@notkevinzhang Looking to build a simulation of the US healthcare system (patients, doctors, PBMs, Pharma companies, etc) - would love access to see if this fills a fews needs for my DS team!
@mitsuhiko The small purpose built model feels like the path forward. Both because it can run locally and it’s fast and it can be aggressively trained to follow a specific languages successful design patterns. Honestly, I just want infrastructure to make any train a tiny LLM on their task
We really need to stop building Agent APIs based on LLM ergonomics and start making them live up to their name: Agent. You give the agent a task, it tells you when it’s done. Not arbitrary chat messages. A clear, done signal.
@tobi N8N is seeing a real drop off in usage as models can replicate the workflows in a single shot or close to it. The drag and drop node editor doesn’t keep folks around. I can’t imagine that day being far off for data scientists as well.
@NoahCRothman Private data center deals have been increasing the price of capacity bids at the electrical auction in PA. I’d prefer we build more power plants but something needed to be done to slow prices increases.
PRODUCT MANAGERS If your software is critical for work (I'm looking at you @claudeai ), stop putting feature launches in a popup window. You are literally delaying me from doing the thing I need to accomplish with your product.
Excellent article by @_anniebabannie_ on the overlap of compression and prediction. Make me wonder what next-gen compression will look like when every OS/Browser has an LLM available for decompression.
https://t.co/etaoin07NC
@daveslutzkin@Devinda_me@KentonVarda Yes and systematically improve our tech stack to make certain categories of errors hard/impossible. Rinse and repeat until we don’t call it vibe coding anymore.