereignty is unrealistic for most countries. Autria asks if AI power is already so entrenched that we’ll just see a widening divide between the haves and the have nots. Ryan says that the US and China have spent so much money building frontier models, that other countries building their own frontier AI is now an unrealistic strategy. Instead, they need to figure out how to take part in the AI revolution by leveraging their strengths and opportunities, like Kazakhstan’s pan to train a million people to become AI engineers, or Kenya, which has geothermal energy they’ve used as leverage build partnerships with tech companies to bring AI to their country. Ryan says, "Control what you can, steer where you have leverage, and then depend on those partners for the rest." Could geopolitical tensions bleed over into AI access, so even allies like the UK could end up locked out of US-based AI? Ryan argues that long before this happens, countries need to not get locked into one model. He points out that “Sovereignty is a choice and we have levers that we can pull” and that the UK and Europe are looking at multiple models, including open source models. What about concerns that AI can be used to create more authoritarian states as we’re seeing in China and the US? Political leadership needs to understand the importance of harnessing technology and make the case that it can provide greater privacy protection, safety from crime, and even security during wartime. He points out how Estonia has digital ID and yet ranks as the second freest online environment, after Iceland. Should the US be letting China get its chips? Is AI more like the development of 5G or more like the nuclear arms race? Neither, says Ryan. Sovereign frontier models don’t guarantee national prosperity or security. Advantage comes from a robust and diverse set of tech companies like America has. The path involves proper industrial strategy, communicating with the public, addressing energy needs and data centers, training, and supporting founders and leaders to build next gen AI companies that transform everything from healthcare and public services to boosting national security. CHAPTERS: 00:00 - Power, Partnership and Dependency 01:22 - Is this a Catch 22? 02:30 - What Does AI Sovereignty Really Mean? 03:07 - Is It Better To Build Your Own Frontier Model? 04:02 - What If the US Pulls the Plug? O4:58 - Frontier AI Models Are Impossible for Many Countries 05:34 - What Are The 3 Dimensions of AI Sovereignty? 07:14 - You Can’t Be Dependent on One AI Model 07:59 - Sovereignty Is a Choice and We Have Levers that We Can Pull 08:12 - Europe Embraces Open Source More Readily than US or China 08:56 - Smaller Nations Should Leverage Their Strengths with AI 10:23 - Digital ID, Facial Recognition, Surveillance 15:36 - Should US Give AI Chips to China? 17:36 - Europe Needs More Global Tech Startups 18:40 - The World Is Interconnected 19:54 - Is AI Sovereignty a Fantasy? 20:39 - What Advantages Do Countries Other Than China and the US Have? 22:25 - Energy Costs, Talent and Industrial Strategy 26:30 - Is True AI Sovereignty Even Possible?

AI Superintelligence: Are We Racing Toward Extinction?

Will AI destroy humanity? Most people think that's science fiction. The people actually building it aren't so sure. Geoffrey Hinton - the Godfather of AI - says there's a 10 to 20 percent chance AI wipes us out. OpenAI’s Sam Altman told Congress his own technology could 'cause significant harm to the world.' Our guest, Malo Bourgon, CEO of the Machine Intelligence Research Institute (MIRI) has been warning about this for two decades. He says a machine doesn't need to be sentient to become a global risk. And today's safety measures? Nowhere near enough. Can we build an off switch for a machine that's smarter than us? Malo tells hosts Autria Godfrey and Laila Rivzi that he thinks we’re on the path to building systems that are radically smarter than us, speeding faster in a race to build systems that we don’t understand and that we don’t know how to control that “could end up with none of us around to see the future we could have built instead.” While he’s not worried that current AI models are existentially dangerous, Malo agrees that some emergent behaviors, like the deception we’re seeing in smarter general systems, suggest that if we continue to scale towards superintelligence, they’ll only have a bigger impact. The trio discuss whether it would even be possible to build in a safeguard, like an off switch. Malo considers this a losing battle if we wait too long and even then, it would be better if we built a broader system that allows us to not get into that position in the first place. Some harms and disruptions from AI are already happening. Malo suggests that we need to find some way to have coordinated action globally, even among adversaries. When it comes to existential risk, he draws a comparison to the nuclear arms race and the cold war, and how, thanks to treaties and agreements and some luck along the way, we’re still here. Autria asks about specific ways AI can lead to a catastrophic, apocalyptic ending, including disruptions to the food chain, the creation of bioweapons, mass unemployment and faltering economies. Malo says even if we solve those, there remains the core danger which comes from a misalignment of the values and goals of the superintelligence we build and our own. It doesn’t have to be evil, it just has to” care about weird, other things that aren’t the things we care about and it wants to pursue those things” with an indifference to our existence. So what would convince Malo that AI is safe? Changing how we create AI systems, he says, from growing them “in a very brute force way” the way we do now to crafting them with a more principled sense of what we’re trying to do to make them safe. Finally, Malo suggests that the claim that “the people running these companies are, you know, bad, immoral people" isn’t quite right. He says that most of “these people aren't actually villains, they're normal people who are kind of trying to do the right thing but they're in a really bad situation. But I also think they're also doing a bunch of bad stuff.” What about you? We want to know what you think. How concerned should we be about a doomsday scenario? How concerned are you? Tell us in the comments below, CHAPTERS: 00:00 - Profits, Power, and AI Risk 02:36 - Are We Racing Toward Extinction? 03:33 - Are Big Tech’s Predictions of AGI Accurate? 04:50 - Are AI Models Exhibiting Signs of Understanding? 05:01 - Deception in Today’s Models 07:51 - Can’t We Just Build an AI Off-Switch? 10:10 - What Can We Actually Do? 11:06 - Harms Are Already Here – More Over The Horizon 12:00 - Global Race to AI Superintelligence 13:00 - Parallels to Nuclear Arms Race 15:14 - Pathways to Catastrophic Risk 16:14 - The Boss Fight – Misalignment As The Core Danger 18:51 - What Would “Safe” Look Like? 19:40 - Rapid Fire Questions for Malo Bourgon 19:44 - What Does Your Field Get Wrong? 20:53 - Where Do People Draw The Line On AI In Their Lives? 22:24 - Post-Interview Reflections 24:44 - What Do You Think: Doomsday Scenario or Not?