hallqv

They promised us super intelligence - all we got was valid json

How does it differ from Poetry

E.g. msnbc, New York Times, cnn

This discussion is so dumb - finetuning a base model costs ~$1 with LORA/QLORA and can yield same performance as gpt-4, but at 1/100 of the cost per token.

What Bloomberg did for $10M was not finetuning..

lol Emad was always seemed like an obvious fraud to me. Not quite SBF level but same vibe. Whenever someone goes overboard on the nerd look it’s always a red flag.

The incumbent US car brands barely does any manufacturing themselves anymore, they are mainly big procurement + assemly + marketing blobs.

Not very conducive to driving product innovation.

Afraid of what..? What’s the risk?

Whoever is dumb enough to invest in a company that hasn’t even bothered to come up with their own company name, but just copied the name of the current most hyped competitor in their category, deserves to lose their money.

Depends on your definition of winning - special-purpose tuning is vastly more cost effective since it allows you to train a smaller model that can perform specific tasks as good as a bigger one.

A good analogy is building a webapp - would you prefer to hire a developer with 30+ years experience in various CS domains as well as a PhD or a specialized webdev with 5 years experience at a tenth of the rate?

Gary Marcus is not a serious person

If I had a penny each time a human has confidently concluded something that is entirely incorrect… I’ve inadvertently done it countless times myself, and so has every person I know of.

What you are talking about I would call guessing :)

Fact of the matter is that sota LLMs are highly accurate predictors for many topics, certainly above any living human in terms of total AUC of correct predictions on fact based questions. Some humans are better on certain topics, but noone can match total AUC since LLMs has such breadth.