Solomin Podcast

Is calorie counting really a good way to judge how healthy a food is? Does carrying extra weight always mean something is wrong with your health? And does sugar really “feed” cancer? In this episode, we speak with Giles Yeo, Professor of Molecular Neuroendocrinology at the University of Cambridge. For more than 25 years, he has studied the genetics of obesity, eating behavior, and the mechanisms through which the brain regulates appetite. In this episode: — Why don’t calories tell the whole story when it comes to nutritional value? — How does genetics influence appetite, overeating, and weight gain? — When does excess body fat actually become dangerous to your health? — Is sugar really addictive, and does it “feed” cancer? — Why might orange juice be more harmful than Coca-Cola? — Do intermittent fasting and Ozempic actually work? — Which principles of healthy eating matter more than constantly counting calories? ▶︎Gleb Solomin's X Account: https://x.com/gleb_solomin200 ▶️︎ Follow Giles Yeo: X: https://x.com/GilesYeo?s=20 Instagram: / gilesyeo ▶︎ For business inquiries: adv@glebsolomin.com

Most AI researchers think alignment is a hard problem. Roman Yampolskiy argues it's an impossible one. Yampolskiy is a computer scientist at the University of Louisville and one of the longest-standing voices in AI safety research. For over a decade he has argued that controlling a system more intelligent than ourselves isn't a challenge the field will eventually solve — it's a structural limit we can't get past. His position sits at the far end of AI safety discourse, and most of the field disagrees with him. In this conversation we get into why he holds it, what he thinks the rest of the community is missing, and what the next decade looks like if he's right. What we cover: The impossibility argument: why he sees alignment not as a problem to solve, but as a wall. His timeline for ASI, and what — if anything — could meaningfully slow it down. Why he's skeptical of the alignment work being done at the frontier labs. What happens to economies, employment, and human agency in the years before ASI arrives. Whether any policy or technical move in 2026 actually buys time. If Yampolskiy is wrong, this is one researcher's pessimism. If he's right, almost nothing else we're doing matters.