@danellisona Billions go into making models smarter, and a tiny fraction goes into making them verifiable. If I'm worried about anything, it's that ratio. More bets should go to teams like @runlatentai, catching hallucinations by reading model internals.
In SF for Tech Week + COLM next week and would love to grab coffee with anyone building with LLMs. Especially if your model has ever been confidently wrong in front of a customer. DMs open!
Some news: I'm in YC F26, building Latent.
I've done interpretability research for a while, and one thing keeps showing up: models often know they're about to be wrong before they say it.
Latent turns that into a score on every answer your open-weight model gives. Demo below 👇