There are bound to be a bunch more results like this, in math, physics, chemistry, and now that we essentially have a DeepBlue for math, a DeepBlue for physics, etc, these results are going to come.
SOME of the problems that have eluded humans are going to turn out to be low hanging fruit that are susceptible to this type of brute force (10,000 agents on a supercomputer running for 7*24 hours straight) AI search.
I'd be more impressed if OpenAI found their own problems to solve, rather than rushing in to re-solve one once they heard it was already solved (and therefore not so hard).
This article claims only 3 of the new materials were actually snythesizable (and all had been previously known of), and that the drug for liver fibrosis had already been investigated for liver fibrosis.
The snythesizable materials is another paper by deepmind not relying on LLMs and unrelated to this one. The article's author briefly mentions one of the other two findings without providing any sources to support the claim that they aren’t novel/useful?
If it helps scientists find answers faster, I don’t see the problem—especially when the alternative is sifting through Google or endless research papers.
Such a bad take. Consider examples like AlphaFold, which has revolutionized protein folding and is already having a profound impact on scientific research and healthcare. AI’s potential extends far beyond being compared to a 90s MS Office suite it has profound, wide-ranging implications for society.
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