21–30 of 53 posts
When my college frets that ChatGPT writes better than our B students, there are various reactions. So I had to see. I signed up for ChatGTP-3.5 and asked it "How can artificial intelligence revolutionise science?"
Huh. It didn't simply plagiarize The Economist. It gave a better answer I found easier to read.
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 collabo…
> This sounds basically of just asking a GPT to suggest ideas for experiments? I think actually the second idea extends quite a bit further than that. The idea is that you enable the agent to interact with an entire collection of laboratory equipment through tool-use. The agent not only generates hypotheses and designs experiments to test them, but then also actually executes the experiments through tool-use and iter…
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 collabo…
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 collabo…
Game developers should be hired to make an UI that allows scientists to accept “quests” and will show the public who accepted what and is collaborating with who on which problems with rankings. The reason to use game is to make it more engaging for everyone and also an incentive to go thru with it when in public
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 collabo…
This matches what I was told earlier this year when looking into what LLMs could do. I work in public health, and asked staff from a large registry what they'd like to me try. I expected something like generating reports from aggregate data (with some of that automatic exploration mentioned in the article). What they really wanted was:
1. A nice chat bot to answer questions from data submitters about reporting policies.
2. A tool to ingest federal grant announcements and filter down to those the registry could apply for.
#1 is useful because that's a lot of their job. Getting people to send accurate data in the correct format on time is exhausting. #2 helps with everything, because it could mean hiring an additional staff member. That extra person can write reports and apply for grants, clean data, answer calls, and cover when somebody's out sick. Humans are still really useful.
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 collabo…
This is half a real insight and half total bullshit. Honestly, what we need robotics and AI for in laboratory science is just old-fashioned standardization and labor-saving.
Earlier quoted context omitted.
Game developers should be hired to make an UI that allows scientists to accept “quests” and will show the public who accepted what and is collaborating with who on which problems with rankings. The reason to use game is to make it more engaging for everyone and also an incentive to go thru with it when in public
I'm now getting an idea for a dystopian cyberpunk novel about a world in which everyone is addicted to an awesome game that they think they are obsessed with that provides gift cards and credits that allow you to purchase real things, but it turns out it's all actually secretly controlled by a massive shadow government/corporation and everything everyone thinks they are doing in the "game" is actually having massive…
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 collabo…
Schmidhuber literally says that his goal is to "create an automatic scientist and then retire."
All he does is write fantastical reviews to grind an axe and harass speakers at conferences.
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 collabo…
Both things sound like massive false positive generators when used at scale. Also, where do those robots come from that can do all these experiments beyond "trivial" setups? The "robot scientists" sound very sci-fi outside of standardized high volume automation.
I see nothing in today's 'deep AI' that addresses these desiderata. And I don't see the current AI strategy of accumulating only existing knowledge as the means to those ends either. Optimization of learning can only learn more facts or do it faster, not think with more creativity or innovation. Memory is but a small part of genius.