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We live in a golden age of biology. So why are people still dying from disease?
Because discovery and development move slower than they should.
Today, we’re partnering with Incyte to change that.
Kosmos is now the first agent that can compress months of drug development into t stages of scientific discovery through to FDA approval. @Incyte will be the first company to deploy it across their pipeline.
Work that used to take a team of scientists months now happens in weeks.
Patients can't wait, and neither can we.
Because discovery and development move slower than they should.
Today, we’re partnering with Incyte to change that.
Kosmos is now the first agent that can compress months of drug development into t stages of scientific discovery through to FDA approval. @Incyte will be the first company to deploy it across their pipeline.
Work that used to take a team of scientists months now happens in weeks.
Patients can't wait, and neither can we.
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Sam Rodriques retweeted
In 5 years, will the success rate of Phase II clinical trials be higher, lower, or the same as it is today?
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The hard part about AI in bio is that by the time you can test the predictions from model X, you already have better predictions from model X+2 or X+3.
god these two charts really hurt my soul
64 hours to dry lab design an multi-binding antivenom and 39 days for results and 4-7 years to release
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This is nonsense. Success in verticals is about more than just intelligence. It depends on also having relationships, supply chains, and assets (e.g. data). These are hard to build. The labs cannot magic these out of thin air, and the people who have them don’t want to sell.
If the labs want to capture the value generated by AI in verticals, they need to partner with existing players, get their hands dirty, and generate value through integration. But there is a not a lot of evidence that they are doing this, or at least not well.
Otherwise, the fundamental problem is that the labs have to bear the cost of training models, and unless you do the hard work of integration, the cost of training the marginal model right now is greater than the value provided by the marginal unit of intelligence. And as soon as they stop training models, everyone else catches up.
Most of the chatter on X right now is that the labs are doomed. I think that is not the case. But their next big challenge is to operationalize the integration of AI into the economy. It is hard and slow.
x.com/eriknewsha/sta…
If the labs want to capture the value generated by AI in verticals, they need to partner with existing players, get their hands dirty, and generate value through integration. But there is a not a lot of evidence that they are doing this, or at least not well.
Otherwise, the fundamental problem is that the labs have to bear the cost of training models, and unless you do the hard work of integration, the cost of training the marginal model right now is greater than the value provided by the marginal unit of intelligence. And as soon as they stop training models, everyone else catches up.
Most of the chatter on X right now is that the labs are doomed. I think that is not the case. But their next big challenge is to operationalize the integration of AI into the economy. It is hard and slow.
x.com/eriknewsha/sta…
by this time next year, most of labs revenue will come from what they build in-house and then sell further up the stack. the average users just don't
1. have deep enough pockets
2. work on hard enough tasks
gpt-synopsys and anthropic wet lab are the first of many products which come as a result of labs gatekeeping and utilizing superintelligent swarms to create new and capture existing markets. currently by use of footholds and in the future independently. by 2030 labs will have eaten practically every economically valuable sector such as finance, legal and healthcare.
what's to stop labs? why wouldn't they? how can a 10,000 employee healthcare company stand a chance if they are up against 10 million vastly superior agents to the swarms publicly available?
the labs understand this and are hence preparing for the "grand capture" by donating shares to the public (anthropic and spacexai already committed with openai about to) to minimize p(public revolution).
the question becomes what to do. one option is obviously to join a lab. if you want to join the lab I believe the best "unit chance of joining lab/time" ratio is proving scaleable user acquisitions and publishing relevant hot topic things on X.
if you don't want to join a lab, acquiring factories, propietary data, licenses, land and things that are human facing and exist in a stack of value creation will be fruitful as they become the primary bottlenecks once suffcient swarm cognition is solved
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This is similar to what we see. On some tasks, there are still major returns on intelligence. However, for the large majority of tasks, we are either close to saturation or are already at saturation. Once intelligence saturates, tacit knowledge, data, supply chains, and operational ability become the bottlenecks.
x.com/theinformation…
x.com/theinformation…
OpenAI, Anthropic and other leading AI labs face a growing challenge: Better models aren't necessarily attracting more usage. A 10-point intelligence advantage now earns just 20% more developer traffic, down from nearly 69% in late 2025.
Full story: thein.fo/4hGJ9jY
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Sam Rodriques retweeted
Come help me make a planet 🙃🚀🌎
We're hiring two scientists to do experiments that nobody has ever tried before.
APPLY: pioneer-labs.org/team
Priority deadline October 31 🎃
TELL YOUR FRIENDS
We're hiring two scientists to do experiments that nobody has ever tried before.
APPLY: pioneer-labs.org/team
Priority deadline October 31 🎃
TELL YOUR FRIENDS
We're hiring two scientists to help engineer life for Mars 🦠🚀
🔧 Mars Simulation Systems: Build unusual experimental apparatus to test life under Martian conditions.
🧪 Materials: Develop and characterize biologically produced materials.
⏱ Priority deadline October 31; applications close November 14.
Apply: pioneer-labs.org/team
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OpenAI's models refuse to support the development of pandemic countermeasures. This needs to be fixed.
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Sam Rodriques retweeted
WHERE'S ED BOYDEN?
Oh. He was only a PhD student when he co-invented optogenetics and performed the first demonstration, so he gets no credit. Instead his advisor gets all the credit.
From National Academy of Sciences: Boyden, "in parallel to his PhD, as an independent side project, co-invented optogenetic control of neurons."
One of the worst snubs in Nobel history IMO!
Oh. He was only a PhD student when he co-invented optogenetics and performed the first demonstration, so he gets no credit. Instead his advisor gets all the credit.
From National Academy of Sciences: Boyden, "in parallel to his PhD, as an independent side project, co-invented optogenetic control of neurons."
One of the worst snubs in Nobel history IMO!
BREAKING NEWS
The 2026 #NobelPrize in Physiology or Medicine has been awarded to Karl Deisseroth, Peter Hegemann and Georg Nagel “for their discoveries concerning light-gated ion channels and optogenetics.”
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Without diminishing the contributions of Peter, Georg, or Karl, I find the omission of Ed Boyden from the optogenetics prize to be highly unreasonable.
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Sam Rodriques retweeted
I joined OpenEvidence!
At Anthropic, I created Claude Science, a product built so that scientists' curiosity, not their capacity to execute, sets the limit on what they can discover. It takes on the heavy lifting across the early stages of the discovery and translational pipeline and scales what a single researcher can carry out. Building Claude Science has been the most fulfilling work of my career so far.
Now I'm excited to help build the future of AI in medicine at OpenEvidence, bringing that same leverage to doctors at the point of care. OpenEvidence already reaches the majority of patients in America. It doesn't get more translational than that.
At Anthropic, I created Claude Science, a product built so that scientists' curiosity, not their capacity to execute, sets the limit on what they can discover. It takes on the heavy lifting across the early stages of the discovery and translational pipeline and scales what a single researcher can carry out. Building Claude Science has been the most fulfilling work of my career so far.
Now I'm excited to help build the future of AI in medicine at OpenEvidence, bringing that same leverage to doctors at the point of care. OpenEvidence already reaches the majority of patients in America. It doesn't get more translational than that.
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The Economist published an article yesterday calling for regulations to protect against mirror life. They propose restrictions on buying mirror chemicals, including extremely normal stuff like L-Glucose or D-amino acids. What is going on, guys? Where did this come from? I think the concerns about AI designing pandemics are overblown, but at least designing viruses is a real thing that we actually know how to do.
1. To be clear: we do not have any idea today how to make an autonomous cell from scratch, mirror or not. Making a mirror cell from scratch is much, much harder than making a non-mirror cell from scratch. I am a believer in strong AI acceleration but there is a lot of hard science and manufacturing that is missing here. People have ideas about how to do it, but they have ideas in the same way we have ideas about quantum computing: we will have lots of hints that it's around the corner before you see in on a shelf at walmart! Call me when we create an autonomous non-mirror cell in the lab from scratch, and then we can chat about sensible regulations.
2. Even if they existed, mirror bacteria wouldn't be able to escape the lab: they couldn't eat anything. Good luck being a left handed organism in a world where all the food is right handed. I know, a malicious person with access to mirror life could in principle give the mirror organism a way to digest non-mirror food, and then it could wreak havoc. But the converse is also possible: if a mirror bacterium were on the loose we could just give the normal non-mirror bacteria enzymes that would allow them to eat the mirror bacteria, and drive competition. This fact is generally ignored.
3. Finally, mirror life doomers pretend we have no defense against mirror life. This is also just nonsense. We have plenty of defenses. They are called mirror antibiotics. Mirror antibiotics would work against mirror life the exact same way non-mirror antibiotics work against non-mirror life. And there are way more options for mirror antibiotics than there are for non-mirror antibiotics, because we don’t have to worry about accidentally killing the human in the process! We actually even already have a ton of mirror antibiotics, since they are usually byproducts of antibiotic manufacturing. Fosfomycin, for example, is extremely simple, easy to manufacture in bulk, and industrial quantities of mirror fosfomycin are already produced today as a byproduct of fosfomycin synthesis. D amino acid analogs, like D-cycloserine, would also be very effective. If we can figure out how to make mirror life we can definitely figure out a bunch of universal mirror antibiotics to kill it.
Spare a thought for the poor scientists studying chiral biochemistry. Their requests to the models are all about to be denied as potentially dual risk. Meanwhile, want help finding a supplier for a toxin with nanogram LD-50? Sure, Claude will help you with that.
I agree mirror life escaping the lab would be bad and it deserves consideration, but can we stop pretending that it is a huge danger right around the corner that deserves front page regulatory attention, and instead focus on real shit like AI cyberattacks and the fact that the poles are still literally melting?
1. To be clear: we do not have any idea today how to make an autonomous cell from scratch, mirror or not. Making a mirror cell from scratch is much, much harder than making a non-mirror cell from scratch. I am a believer in strong AI acceleration but there is a lot of hard science and manufacturing that is missing here. People have ideas about how to do it, but they have ideas in the same way we have ideas about quantum computing: we will have lots of hints that it's around the corner before you see in on a shelf at walmart! Call me when we create an autonomous non-mirror cell in the lab from scratch, and then we can chat about sensible regulations.
2. Even if they existed, mirror bacteria wouldn't be able to escape the lab: they couldn't eat anything. Good luck being a left handed organism in a world where all the food is right handed. I know, a malicious person with access to mirror life could in principle give the mirror organism a way to digest non-mirror food, and then it could wreak havoc. But the converse is also possible: if a mirror bacterium were on the loose we could just give the normal non-mirror bacteria enzymes that would allow them to eat the mirror bacteria, and drive competition. This fact is generally ignored.
3. Finally, mirror life doomers pretend we have no defense against mirror life. This is also just nonsense. We have plenty of defenses. They are called mirror antibiotics. Mirror antibiotics would work against mirror life the exact same way non-mirror antibiotics work against non-mirror life. And there are way more options for mirror antibiotics than there are for non-mirror antibiotics, because we don’t have to worry about accidentally killing the human in the process! We actually even already have a ton of mirror antibiotics, since they are usually byproducts of antibiotic manufacturing. Fosfomycin, for example, is extremely simple, easy to manufacture in bulk, and industrial quantities of mirror fosfomycin are already produced today as a byproduct of fosfomycin synthesis. D amino acid analogs, like D-cycloserine, would also be very effective. If we can figure out how to make mirror life we can definitely figure out a bunch of universal mirror antibiotics to kill it.
Spare a thought for the poor scientists studying chiral biochemistry. Their requests to the models are all about to be denied as potentially dual risk. Meanwhile, want help finding a supplier for a toxin with nanogram LD-50? Sure, Claude will help you with that.
I agree mirror life escaping the lab would be bad and it deserves consideration, but can we stop pretending that it is a huge danger right around the corner that deserves front page regulatory attention, and instead focus on real shit like AI cyberattacks and the fact that the poles are still literally melting?
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Matt is a powerhouse. We are super excited to have him on board.
Personal update: This week, I joined @EdisonSci , focused on building new partnerships across biopharma.
It’s bittersweet to be stepping back from the team at @ferment_co , who I've worked with for the past six years. We’ve accomplished a lot since launching Ferment, including raising our first fund and building seven new industrial biotech companies at the intersection of biology, hardware, and computation.
I’m a deep believer that AI and agentic science will drive extraordinary progress in human health. I’m an even deeper believer that this impact will only come when we put these tools in the hands of drug hunters who know which problems matter and where to point them.
That’s a big part of what drew me to Edison. The team pairs enormous ambition about what AI can do for science with an extremely practical lens on what must be true for the technology to actually be useful, both for our individual scientist users and for the scaled biopharma organizations they work within.
I’m excited to be an AI arms dealer for drug hunters everywhere. If you’re thinking about how to bring cutting-edge, sovereign AI into your biopharma organization or have ideas on how agentic science can accelerate drug development, don’t hesitate to say hello!
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Major extinction risk here. Within 3 years most women will have AI boyfriends and then there will be no more babies.
Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
It’s the first Human Interaction Model (HIM).Community noteThe 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-gri…
research.nvidia.com/labs/amri/proj…
tech-ish.com/2026/10/02/tav…
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Okay I don’t say this about much, but definitely agree that use of this thing needs to be heavily regulated.
Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
It’s the first Human Interaction Model (HIM).Community noteThe 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-gri…
research.nvidia.com/labs/amri/proj…
tech-ish.com/2026/10/02/tav…
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Sam Rodriques retweeted
This looks great. Time spent on filing INDs is extremely precious and should be saved.
Writing an Investigational New Drug (IND) application is a major hurdle for drug developers. It can take a team of specialists three to four months, and mistakes can trigger protocol amendments or clinical holds.
In June, we started working with Population Health Partners (PHP) Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
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Sam Rodriques retweeted
Writing an Investigational New Drug (IND) application is a major hurdle for drug developers. It can take a team of specialists three to four months, and mistakes can trigger protocol amendments or clinical holds.
In June, we started working with Population Health Partners (PHP) Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
In June, we started working with Population Health Partners (PHP) Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
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At FutureHouse, we focused on scientific discovery. However, if we want to actually accelerate progress in medicine, we need to work across the entire R&D stack. We are now deploying specialized Kosmos agents for Clinical Protocol Design and Regulatory Authoring to several of our partners, which can cut months off the amount of time needed to get molecules into the clinic, save companies tens of millions of dollars, and dramatically reduce the likelihood that submissions get stuck at the FDA. Super excited to be able to share this story now, thanks to our work with Population Health Partners, one of the best drug developers in the world and a fantastic development partner for us.
The AI-native pharma stack is here now, and the future of medicine is around the corner. Read more:
x.com/EdisonSci/stat…
The AI-native pharma stack is here now, and the future of medicine is around the corner. Read more:
x.com/EdisonSci/stat…
Writing an Investigational New Drug (IND) application is a major hurdle for drug developers. It can take a team of specialists three to four months, and mistakes can trigger protocol amendments or clinical holds.
In June, we started working with Population Health Partners (PHP) Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
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This is very good
@ID_AA_Carmackou we have already been working on revisions to the planetary protection policies to bring them back in line with the common-sense principles originally established by COSPAR in the early days of planetary exploration and later reflected in Article IX of the Outer Space Treaty. We are needlessly adding extreme cost and time to robotic missions to Mars when the overarching goal is to send astronauts there as quickly and safely as possible.
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Sam Rodriques retweeted
@ID_AA_Carmackou we have already been working on revisions to the planetary protection policies to bring them back in line with the common-sense principles originally established by COSPAR in the early days of planetary exploration and later reflected in Article IX of the Outer Space Treaty. We are needlessly adding extreme cost and time to robotic missions to Mars when the overarching goal is to send astronauts there as quickly and safely as possible.
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