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Artificial intelligence can revolutionise science

economist.com

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Re: Artificial intelligence can revolutionise science

#4

Post by soperj »

> It can identify promising candidates for analysis, such as molecules with particular properties in drug discovery, or materials with the characteristics needed in batteries or solar cells. It can sift through piles of data such as those produced by particle colliders or robotic telescopes, looking for patterns. And AI can model and analyse even more complex systems, such as the folding of proteins and the formation of galaxies. AI tools have been used to identify new antibiotics, reveal the Higgs boson and spot regional accents in wolves, among other things.

Wonder how much AI is actually doing here, and how much it's just paper hype, in the same way that AI companies have been shown to actually just use human resources (until they figured out the AI part ;]), I wonder how much these were just to juice up the paper a little bit.

Re: Artificial intelligence can revolutionise science

#8

Post by kurthr »

seydor wrote: post #3

... and take it private. In the end, the role of scientist itself is being put in question

Just remember you privatize the profits, and socialize the losses!

The costs (drug research and healthcare) should be born by by the public without negotiation, while the profits (drug pricing and patents) should be monopolized.

Re: Artificial intelligence can revolutionise science

#9

Post by gustavus »

Here's the heart of how they say it can be done

> Two areas in particular look promising. The first is “literature-based discovery” (LBD), which involves analysing existing scientific literature, using ChatGPT-style language analysis, to look for new hypotheses, connections or ideas that humans may have missed. LBD is showing promise in identifying new experiments to try—and even suggesting potential research collaborators. This could stimulate interdisciplinary work and foster innovation at the boundaries between fields. LBD systems can also identify “blind spots” in a given field, and even predict future discoveries and who will make them.

I have to question to the value of looking over existing papers given the current replication crises, is using an LLM to review existing papers just going to enable us to do more bad science faster? Does that do anything for us?

> The second area is “robot scientists”, also known as “self-driving labs”. These are robotic systems that use AI to form new hypotheses, based on analysis of existing data and literature, and then test those hypotheses by performing hundreds or thousands of experiments, in fields including systems biology and materials science. Unlike human scientists, robots are less attached to previous results, less driven by bias—and, crucially, easy to replicate. They could scale up experimental research, develop unexpected theories and explore avenues that human investigators might not have considered.

This sounds basically of just asking a GPT to suggest ideas for experiments?

Honestly based on what I understand of science right now the biggest way generative AI could help advanced things is by assisting in the writing of grant applications faster.

EDIT: Relevant XKCD https://xkcd.com/2341/

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