holy fuck, a hair dryer at a Paris airport broke Polymarket weather markets & made someone $34,000 richer - polymarket was settling Paris temperature bets on a single Météo France sensor sitting near the Charles de Gaulle runway perimeter - basically unguarded - the guy bought the long-shot outcome (like "22°C" when everyone expected 18°C) for pennies, since nobody thought it'd hit - then he walked up to the probe and briefly heated the air around it with a portable heat source, spiking the reading just long enough to register as the daily max - temperature snapped back to normal in minutes, the market resolved in his favor, and he cashed out - twice, on April 6 and April 15, before Météo France caught on and filed charges hyperstitions.

Exclusive: A U.S. official has alleged wrongdoing by U.S. spy chief Tulsi Gabbard in a complaint that is so highly classified it has sparked months of wrangling over how to share it with Congress, according to people familiar with the matter on.wsj.com/45Mx1aO

Anthropic is donating the Model Context Protocol to the Agentic AI Foundation, a directed fund under the Linux Foundation. In one year, MCP has become a foundational protocol for agentic AI. Joining AAIF ensures MCP remains open and community-driven. anthropic.com/news/donating-…

There’s this notion that product market fit is this binary condition that once you pass the gate, you’re done. And that’s no longer the case. Product market fit is like United Miles. You continue to fly to maintain 1K. And we saw it between 2021 and 2024, companies that were classic software companies literally overnight lost their product market fit. And that’ll be very much the case. AI is changing what the market wants & what’s possible so quickly that PMF is no longer static. I discussed this idea on TBPN with John & Jordi. youtube.com/watch?v=_0SJe7GX… I remember reading Steve Blank’s The Four Steps to the Epiphany in 2005. It established the idea of product-market fit. The magical moment customers pull your product into the market, & the playbook by which to develop it. In the previous era, once PMF was established, it was taken for granted that it would continue. The underlying technologies advanced incrementally. AI models & their capabilities evolve so quickly today that product market fit must be constantly re-established. Polymarket predicts Google will have the best AI model at the end of the year. At the beginning of 2024, Google was far behind. The most advanced companies in AI are still jockeying for position & so are startups. This is one reason for the boom in deployed engineers—teams need people working directly with customers to understand these dynamics in real time. The velocity of change demands constant feedback loops. Product-market fit is not a one-time event. As the technology changes rapidly underneath, so must your product. tomtunguz.com/product-market…

Until ~2015, GitHub Pages hosted over 2 million websites on 2 servers with a multi-million-line nginx.conf, edited and reloaded per deploy. This worked incredibly well, with github.io ranking as the 140th most visited domain on the web at the time.

I don't know what labs are doing to these poor LLMs during RL but they are mortally terrified of exceptions, in any infinitesimally likely case. Exceptions are a normal part of life and healthy dev process. Sign my LLM welfare petition for improved rewards in cases of exceptions.