alt Hacker News > But as impressive as these feats are, they obscure a simple truth: being a "test-taker" is not what most people need from an AI.
I haven't looked at the benchmark details they've used, and it may depend on the domain, empirically it seems coding agents improve drastically on unseen libs or updated libs with the latest documentation. So I think that a matter of the training sets, where they've been optimized with code documentation.
So the interim step until a better architecture is found is probably more / better training data.
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jkhdigital • yesterday at 11:37 PM
For all the disparagement of “fact regurgitation” as pedagogical practice, it’s not like there’s some proven better alternative. Higher-order reasoning doesn’t happen without a thorough catalogue of domain knowledge readily accessible in your context window.
Don't confuse what I'm saying, I do find LLMs useful. You're right, about knowledge based systems being useful and I'm not disagreeing with that in any way. I don't think any of the researchers claiming LLMs are not a viable path to AGI are. We're saying that intelligence is more than knowledge. Superset, not disjoint.
And yes, the LLM success has been an important step to AGI but that doesn't mean we can't scale it all the way there. We learned a lot about knowledge systems. That's a big step. But if you wonder why people like Chollet are saying LLMs have held AGI progress back it is because we put all our eggs in one basket. It's because we've pulled funds and people away from other hard problems to focus on only one. That doesn't mean it isn't a problem that needed to be solved (nor that it is solved) but that research slows or stops on the other problems. When that happens we hit walls as we can't seamlessly transition. I'm not even trying to say that we shouldn't have most researchers working on the problem that's currently yielding the most success, but the distribution right now is incredibly narrow (and when people want to work on other problems they get mocked and told that the work is pointless. BY OTHER RESEARCHERS).
Sure, you can get to the store navigating block by block, but you'll get there much faster, more easily, and better adapt to changes in traffic if you incorporate route planning. You would think a bunch of people who work on optimization algorithms would know that A* is a better algorithm than DFS. The irony is that the reason we do DFS is because people have convinced themselves that we can just keep going this route to get there but if more intellectual depth (such as diving into more mathematical understandings of these models) was taken then you couldn't be convinced of that.