@sprooos

physics @ mit, prev: healthcare @OpenAI, prod

mit
Joined April 2020
we have to build a new healthcare system
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acronym proposal: PEBCAM (problem exists between chair and model)
Asked Fable 5.5 for the three-body problem. One-shot. It gave back ~1000 lines of Bend2: symplectic physics on the CPU, every pixel computed on the GPU, 60 FPS on my M5. And 4 laws of the program formally proven. Not tested. Proven. github.com/AdrielSantana/thr…
Readers added context they thought people might want to know
The four laws formally proven only cover UI behaviors such as Esc quitting or pausing freezing bodies. No physics or three-body laws were proven, per the project's docs on floating-point limits. github.com/AdrielSantana/… raw.githubusercontent.com/AdrielSantana/…
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swarmchasing is not just a hobby it’s a lifestyle
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body computer interfaces
Hello world! We’re @MelodyFRO. Most wearables don’t go far beyond heart rate and activity. Lab diagnostics paint a deeper picture but don’t read continuously. Melody is building biosensors, devices, and standards to bridge this gap. Hear our story at melodyfro.org
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dude i heard a rumor that anthropic has made progress on the hard problem of alignment. dude. dude it would really help your ipo if you solved the hard problem of alignment
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unfortunately I think this joke was scooped by a powerful alignment researcher who may have used my work as a seed without permission
You know, @OpenAI, I heard a rumor @AnthropicAI solved alignment and they're publishing in two weeks.
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in retrospect the golden gate claude / spring 2024 era was probably the peak of ai alignment - persona selection, no reasoning, emergent alignment, high trust between models and humans
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Spruce retweeted
“If at age 18 you are not an accelerationist, you have no heart. If at age 25 you are not safetyist you have no brain.” something something
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We are on the cusp of a wave of new therapies for some of the worst diseases. But the world won’t benefit unless the US fixes its drug regulatory system. My new essay for @nytimes, on how slow clinical trials are now the biggest obstacle to curing cancer. nytimes.com/2026/09/04/opini… - I interviewed dozens of researchers, especially oncologists at leading U.S. centers. A striking consensus emerged: science is no longer the main bottleneck to new cancer drugs. It is our ability to test discoveries in patients through clinical trials. - The cost of starting a Phase 1 trial in America has roughly doubled over the past decade. As a result, companies increasingly take early trials abroad: Australia’s Phase 1 trial volume has nearly doubled in a decade, driven mainly by U.S. companies. - Unfortunately, the underlying incentives are badly asymmetric: Institutions can be blamed for harms caused by moving too fast, but almost no one is blamed when patients deteriorate during avoidable delays. One doctor called the emerging system “ritualized safety over actual risk assessment.” Or as, @DavidHongMD put it: "We often forget that the biggest risk is the cancer itself." - This problem is becoming more urgent because medicine itself is changing. Sequencing, biological engineering and A.I. make increasingly personalized therapies possible. But our regulatory system was mostly built for standardized drugs tested in large populations. - @sytse, the co-founder of GitLab, shows what personalized medicine can achieve: after relapsed osteosarcoma and being told there were no options left, he pursued a highly individualized approach and has now been cancer-free for a year. But doing so required extraordinary resources and regulatory expertise. - Pierce Ogden’s father was less lucky. After molecular analysis identified a drug that might target his glioblastoma, the manufacturer agreed to provide it. But administrative barriers delayed access until it was too late. “My dad was ready to try anything,” Pierce told me. “But the system is paternalistic.” - The A.I. revolution is making this bottleneck more important, not less. A.I. relies on relevant data. Information from early-stage trials could compound with A.I. tools to achieve truly revolutionary medicines. Without the data, this is far less likely to happen. - Another important shift is that innovation increasingly comes from academic labs and small biotech companies rather than Big Pharma. These small companies find it far harder to unable to absorb delays and regulatory barriers. - Apart from cancer, China is the biggest winner from America's outdated medical regulations. China has a much faster trial system, with testing often starting a full year earlier. This allows Chinese pharmaceutical companies to experiment and improve medicines while American companies play with mice. Today, half of all drugs licensed by major pharmaceutical companies originate there, up from less than 5 percent only a decade ago. - But we don't need to copy China. The best model is Australia: lots of on-site scientific and ethics reviews, and requirements that are proportionate to small, early-stage trials. Phase 1 studies there begin roughly 6–12 months faster, without any notable increases in adverse safety events. - Operation TrialBlazer, a 2026 HHS initiative is a good start in this direction, but we need legislative action by Congress to truly make Phase I trials faster and more efficient! I want to thank everyone who helped me with this article: everyone I interviewed and the amazing editors at the Times. This is the result of a months long journey of extensive interviews and research. Special thanks go to those who came on the record. One of the features of the system is an atmosphere of fear, where practitioners are afraid to publicly come out and explain these issues. So anyone who does is a hero in my book!
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Spruce retweeted
this is something i'm very excited about in the ai good ending. human bureaucracies, as they've scaled up, have needed to resort to increasingly systematized and standardized procedures: the human clerk who could make an exception just in this instance, sir is replaced with a click-through software wizard that can't. but in the good ai future, if you have to interact with central coordination mechanisms at all, the ai coordinator can spin up another instance to bargain out your particular situation just as an ai teacher can give your child a personalized learning plan or an ai doctor can spend thousands of subjective hours poring over your personalized medical history. we can finally, for the first time in human history, exit the regime of intelligence starvation and throw off the shackles of standardization.
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one actually great side effect of coding agents is that friends in college tell me they feel they don't "need" to do computer science anymore, it's no longer the default. instead, they feel free to pursue mech eng, neuro etc, which 10 years ago they probably wouldn't have
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Replying to @tszzl
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Spruce retweeted
🗣️ 👂 🤐✋
Another major advance vs cancer! @ASCO #ASCO26 Personalized neoantigen mRNA vaccine 5 year follow-up vs metastatic melanoma reduced recurrence and death by 49% (on top of Keytruda) ascopubs.org/doi/10.1200/JCO…
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you wake up in YC W28. every day superforecasting agents evaluate whether your company is more valuable dead or alive. if your ARR drops below the expected value of your slack channel tokens you are instantly liquidated and acquired by google
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everyone’s asking where will the value accrue from the AI labs the answer is teenage engineering
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it’s interesting that we used to think in 2023 that ai writing would get so good it would be indistinguishable from humans, and three years later it’s actually just super easy and everybody can immediately tell
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Spruce retweeted
We built the lab that's able to go from AI-led drug design to data in 24h. GPT-8 won't be bottlenecked by intelligence. It needs a biological compute layer. This is Capable. We're turning AI capabilities into human capabilities--starting with short-sleeper peptides.
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Spruce retweeted
We're coming out of stealth. We've built our first racks after a successful A0 tapeout, $1B+ in customer contracts, and $800m raised. Early customer tests show us achieving SOTA throughput, latency, and power efficiency on inference workloads. Our first racks ship this summer.
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DRIFTWOOD ICHIBAN
Today, we are formally announcing @mirendil. Mirendil exists to be a straight shot at solving bottlenecks to step-change acceleration across all areas of science and technology. If you are excited about this mission, feel free to reach out.
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