hnthrowaway9812's comments

Thanks for this spreadsheet! It's amazing!

It's a wast if they are mostly all trying the SAME things. Which is mostly what is happening.

I want someone to spend a million on a Chess LLM so we can get a sense of how sophisticated they can get at non-linguistic pattern matching.

I want someone to spend a million on an LLM trained on Python program traces so we can try to teach it cause and effect and "debugging". Maybe it will emulate a Python interpreter and get highly reliable at predicting the outcome of Python code.

etc.

It claims to have a knowledge cut-off of 2021. Not sure if its hallucinating or its true.

But when I asked it about the best LLMs it suggested GPT-3, Bert and T5!

It doesn't seem like that's true at all.

If the "best model" only stays the best for a few months and if, during those few months, the second best model is near indistinguishable, then it will be extremely hard to extract trillions of dollars.

Groq seems to be well positioned to give Nvidia a run for their money, actually.

Snowflake could have the same story by hosting Llama 3 which is probably more efficient/better.

You've nerdsniped me so hard that I had to make an account.

There are DOZENS of orgs releasing foundational models, not "a handful."

Salesforce, EleuthierAI, NVIDIA, Amazon, Stanford, RedPajama, Cohere, Mistral, MosaicML, Yandex, Huawei StabilityLM, ...

https://docs.google.com/spreadsheets/d/1kT4or6b0Fedd-W_jMwYp...

It's completely bonkers and a huge waste of resources. Most of them will see barely any use at all.