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by omegalulw
1716 days ago
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> We have beat humans on every single atari game by at least one order of magnitude There's mechanical skill involved, it's not purely intelligence. > We are also seeing models that are able to generate code given prompts. This has been discussed a lot, but the generated code is nowhere close to good enough for large projects where you really need intelligence. > Given enough representational power, I don't see why a... Except that it's not linear scaling. The larger NLP models consume absurdly large resources, it's not straightforward to "get enough representational power" Also, most models fail to adapt to new tasks outside of their narrow training scope, that's a massive problem. Even if you make models large, you will find that getting data covering all edge cases is exponentially expensive. |
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> This has been discussed a lot, but the generated code is nowhere close to good enough for large projects where you really need intelligence.
> Except that it's not linear scaling. The larger NLP models consume absurdly large resources, it's not straightforward to "get enough representational power"
When allowing maximizers to run wild, just like reinforcement learning, they will find hidden solutions, and when the model can provide an action in the form of a dense representation, it can also use code generation models with much more precision that we do because it can skip the encoding part.
> Also, most models fail to adapt to new tasks outside of their narrow training scope, that's a massive problem. Even if you make models large, you will find that getting data covering all edge cases is exponentially expensive.
We are still 6-7 years in. Deepmind's last paper on general agents has them generalizing to new tasks relatively easily. It's still not there, but we miles ahead than we were 5 years ago.