Tubby Cats investment thesis...
- they are cats
- crypto native visible lead artist and team
- well matched traits make each one feel unique
- 1 address = 1 mint on allow list, makes it much harder to flip and crush floors
- meme them to the moon
@danshipper I really can’t stand the full LLM written articles, there’s no human voice in the article at all. Becomes really grating after the first 5-10 paragraphs
@scaling01 4.8 is better at coding and knowledge work but hates high difficulty tasks? Does this mean the model itself finds these tasks easier? Or that it’s a reluctant participant?
Very weird result that feels contradictory
New paper:
We finetuned models on documents that discuss an implausible claim and warn that the claim is false.
Models ended up believing the claim! Examples:
1. Ed Sheeran won the Olympic 100m
2. Queen Elizabeth II wrote a Python graduate textbook
When I found out the 49ers were using ChatGPT to draft people I asked it who the 49ers should draft in 2026 without looking using the web tool (so it wouldn’t see who they picked) and one of the choices was Emeka Egbuka. It then hallucinated a guy called Kevin Stribling
@deanwball Easily from GPT-5.2 through 5.4, not sure if 5.5 carries the same tic forward. Just gotta work “goblin” in there and we’ve got the whole stew
@tenobrus I’ve noticed this a lot in the past couple of weeks. Opus delegates and the subagent fucks it up big time, then Opus has to go back and fix everything.
Made me trust every output less and add extra review layers
@AndrewCurran_ Btw I don’t believe this is “leaked” but a guess/estimate based on publicly available information.
I saw it yesterday from another account and I can’t find the original post. The sheet also has a lot of Claude excel tells