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by D-Machine 136 days ago
> The LLM can output to a tool calling which moves the bike.

No, it literally cannot. See the reasons I give elsewhere here: https://news.ycombinator.com/item?id=46948266.

A more general AI trained with reinforcement learning and a novel architecture could surely learn to ride a bike, but an LLM simply cannot.
2 comments
skeptic_ai 136 days ago
I don’t get it from your message why am llm can’t do it

Related: Have you seen nvidea with their simulated 3d env. That might not be called llm but it’s not very far away from what our llm actually do right now. It’s just a naming difference

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anthuswilliams 135 days ago
This argument was specifically about LLMs, not about other techniques (RL, multi-armed bandit, etc) that might be better leveraged to accomplish this type of goal.

An LLM which makes a tool call to a function called `ride_bike`, where that function is a different sort of model with a different set of feedback mechanisms than those available to the LLM, is NOT the same thing at all. The LLM hasn't "learned" to ride the bike. The best you can say is that the LLM has learned that the bike can be ridden, and that it has a way of asking some other entity to ride on its behalf.

Now, could you develop such a model and make it available to an LLM? Sure, probably. But that's not an LLM. Moreover, it involves you, a human, making novel inroads on a different sort of AI/robotics problem. It simply is not possible to accomplish with an LLM.

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CamperBob2 134 days ago
(Shrug) LLMs, being composed of MLPs, belong to the class of universal approximators.
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D-Machine 134 days ago
Theoretical, infinite-width, single-layer MLPs are universal approximators: modern models that actually exist are not.

And modern transformers definitely underperform models with built in priors (e.g. CNN) when they don't have massive amounts of data. Nevermind that LLMs simply can't at all handle all sorts of data types https://news.ycombinator.com/item?id=46948612.

Just another example of an HN commentator making statements about something they don't have any actual basic understanding of. Try reading some actual papers instead of the usual blog posts and marketing spam from frontier AI companies, you might learn something important.

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