All the encouragement one needs to work in AI:
AI researchers seek to understand intelligence well enough to create beings of greater intelligence than current humans.
Reaching this profound intellectual milestone will enrich our economies and challenge our societal institutions. It will be unprecedented and transformational, but also a continuation of trends that are thousands of years old.
People have always created tools and been changed by them; this is what humans do.
The next big step is to understand ourselves.
This is a quest grand and glorious, and quintessentially human.
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We‘ll never ‘solve’ biology for the same reason quantum uncertainty retired Laplace’s demon.
What we will do is improve our theories-of-biology. Our models will increasingly reflect the patterns of life, hopefully toward useful new bioengineering and drug discovery tools.
What we will do is improve our theories-of-biology. Our models will increasingly reflect the patterns of life, hopefully toward useful new bioengineering and drug discovery tools.
Each of the 400k particles is a unique, untrained, randomly mutated ~10k param neural net btw 🤗
🔊🦠 Neural-Kimchi-4B 🔊🦠
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“An approach we call distributed biological reasoning.”
Slowly but surely, AI is absorbing the shared intuition of the world’s great biologists.
We won’t *just* get valuable new findings from existing bio data — we’ll also begin to more deeply understand how to make highly effective *new* bio data.
So exciting!
Slowly but surely, AI is absorbing the shared intuition of the world’s great biologists.
We won’t *just* get valuable new findings from existing bio data — we’ll also begin to more deeply understand how to make highly effective *new* bio data.
So exciting!
GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration?
DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in making cholesterol. GPT-Rosalind suggested a possible explanation: cholesterol may not be reaching where neurons need it.
That gives scientists a specific mechanism to test and, if confirmed, a direction for developing new treatments for neurodegenerative disorders.
With @perturbai_tx and @scrippsresearch, a team of thousands of GPT-Rosalind agents worked in parallel, connecting gene-expression results from millions of mouse brain cells with scientific literature in just 32 minutes. We’re now expanding this collaboration to identify new drug targets.
openai.com/index/scaling-…
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Our team just minted a 1-million-cell drug-response dataset.. in zebrafish.
I'll be in San Francisco Monday, Tuesday and Wednesday this week.
I'd love to meet AI folks interested in modeling biology.
DMs open
I'll be in San Francisco Monday, Tuesday and Wednesday this week.
I'd love to meet AI folks interested in modeling biology.
DMs open
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Well articulated 🫡
Building toward a true 'bio-generalization' North Star is what gets people excited.
Recalibrating expectations toward mini-generalization wins along the way is the road to effective progress. Ideally, we can balance hype with bite-sized utility year-by-year
Building toward a true 'bio-generalization' North Star is what gets people excited.
Recalibrating expectations toward mini-generalization wins along the way is the road to effective progress. Ideally, we can balance hype with bite-sized utility year-by-year
We need to continue to be honest about what our models are actually capable of and where they fail so we keep moving forward. Less hype & blind faith in parameters & arbitrary scaling. More evidence based strategies & honest reflection. 6/6
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Yeah!
As I've begun to develop an intuition on the limits of AI, I've had to incorporate concepts as far out as the philosophy of knowledge, as 'practical' as brain surgery, and as basic as statistics.
As I've begun to develop an intuition on the limits of AI, I've had to incorporate concepts as far out as the philosophy of knowledge, as 'practical' as brain surgery, and as basic as statistics.
Hot take: machine learning and AI did more to understand the nature of knowledge, and our relation to reality than 20 centuries of philosophy.
I am ready to kind of defend this hill.
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I bet we’re going to discover many very useful abstractions on the long road to ‘full AI’ understanding.
Some of biology’s most reliable, important patterns won’t require atom-by-atom reconstruction to be effectively learned.
Some of biology’s most reliable, important patterns won’t require atom-by-atom reconstruction to be effectively learned.
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If you enjoyed reading Isaac Asimov's robot stories, I guarantee section 7 of the Claude Mythos Model Card will tantalize you.
It reads like Dr. Susan Calvin -- Asimov's fictional 'chief robopsychologist' -- dissecting the mind of yet another robot gone awry.
It reads like Dr. Susan Calvin -- Asimov's fictional 'chief robopsychologist' -- dissecting the mind of yet another robot gone awry.
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couldn't agree more.
1. human relationships
2. artistic creation
3. scientific exploration
these three will remain the most engaging, meaningful categories of human activity post-ASI (i think..)
1. human relationships
2. artistic creation
3. scientific exploration
these three will remain the most engaging, meaningful categories of human activity post-ASI (i think..)
I think most people should consider becoming scientists.
While there is a real risk AI will eliminate jobs, conversely the need for models to understand the world around us through more and better data will increase exponentially.
AlphaFold, for example, would not have been work of thousands of grad students and postdocs painstakingly depositing well-curated datasets over decades of meticulous experimental work.
We still only understand a fraction of the physical world and beyond, and we’ll only be able to do so if we collect more data and put it into context.
Maybe this is a bit naive or utopian thinking, but humans are not designed to look through pages of receipts, read 100-page legal documents, or write reports and POCs no one will ever read. They are wired to explore, driven by curiosity, and have an innate desire to understand the world.
Many who are bored or feel a lack of purpose -- with the overhanging (and maybe exaggerated) doom and gloom of AI replacement -- should think about this.
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More intelligent models should not only be capable of producing simulations like these, they should also be capable of evolving the environments and variables themselves toward undiscovered categories of useful new patterns.
"artificial interestingness selection"
"artificial interestingness selection"
the secret life of boids
using gemini 3 flash to simulate simple rules that lead to emergent behaviours (attraction, repulsion, cohesion)
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Science fiction is science vision.
The very first short story in I, Robot is about a young girl’s heartache after being separated from her loving robot..
Surreal to see it happen for real this year:
The very first short story in I, Robot is about a young girl’s heartache after being separated from her loving robot..
Surreal to see it happen for real this year:
A Chinese father's video of his daughter tearfully saying goodbye to her broken Al learning robot.
People already get emotionally attached to AI. Now imagine Figure03 at home and it breaks, people will have a breakdown.
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Very lucky to have been invited - @1517fund fuels the spirit of young scientific/technological pioneers better than any other. 🌲🏕️
Kudos
Kudos
1517 Unplugged was a hit! Founders, community members, teens, LPs -- can't wait to host again next year.
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In SF this week.
I’ve closed a pre-seed.
Would love to chat with bio foundation modellers.
Any leads?
I’ve closed a pre-seed.
Would love to chat with bio foundation modellers.
Any leads?
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Anyone from @cziscience or @arcinstitute would be amazing to chat with.
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