[bwfan123]

> AI is largely automating the most tractable parts of science rather than expanding its frontiers

By definition, creativity cannot be automated, and AI is a fantastic automation machine. It can explore thinking paths at a rate humans cannot match. But creativity is bringing the unthinkable into the thinkable, and that requires sensory experience [1]. Specifically, new definitions and symbols which never existed before. Imagine the concept vector space, and expanding that with new independent dimensions. Is that even possible ? When you look at history the answer is yes !. And each time there was an independent dimension added, it was an act of genius. It is an instructive exercise to name these moments in history where an independent dimension was added to human thought. Some examples in math would be the invention of a number, and in politics could be the idea of democracy. By contrast, LLMs are trapped in the vector space they are trained on, and they lack the feedback loop with sensory experience to be able to create and validate theories.

[1] https://philsci-archive.pitt.edu/28024/1/Scientific_Inventio...

[psadri]

I don’t think we have spent enough time on the creativity axis.

When we solve problems we usually follow a heuristically guided energy efficient path. We just prune a lot of possibilities based on our existing knowledge and experience.

Creativity happens when we consciously (or not) go off the beaten path and explore. Most of those explorations are dead ends. But some will yield unexpected connections, patterns etc that we call “creativity” .

An AI system could also go on those kinds of explorations. Today they aren’t it because we are not asking them to.

[mym1990]

Machine learning systems do have a component of exploring suboptimal path, otherwise they would never get off a singular track. The creativity issue in regards to AI is not about taking unexplored paths, but doing so in a computationally efficient manner when there are infinite combinations of ideas between domains.

[psadri]

Sure. But I think they can do it more exhaustively than humanly possible.

[ianm218]

> LLMs are permanently trapped in the vector space they are trained on.

A lot of the time people state the kind of fundamental limitations of LLMs very confidently when it feels like it is too early for people to really know. Like we are already well past the point where where LLMs are just pre trains on the internet with some RLHF for chatbot… Most of the effort is spent on elaborate reinforcement learning.

Is it unconceivable that future generations of LLMs could be RL’d to use einsteins visual method for theories [1] with the right tooling and geometry representations? Or just something random like that.

[1]. https://www.visualscribing.com/blog/2019-11-11-einstein-on-v...

[skybrian]

That paper argues that an LLM “lacks the mechanism for Abduction,” which is not the same thing as a claim that “creativity cannot be automated.” They propose a different kind of AI:

> The emergence of physically consistent World Models offers a pathway to a synthetic laboratory. By enabling agents to run counterfactual simulations—to experience the physical consequences of a thought experiment—we may finally mechanize the feedback loop between intuition and logic.

[vatsachak]

Creativity can be automated. Humans are automated creativity invented by evolution