
ryan
2.4K posts

ryan
@RyanJosephHill
currently @GigaAI, previously a product manager, startup generalist, culinary student, and woodworker. Ask me anything about food.



hosting a small invite-only sake tasting night in SF with some cool founders and builders~ comment if you’d like an invite :)

Introducing hallucination correction. We have reduced hallucination by 70%. Giga's hallucination rate is at ~1%. Better than the best frontier models. Deploy AI your customers can trust.



Introducing hallucination correction. We have reduced hallucination by 70%. Giga's hallucination rate is at ~1%. Better than the best frontier models. Deploy AI your customers can trust.




4.7 is completely unusable

seriously, working with AI is MISERABLE for one and only one reason: having to re-explain the same thing "oh yeah this new session obviously doesn't know what proper case trees are, so let me explain it for the 5000th time in my life" I'm tired AGENTS.md doesn't solve this because it is impossible to fit the entire domain knowledge without nuking the context - it would be 1m+ tokens worth RAGs don't solve this, the agent won't search unknown unknowns SKILLs don't solve this unless I keep like a collection of 1750 skills with specific cuts of domain knowledge for each possible subset of my domain that I might need in a given chat, but that's a lot of manual work recursive LLMs or whatever don't solve this for the same reason, you can't dump a domain book and expect the AGENT will magically guess that it is supposed to search for a specific bit knowledge. unknown unknowns fine tuning doesn't solve this (OSS models suck and OpenAI / Anthropic gave up on user fine tuning) I honestly think a good product around fine tuning on your domain would be a major hit and an underdog lab should take this opportunity










