Even in natural language you need to continually learn
learned this from the youth:
if something sucks, you no longer say it's ass. you say it's "cheeks"
e.g. "this model is cheeks"
Core Automation
@CoreAutoAI
Building systems to automate and optimize
- AI discourse often focuses on scaling because of eye popping numbers spent on datacenter compute. Credit assignment is very difficult Most people from outside big labs and even many inside get this credit assignment wrong. It’s worth doing a simple thought experiment: It’s may
- Power of friendship is one of few durable moatsPower of friendship was always going to be one of the new pretraining axis
- We are very proud to co-organize open participation competition inviting scientists from around the world on one of the deep learning problems that is still open:
- In deep learning, deeper is almost always better. If it isn’t, that means you’re just not very good at optimization.One Layer Deeper is officially live! The motivating idea is that some models just don’t want to learn. Most optimizer benchmarks ask how quickly you can train a given model, but baked into that question is the assumption that it can be trained (well) at all. We think this
