Linas Beliūnas
@linasbeliunas • 14,340 subscribers
Connecting & deconstructing all things Finance + Tech. FinTech, Financial Technology, and AI constantly meets here on X & in my daily newsletter👇
Videos
Peter Thiel just said America’s deficit era is ending. His argument: once interest rates stopped being zero, the West’s model of big welfare states, already-high taxes, and large deficits stopped being sustainable. There are only three choices left. 1. Massively cut spending 3. Massively hike taxes 3. Keep kicking the can down the road For close to 20 years, the answer has been #3. Ever since the 2008 crisis, we’ve just been borrowing more and more money. The result is a fiscal trap that arithmetic, not ideology, is now closing. Think exploding interest costs crowding out everything else. Trust funds running down. No slack left for the next shock. A country that used cheap money to delay every hard choice. The numbers already show the can is getting heavier: > FY2026 deficit already $1.4 trillion through 9 months and on track for $2T or more > Total federal debt around $40T, roughly 123% of GDP > Annual interest now over $1T Then he added the part people usually skip: “My intuition is we’re close to the point where that ends, and then you’re going to be pushed to a very non-centrist solution of either socialist levels of taxation or some really tough austerity measures.” Zero rates made centrism look possible. Higher rates make it look like delay. It seems America’s real fiscal problem may not be starting the spending. It’s refusing to admit the cheap-money version of kicking the can has an expiration date.
Linas Beliūnas551,783 Aufrufe • vor 5 Tagen
Peter Thiel just said Europe fears success. His argument: German founders treat a working company as something to sell, not something to scale into a Musk- or Zuckerberg-sized giant. The result is almost no large new firms built in decades. Think missing follow-on jobs. No employee millionaires at scale. Rich lists full of heirs instead of builders. When he compared the 50 wealthiest people in each country, Thiel laid out the numbers: - Of the 50 richest Americans, 12 are Gen X or younger. - 9 of those 12 made their own money. > Of the 50 richest Germans, 20 are Gen X or younger. All 20 inherited it. > “Not a single person did something new, made some new money, built a large, new scalable company.” Then he added the cultural twist people usually miss: “One of the things in Germany that people always talk about in this entrepreneurship context is there’s a fear of failure. A ‘no risk’ culture… Perhaps there’s also a fear of success.” If something works, “you’re not going to scale it to this extreme degree like an Elon Musk or Mark Zuckerberg. At some point you’ll sell the company or exit.” It seems that Germany’s (& Europe's) real entrepreneurship problem may not be starting companies. It’s refusing to let the winners get too big.
Linas Beliūnas198,930 Aufrufe • vor 7 Tagen
Instead of watching 1 hour of Netflix tonight, watch this ex-Google Chief Scientist Jeff Dean’s lecture. It’s the clearest explanation I’ve seen of the full AI engineering stack - from building LLMs from scratch all the way to one human coordinating 100 agents. The best part is that it’s useful whether you’ve never touched a model or you’ve been shipping agent systems every day for the past year. Bookmark it & watch the whole lecture this weekend, because it might end up being the most valuable thing you learn all week.
Linas Beliūnas619,970 Aufrufe • vor 1 Monat
Google co-founder Sergey Brin rarely speaks publicly. He just sat down for an unscripted Q&A on Frontier AI and admitted something most lab leaders won’t: Even the people building these models do not fully understand what they have created. In this 29-minute conversation at AGI House, Brin walks through the surprises that actually matter right now: ↳ Specialized models are converging into one general system faster than anyone predicted. - Train on coding and math reasoning mysteriously improves. - Feed it images and geometric word problems get better. - The capabilities bleed into each other in ways nobody fully engineered. ↳ One of the biggest leaps came from the dumbest-sounding trick imaginable: - Just telling the model to “think step by step.” - Brin says there was no obvious reason it should work. It did. ↳ He pushes back on hype around superintelligence (it still can’t solve the impossible), notes that AI mastering a domain has never stopped humans from getting better at it (chess after Deep Blue, Go after AlphaGo), and says something close to transformers is probably enough to reach AGI. ↳ Inside Google, they are already using the AI to build the AI. - That self-improvement loop is where Brin spends most of his time. - World models and physical interaction are the missing piece for the version of AGI that can do anything a person can. Candid, technical, and free of the usual marketing. One of the clearest looks at how the people actually shipping frontier models are thinking in real time. Instead of another Netflix series tonight, watch this talk.
Linas Beliūnas549,742 Aufrufe • vor 2 Monaten
Jeff Dean explaining Google built a ChatGPT-style chatbot roughly a year before OpenAI released theirs. Tens of thousands of Google employees were already using it and loved it. Leadership still killed any public launch because: • “What if people stop searching on Google?” • “What if it says inaccurate or ‘bad’ things?” Google invented the Transformer architecture, and still threw away the first-mover advantage for nothing. Innovator's Dilemma at its finest.
Linas Beliūnas393,772 Aufrufe • vor 1 Monat
Monzo & GoCardless co-founder Tom Blomfield just joined Anthropic. In just 13 minutes, he explains exactly how to build a self-improving, AI-native company. Tom recently served as YC’s General Partner, so he clearly walks through how to create recursive, self-improving AI loops, and why founders who get this right will run companies that improve while they sleep. One of the best videos available to date. From the person who founded two iconic fintech unicorns.
Linas Beliūnas56,696 Aufrufe • vor 2 Monaten
Kimi CEO Zhilin Yang nailed it: "Every AI lab like Anthropic thinks the model is what matters most. That's wrong. It's how you organize the people building it that wins. And that's about Kimi 3.” In this keynote, Moonshot AI founder breaks down exactly how to stop treating the model as the only thing that matters and start winning through superior organization instead. The key? Long context is basically the AI era’s version of RAM - the same jump from 128K to gigabytes, just compressed into a couple of years instead of forty. He traces the idea back to a 1970s Intel chip nobody wanted to buy to show that your biggest advantage, and perhaps your only advantage, is your organization. One of the clearest, most practical frameworks for AI strategy and org design I’ve seen. Instead of another Netflix series tonight, watch this talk.
Linas Beliūnas32,275 Aufrufe • vor 2 Monaten
Aswath Damodaran on AI bubble: “Dot-com was an equity bubble. AI is becoming an infrastructure debt bubble.” In the 1990s, many internet companies raised money, built websites, burned cash, and disappeared. When the bust came, shareholders got wiped out. AI is different, because this boom is not just apps and pitch decks. It is data centers, GPUs, power contracts, fiber, leases, project finance, and private credit. The numbers are wild: ↳ Goldman Sachs estimates hyperscalers may spend ~$5.3T on AI/data center capex from 2025–2030 ↳ Morgan Stanley estimates ~$2.9T in global data center construction from 2025–2028 ↳ Top hyperscalers are projected to spend ~$600B in 2026 alone, with roughly 75% tied to AI infrastructure Dot-com asked investors to believe in traffic. AI is now asking lenders to believe in utilization. If demand keeps compounding, the buildout looks genius. But if demand disappoints, the problem is not just “stocks go down.” It becomes stranded capacity. Refinancing pressure. Private credit stress. Defaults. AI may end up becoming the defining technology platform of our lifetime. But the bubble risk is not where most people are looking.
Linas Beliūnas41,948 Aufrufe • vor 3 Monaten
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