5 ms·
This is actually a pretty neat, self-contained implementation that can super easily extended beyond stereotypical natural language models, for example to create
by polygamous_bat 4y ago
This is actually a pretty neat, self-contained implementation that can super easily extended beyond stereotypical natural language models, for example to create world models for video games [1] or to create robot models that can learn to imitate from large, chaotic human demonstration data [2] (disclaimer, I'm an author on the second one.) Basically, GPT (or minGPT) models are EXCELLENT sequence modelers, almost to the point where you can throw any sensible sequence data at it and hope to get interesting results, as long as you don't overfit.
Even though I have only been working on machine learning for around six years, it's crazy to see how the landscape has changed so fast so recently, including diffusion models and transformers. It's not too much to say that we might expect more major breakthroughs by the end of this decade, and end in a place we can't even imagine right now!
[1] https://github.com/eloialonso/iris https://github.com/eloialonso/iris
[2] https://github.com/notmahi/bet https://github.com/notmahi/bet
- a-dub 4y ago> Even though I have only been working on machine learning for around six years, it's crazy to see how the landscape has changed so fast so recently, including diffusion models and transformers. it's pretty wild considering how hidden markov models were considered state of the art not all that long ago.
- visarga 4y agoSome people demean GPT-3 saying it's just a Markov model.