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That’s trivializing deep learning, calling it merely a dataset. It’s something that was grown, not built. It’s patently false to say that models don’t create i
by benatkin 2y ago
That’s trivializing deep learning, calling it merely a dataset. It’s something that was grown, not built.
It’s patently false to say that models don’t create information. What about AlphaGo? Why is it hard to tell exactly why an LLM arrives at a particular response? Again, grown, not built.
This is what Connor Leahy emphasizes. It’s worth checking out some of his content.
- upghost 2y agoNo, this is false. Reinforcement learning also uses a dataset, it's just not an enumerable dataset. The dataset it is trained on comes from the Bellman Backup equation (or variants, including DL variants) being run against a simulation (which is an unenumerable dataset). The reward model can only make a prediction against the state and observe the actual reward output and backpropagate the error differential. This is the way all DL works, as function and dataset approximators. It is not trivializing the field.
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