[HN Gopher] Language agents achieve superhuman synthesis of scie...
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Language agents achieve superhuman synthesis of scientific
knowledge
Author : rntn
Score : 38 points
Date : 2024-11-14 19:46 UTC (3 hours ago)
(HTM) web link (arxiv.org)
(TXT) w3m dump (arxiv.org)
| therobot24 wrote:
| i only performed a quick read of the paper but couldn't find how
| many humans they used to generate their expected human
| performance, this seems to be the main content:
|
| > To ensure that we did not overfit PaperQA2 to achieve high
| performance on LitQA2, we generated a new set of 101 LitQA2
| questions after making most of the engineering changes to
| PaperQA2. The accuracy of PaperQA2 on the original set of 147
| questions did not differ significantly from its accuracy on the
| latter set of 101 questions, indicating that our optimizations in
| the first stage generalized well to new and unseen LitQA2
| questions (Table 2).
|
| > To compare PaperQA2 performance to human performance on the
| same task, human annotators who either possessed a PhD in biology
| or a related science, or who were enrolled in a PhD program (see
| Section 8.2.1), were each provided a subset of LitQA2 questions
| and a performance-related financial incentive of $3-12 per
| question to answer as many questions correctly as possible within
| approximately one week, using any online tools and paper access
| provided by their institutions. Under these conditions, human
| annotators achieved 73.8% +- 9.6% (mean +- SD, n = 9) precision
| on LitQA2 and 67.7% +- 11.9% (mean +- SD, n = 9) accuracy (Figure
| 2A, green line). PaperQA2 thus achieved superhuman precision on
| this task (t(8.6) = 3.49, p = 0.0036) and did not differ
| significantly from humans in accuracy (t(8.5) = -0.42, p = 0.66).
| PaulKeeble wrote:
| One of my big uses of LLM's has been searching through medical
| research. The issue has been a few times running into confidence
| where it shouldn't be but I have found it hallucinates a lot less
| in science topics than it does for more common topics.
| mdp2021 wrote:
| > _hallucinates a lot less in science topics_
|
| Extremely dangerous for that one detail you will not expect
| also since hallucination becomes more rare; extremely dangerous
| in the hands of practitioners non paranoid in front of
| hallucination.
|
| (Incidentally: apparently, somebody recently lost a house after
| having some chatbot write the contract. This is indicative of
| the possible level of carelessness of users.
|
| Edit: I am trying to find that piece of news, but it seems non
| trivial. Maybe the original reference itself, which reported
| the news, was victim of hallucination? Meanwhile, I have found
| this noteworthy piece: _firm allows people to have contractual
| terms presented by chatbot, which presents hallucinated terms,
| and loses legal action_ - https://mashable.com/article/air-
| canada-forced-to-refund-aft... )
| tantalor wrote:
| I have an idea how to test whether AI can be a good scientist:
|
| Train on all published scientific knowledge and observations up
| to certain point, before a breakthrough occurred. Then see if
| your AI can generate the breakthrough on its own.
|
| For example, prior to 1900 quantum theory did not exist. Given
| what we knew then, could AI reproduce the ideas of Planck,
| Einstein, Bohr etc?
|
| If not, then AI will never be useful for generating scientific
| theory.
| polishdude20 wrote:
| Or just have the AI generate new specific experimental setups
| and parameters that we can try and be like "oh yeah, we just
| made a room temperature superconductor".
|
| Honestly given what we know about physics, the AI should be
| able to simulate physics within itself or deduce certain things
| we've missed.
| AnimalMuppet wrote:
| > Honestly given what we know about physics, the AI should be
| able to simulate physics within itself or deduce certain
| things we've missed.
|
| If by "AI" you mean language models, then no, it will _not_
| "be able to simulate physics within itself". No way.
| polishdude20 wrote:
| Oh no I mean if we claim we have an AGI and it's true, it
| should be able to do that. LLMs are not that
| potatoman22 wrote:
| It can simulate basic problems well enough when viewed as a
| black box. Give it one of Galileo's experiments.
| tiahura wrote:
| Discover quantum mechanics or you're a failure!
|
| I hope your approach with your kids is a bit more nuanced.
| tasty_freeze wrote:
| Is your second sentence sincere? Attacking someone's
| parenting to win rhetorical points on an unrelated topic is
| pretty low.
| vzaliva wrote:
| I don't think this is the main point of the paper. They're not
| claiming that AI is capable of scientific breakthroughs.
| Rather, they argue that AI excels at summarising vast amounts
| of existing scientific knowledge.
| tantalor wrote:
| That's literally what "knowledge synthesis" is. Not just
| summarizing, but "the combination of ideas to form a theory
| or system."
|
| Breakthroughs are just a special case of synthesis.
| wslh wrote:
| Formally speaking, breakthroughs are not simply a subset of
| synthesis, as they can exist outside the realm of prior
| knowledge.
| dcreater wrote:
| Academic writing is notoriously hard to read and often poorly
| written. If this lives up to billing it will be a game changer -
| no need to rely on sporadic, manual, intrinsically limited nature
| of surveys from academics, analysts through to gym bros, reddit
| posters.
| handfuloflight wrote:
| Github: https://github.com/Future-House/paper-qa
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