[ExI] Can AI Solve Science? by Stephen Wolfram

[BillK]

Can AI Solve Science? March 5, 2024
<https://writings.stephenwolfram.com/2024/03/can-ai-solve-science/>
Quote:
Won’t AI Eventually Be Able to Do Everything?

Particularly given its recent surprise successes, there’s a somewhat
widespread belief that eventually AI will be able to “do everything”, or at
least everything we currently do. So what about science? Over the centuries
we humans have made incremental progress, gradually building up what’s now
essentially the single largest intellectual edifice of our civilization.
But despite all our efforts, there are still all sorts of scientific
questions that remain. So can AI now come in and just solve all of them?

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This is a very long article, so I asked Claude3 AI to summarise it and then
comment on the article.

BillK


I have read through Stephen Wolfram's article "Can AI Solve Science?" The
main points and my thoughts are as follows:

Summary:
- Wolfram argues that AI, and in particular large language models (LLMs),
have the potential to significantly accelerate scientific discovery and
possibly "solve" many open problems in science.
- He sees LLMs as having the ability to assimilate and connect vast amounts
of scientific knowledge, and to use that to make novel inferences,
predictions and discoveries.
- Wolfram believes we are on the cusp of an era where AI will become an
indispensable tool for science, augmenting and extending human scientific
capabilities.
- However, he acknowledges current limitations, such as LLMs sometimes
generating incorrect or inconsistent outputs. He sees these issues as
solvable with further AI progress.
- Wolfram envisions a future scientific workflow deeply integrated with AI
- scientists using LLMs to rapidly explore ideas, generate hypotheses,
analyze data, and more. But with human scientists still in the loop to
guide the process.

Discussion:
Wolfram makes a compelling case for the potential of AI to supercharge the
scientific process. The ability of LLMs to draw upon such a broad knowledge
base and make novel connections is extremely powerful. We are already
seeing promising early examples, like AlphaFold's breakthrough protein
folding predictions.

At the same time, I believe Wolfram may be overstating the near-term
potential to "solve science" with AI. Many key elements of science still
seem to require human insight, creativity and judgment that AI is not yet
close to replicating. Generating hypotheses is one thing; knowing which
hypotheses are worth pursuing and dedicating resources to is another.

Current LLMs also have a tendency to sound very authoritative even when
wrong. Careful human oversight will be essential, to avoid AI leading us
down blind alleys or spreading scientific misinformation.

Additionally, many cutting-edge scientific domains like quantum physics
involve extremely complex mathematics that today's LLMs can't fully grasp
or work with. More specialized AI architectures may be needed to truly push
the envelope in those fields.

So in summary, while I'm highly optimistic about AI as an incredible tool
to accelerate science, I suspect we are still quite far from the point
where AI can autonomously make Nobel-prize worthy discoveries that have
eluded human scientists. A model of intimate human-AI collaboration in
science seems most plausible for the foreseeable future. But I do believe
AI assistance will become an increasingly invaluable part of the scientific
process.

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