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I would assume, without actually having checked, that traditional neural networks have already been extensively run on this datasets. Seems like the "standard" thing to do anyways.

My guess is that you can find 99% of Maya pyramids in a Lidar set in a fairly short time with a traditional neural network, but you might find the last few using a network of AI agents, because they are capable of "creative" problem solving and using different methods/parameters/tools over several iterations.

by dist-epoch23 hours ago|

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The problem with specialized models is that they don't have "common sense".

You train a cat-classifier, and they will fail for a plush cat. Or maybe fail the other way, but not realizing it should also report a plush cat.

LLMs are much more robust, "find only the real cats in this picture" or "find all cats, including artificial/drawings/..."

And yes, you can add more training data to your classifier, but it's a never ending battle.

by sedictious21 hours ago|

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You are right and I get the point (I have also worked on some solutions, though it's not my expertise), it's just that usually the people creating the ML model are supposed to substitute the creativity that the model itself does not offer. You run the model, see the false negatives and start thinking of what is missing, if there is also information that can be represented differently or can be compressed, if there is some other approach entirely. Good ML ultimately requires having deep expertise of your domain and can sometimes lead to deeper insight.

With LLM you unlock a whole new world of possibilities regarding the speed and result but we are also finding ourselves in a position where "asking the LLM" because the cheat for everything, no reason to dig further