Stirling Churchman retweeted
I’ve built DNA synthesizers and sequencers by hand. I used the engineer viruses for a living. I used to engineer human immune evasion for therapeutic constructs. Who the fuck are you people? Have you ever so much as held a pipette before?
You can spaghetti blast an ensemble of DNA sequences at some shitty provider but 1) you still have to assemble it and bootstrap a system for making virions 2) you are not single shotting a viable, virulent viral design without a ton of experimental selection and development. Viral fitness is deeply dependent on codons and cotranslational kinetics - you’re not just gonna obfuscate away from wild type and get something good by magic.
You keep treating AI like some kinda god, but molecular physics has computational complexity that scales exponentially in particle number which just crushes the abilities of any classical computer to do end-to-end design of biological functions ab initio.
Grabbing a bunch of bacteriophage phi174 hits from a mass ensemble screen in lab microbes is not evidence of some magical AGI bio design ability - it's just a classic spray and pray selection. This is just nothing like building something viable in humans.
Goddamn it read some books before you waltz into biomedicine and lecture us on protecting human life.
Stirling Churchman retweeted
I run one of these API-driven automated biolabs at @ginkgo and @DavidRBellamy is right -- we are miles away from AI killing us with viruses being a real risk. There are many physical checkpoints you can implement easily that prevent dangerous biological work from happening.
Stirling Churchman retweeted
Of course bioweapons are dangerous but there is no biological agent stored in any lab anywhere that, if released, would mean “goodbye humans.” Unlike nuclear weapons.
From a great piece on apocalyptic AI talk by my @WashU colleague Ian Bogost:
theatlantic.com/ideas/2026/0…
Stirling Churchman retweeted
Hiring 1-2 experienced wet lab biologists in SF for a several-month contract (potentially longer). Experience with RL environments is preferred. In-person, five days a week, in Dogpatch area.
Interested —> DM with background and send a phone number. Optionally include some times of availability and ideally details of RL env work. I will give you a call if there’s potentially a good fit.
Stirling Churchman retweeted
Finishing your PhD or looking for a post-bac research position? We’re recruiting multiple postdocs and research technicians to study somatic evolution!
Come do interdisciplinary science in a friendly, collaborative environment at @harvardmed Genetics.
naxerova.hms.harvard.edu/con…
Stirling Churchman retweeted
The biotech era debuted in the 1980s, and this is the type of lab the NIH thought a single R01 could support.
Using the NIH entry-level postdoctoral stipend as a consistent benchmark, a single R01 with $250,000 in annual direct costs could theoretically pay for about 15.6 postdoc-years in 1987, when the stipend was $15,996 per year.
How about today? At the FY2026 stipend of $63,480 per year, that same $250,000 would pay for only about 3.9 postdoc-years.
This means that while a single R01 could theoretically support the equivalent of about 3 entry-level postdocs over 5 years in 1987, it could support fewer than one (one for four years) today—a roughly 75% loss in personnel purchasing power.
And, of course, this assumes that every dollar goes directly to postdoc stipends. It does not include fringe benefits, PI salary, graduate students, technicians, supplies, equipment, animals, core-facility fees, travel, publication charges, or any of the other costs required to run a modern laboratory.
Same nominal R01. Roughly one-quarter of the scientific labor.
The Simpsons debuted in 1987 and this is the type of house the shows creators thought a single-income family could afford.
According to an episode in Season 1, Homer made 25k a year(60k in 2026 dollars).
In 1987 that house would cost about 100k(which was the national average) with a mortgage of roughly $700/month(assuming 20% down and interest rates consistent with that time)
How about today? The same house would cost 450k with a mortgage of roughly $2,500/month.
This means that while Homer was spending ~30% of his income on his mortgage in 1987 he would need to spend closer to 50% of his income on his mortgage today.
And of course, this doesn't include other areas of inflation such as food, gas or etc.
Stirling Churchman retweeted
We’re giving scientists, mathematicians, and engineers free access to our frontier models—starting with 10,000 researchers and expanding to 100,000 through 2027.
ChatGPT for Academic Researchers is built to accelerate discovery across disciplines.
Stirling Churchman retweeted
So excited to share my first preprint of grad school! Check out this thread to learn more about a cool new technique we are using to learn more about hidden layers of RNA regulation! Thank you so much to my coauthors, mentors, and lab for helping us get this story up!
RNA-seq tells us how much RNA is present in the cell. But to understand gene regulation, we need to easily measure the synthesis and decay rates driving this abundance. We introduce AIR-seq: analog intrinsic recoding sequencing. (1/6) biorxiv.org/content/10.64898…
Stirling Churchman retweeted
Introducing Pantheon Fleet, building on PantheonOS, a distributed, open-source drop-in for Claude Science + GPT Rosalind.
Claude Science @claudeai GPT Rosalind @OpenAI made AI research accessible. But your data, compute, and workflows still live on someone else's platform.
Today we're launching Pantheon Fleet: one command to orchestrate every resource you own—laptop, HPC cluster, cloud GPUs, private infrastructure—privacy preserved by default.
But there are more:
Pantheon-Store: 2,300+ skills, agents, and scientific teams. Pantheon auto-picks the right ones for every task.
Pantheon-Evolve: improves ML algorithms on its own—already beating human baselines on single-cell batch correction.
Real discoveries: asymmetric gene-expression gradients in mouse embryos, congenital disease genes in the human heart.
Full stack: Web, Desktop, CLI, Jupyter, Pantheon Claw.
Your data. Your compute. Your models. Your science.
Stirling Churchman retweeted
Introducing LifeSciBench, a benchmark for measuring and improving how well AI supports real-world life science research.
Developed with 173 scientists from biotechnology and pharmaceutical research, LifeSciBench includes 750 expert-authored tasks across seven biological research workflows.
openai.com/index/introducing…
Stirling Churchman retweeted
We are thrilled to announce an opening for a tenure-track assistant professor in PCMM, Boston Children's Hospital and Harvard Immunology! Apply by August 2, 2026.
Stirling Churchman retweeted
congrats to the team, especially excited for the new medchem capabilities and performance on our new out of distribution evals! @bacchuswng @yunyunash @suyashss @davediego @edwardzhou_ @kevinrao99
We’re bringing new capabilities to GPT-Rosalind, a model series purpose-built for life sciences research at enterprise scale.
It brings GPT-5.5’s agentic coding and tool use together with stronger intelligence for drug discovery, analysis, design, and experimental workflows.
openai.com/index/introducing…
Stirling Churchman retweeted
We’re bringing new capabilities to GPT-Rosalind, a model series purpose-built for life sciences research at enterprise scale.
It brings GPT-5.5’s agentic coding and tool use together with stronger intelligence for drug discovery, analysis, design, and experimental workflows.
openai.com/index/introducing…
Stirling Churchman retweeted
Characterizing AI-designed proteins requires quantitative biochemistry at massive scale. Enter Amplicon/Protein Bead Display (APB-Display), a fully in vitro platform that quantifies Kd's for >100,000 variants in <3 days (preprint link below!) @Stanford_ChEMH @czbiohub (1/n)
Stirling Churchman retweeted
Today we report single-cell APEX-seq (scAPEX-seq) — a new method for unbiased mapping of *subcellular* transcriptomes at single-cell resolution. This approach reveals cell states that are not detectable by standard scRNA-seq, and enabled us to identify regulators of CAR T function that improve solid tumor killing.
biorxiv.org/cgi/content/shor…
Stirling Churchman retweeted
Next week, @_AndrewLeduc will present at the CSHL (@cshlmeetings) Systems Biology: Global Regulation of Gene Expression meeting.
His talk will focus on in vivo protein regulation in single cells, including results from this preprint:
biorxiv.org/content/10.1101/…
Stirling Churchman retweeted
💥 AI accelerating high energy physics
Just a few weeks after the gluon scattering paper, this morning we posted the more complicated graviton scattering analogue. See below for more from @ALupsasca 👇
We just posted a new preprint: “Single-minus graviton tree amplitudes are nonzero.”
Yes: a helicity sector long assumed to vanish in quantum gravity can actually appear under well-defined kinematics. Preprint: cdn.openai.com/graviton/grav…
Stirling Churchman retweeted
We just posted a new preprint: “Single-minus graviton tree amplitudes are nonzero.”
Yes: a helicity sector long assumed to vanish in quantum gravity can actually appear under well-defined kinematics. Preprint: cdn.openai.com/graviton/grav…