Weekly Dose of Optimism #217
Weekly Dose of Optimism #217
Anduril BlueChip, OpenAI Science, Anthropic Drugs, Robot Brain Surgery, Readwise Books, Reta, Neuralink VOICE + Extra Doses
Hi friends 👋,
Happy Friday and welcome back to our 217th Weekly Dose of Optimism.
And what a week it’s been! Per New York Metro Weather, we’re in the midst of the longest streak of 8/10 or higher days since the account started in 2021, and here at the Dose, we’re in the middle of a string of 9/10 or higher weeks so long that I’ve lost count.
Have a great Halloween tomorrow. For now, all treats no tricks.
Let’s get to it.
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(1) Anduril Unveils American-Made BlueChip Computer
Another week, another extension of Anduril’s capabilities¹.
Last week, we wrote about Warhound, Ben Lamm’s effort to (humanely) genetically engineer dogs to be used in police and military work. Anduril is providing “software and hardware enhancement for items such as dog protection vests and eye goggles.”
This week, Palmer Luckey announced that Anduril would be making its very own Made in America computer, BlueChip: designed here, with components from here, with metals America can mine, refine, process, and mill at scale and at reasonable price. American batteries, too.
This is cool because as Palmer says in the video, “If you don’t control your technology, you can’t control your future.” But it’s also cool because it seems as if Anduril has gotten to the point where it’s built a machine that can make machines. Assemble enough engineers, capital, manufacturing capacity, distribution, etc… and you can build almost anything. It’s very Elon Companies-esque.
And as we wrote in The Electric Slide, making products that can sell a ton of units, like laptops, can create the pull to bring more of the supply chain here, too.
(2) OpenAI Says Its Models Disproved the ETH (and more)
Video created with Runway
The race to solve everything solvable continues apace.
This week, OpenAI announced “three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.”
In math, OpenAI’s models produced a proof of Christopher Sogge’s 1991 local smoothing conjecture in every dimension, which would also settle the Kakeya conjecture and Stein’s restriction conjecture (of course). For context, Hong Wang and Joshua Zahl proved Kakeya in three dimensions just last year, and it was one of the biggest math stories of 2025.
In computer science, a model refuted the Exponential Time Hypothesis (ETH), the widely held belief that problems like 3-SAT can’t be solved meaningfully faster than brute force. If that makes no sense to you, check out the explainer video I made with Runway, which breaks it down in claymation well enough that I could actually understand it.
In physics, the models produced a rigorous proof that interacting quantum field theories, including QCD and pure Yang–Mills, exist in four dimensions. That’s half of a Millennium Prize problem.
Whereas before OpenAI has just dropped a bunch of solutions on the internet’s head and walked away, leading to quasi-embarrassing situations like when they said GPT-5 had solved ten open Erdős problems but it turned out the model had mostly found solutions that were already sitting in the literature, this time, OpenAI is sharing the outputs as research data with experts they call “shepherds” in each field, who will choose what to do with the data and where/when to publish.
Shepherds don’t have to sign NDAs, don’t get paid, and do get the credit for explaining the work. Russell Impagliazzo and Ramamohan Paturi, who proposed ETH, are leading the review of its disproof with MIT’s Ryan Williams. Nobel laureate David Gross is leading the physics group, which chose to withhold the AI material and write it up themselves. The math proof and the ETH disproof are on GitHub with Lean formalizations. Lean, a checking software, guarantees the proof proves the formal statement, but human shepherds still have to confirm that the formal statement is the right one.
Big week for Lean, by the way. On Tuesday, Axiom announced a complete Lean auto-formalization of the Classification of Finite Simple Groups, the “periodic table of symmetry.” The proof runs about 15,000 pages and was written by more than 100 mathematicians over several decades. It’s so big that no single person has ever checked all of it. For a sense of scale, it took Georges Gonthier’s team six years to formalize just one piece of the classification, the Feit–Thompson theorem, back in 2012. But Axiom’s machines can do a lot of human-years quickly, and they’re going to need to to keep up with all of the math and physics coming out of the labs.
Because not only did OpenAI announce those results this week, a physics neolab, Physical Superintelligence (which we covered in Dose #209) released results on five problems from IQOQI Vienna’s list of open quantum problems, each with a paper, a Lean formalization, and open source verification code on GitHub.
For those of you who were planning to spend the weekend cracking OQP 12: Can vacuum correlations violate the CHSH Bell inequality at arbitrarily large separations? or OQP 12: Can vacuum correlations violate the CHSH Bell inequality at arbitrarily large separations?, I’m sorry. Machines did it. You’re going to have to find a new hobby.
Also, if you were trying to use the entanglement between two empty regions of space no matter how far apart they are to violate the Bell Theorem, I’m sorry for you too. The machine found that you can’t do it past some finite distance.
Anyway, it seems like this is just how we do math and physics now.
(2a) Anthropic Publishes Progress on Accelerating Drug Development
Apparently, it’s how we do drug development now too, if Anthropic succeeds.
AI for drug discovery is hot, but most of the focus is on discovering new molecules, which creates bottlenecks further downstream in actually developing these drugs and getting them to market. To understand and fix them, Anthropic believes, it needs to get inside the programs themselves, so for the past several months, its life sciences team has partnered with six organizations to start running programs of its own.
At the discovery end, Divergence Labs announced positive results in the fight against food allergies. Allergic reactions are triggered by IgE, which sits on your immune cells as well as floating in your blood. Standard drugs mostly neutralize the floating IgE, so Divergence’s approach aims to pry it off the cells instead. Claude turned that goal into a design plan and, largely on its own, generated about 35,000 antibody designs in a month. Three of the early hits dislodged IgE better than the standard medication, and people seem psyched that this represents meaningful progress against food allergies.
Another biotech, Generate Biomedicines, used Claude Code to redesign part of CAR-T, the therapy that uses a body’s own immune cells to hunt and kill cancer, so that it could eventually work on solid tumors. One of Claude’s designs was about 70% shorter than the standard version and got cells to make roughly 10 times as many cancer-spotting receptors.
At BigHat Biosciences, Claude proposed improvements to two antibody fragments, and BigHat’s automated lab made and tested about 1,010 variants in 10 weeks. The best ones bound more than 10x more tightly. Along the way, Claude and an Anthropic researcher figured out that the standard stability metrics were misleading and proposed better ones.
But the point is that these improvements are still hard to get to patients, so Anthropic turned to paperwork with Enveda, whose manufacturing scientists spend up to 75% of their time on it. Claude reviewed 1,061 pages of manufacturing records, caught all of the issues human reviewers had found (plus seven they’d missed), and cut review time by 89%. It also drafted a regulatory document in four hours that takes about three months by hand.
At the trial stage, Bristol Myers Squibb is using Claude to assess plans for an early-stage drug and estimate its odds of success. The Column Group, a biotech investor, is launching Pleiades, a company built to run many more drug programs with Claude than a small team normally could. The theory is that if discovery gets cheaper and faster, investors can back riskier ideas.
Anthropic is also running programs itself. In July, it acquired Mithril Medicine, a one-person company whose founder, Cody Tranbarger (aka Professor Oak), used Claude to run experiments across 11 outside labs. In under 18 months, he took a treatment for a rare muscular dystrophy from idea to promising results in mice. In one cohort of 42 kids with the severe form of the disease, only one ever walked on their own. If the treatment holds up, human trials could start as soon as late 2028.
Anthropic is upfront that nearly all of this is preclinical, so most of these drugs haven’t been tested in people yet, but they showed speedups in every part of the process. The tricky thing about complex processes like drug development is that you have to improve the whole thing at once, lest any one thing that didn’t improve slows the whole thing down.
We might finally have a machine capable of doing just that. Bad time to be a disease. Good time to be a human.
(2b) Robot + Agent Perform Brain Surgery on Mouse
I just saw this one this morning, so didn’t have time to write it up, but that’s ok, just read the headline and the tweet thread and realize that AI AGENTS PERFORMED BRAIN SURGERY ON A MOUSE.
(3) Readwise Launches Readwise Books
I’m an investor in Readwise, friends with its founders Dan Doyon and Tristan Homsi, and I love reading, so I’ve been lucky enough to get to be a part of the beta for what they were calling Bookwise and are not calling Readwise Books.
I love this app. It’s my second-most-used app on my phone, after X (need to break that habit again), and that’s not counting the time that I spend reading through Readwise Books on my Daylight Computer. The description people give most often is Kindle x Goodreads, which is part of it, but there’s also a little Strava mixed in there. There’s a leaderboard, which has definitely pushed me to read more, like the week I ended up #1 on the Readerboard in July.
The reading experience itself is familiar to those used to reading on the Kindle App, but it’s just a little bit better in places. There’s AI natively built in, which I don’t use normally, but was a lifesaver when I was reading Jean Beaudrillard’s Simulacra and Simulation, for example. Highlights go right into Readwise. And its text-to-speech is really good for listening when I get off the subway and start walking.
I am a firm believer that people should Read More Books, and although I’m biased, I’ve also voted with a ton of my time that this is the best product out there for doing that.
So go Read More Books. There’s a waitlist, but if you’re reading this, you can skip it here.
(4) Reta Works on Sleep Apnea, Too 😴
Lilly’s Retatrutide is perhaps the closest thing we have to a miracle drug.
We first covered Reta in Dose #175, as a gray-market “holy grail” in Vectorculture’s piece on Chinese peptides. By May, it was the lead item in Dose #194, after Lilly’s TRIUMPH-1 trial showed people on the top dose losing 28.3% of their body weight over 80 weeks.
Since then, the triple-hormone shot, which mimics GLP-1, GIP, and glucagon, has kept piling up wins. Now, it seems to work on sleep apnea.
Tens of millions of Americans have obstructive sleep apnea (mostly undiagnosed). The standard treatment is strapping a CPAP mask to your face every night. In two 80-week Phase 3 trials, TRIUMPH-1-OSA and TRIUMPH-2-OSA, 691 adults with moderate-to-severe sleep apnea started out stopping or nearly stopping breathing about 57 times an hour. In the trial without diabetes, the 9 mg dose cut that by 34 events an hour, versus 10 on placebo. About half of patients on the higher doses ended up with apnea that was resolved or mild without daytime sleepiness, compared with roughly one in ten on placebo. Along the way, they lost about a fifth of their body weight.
Some people have pointed out that of course, losing weight should help with sleep apnea, but OK sure whatever the mechanism, Reta just keeps fixing stuff:
Diabetes: In TRANSCEND-T2D-1, presented at ADA in June, 75–83% of patients got their A1C to 6.5% or lower in 40 weeks.
Heart risk: In TRIUMPH-3 in July, people with severe obesity and existing heart disease lost 22.6% of their body weight, with inflammation (hsCRP) down 51% and systolic blood pressure down 9.3 points.
Knees: In TRIUMPH-1, knee osteoarthritis pain fell by about three-quarters.
Liver: In a Phase 2 substudy, 93% of patients on the top dose had normal liver fat after 48 weeks.
The drug hasn’t even hit the market yet (if you don’t count the grey market). There’s still an open question as to whether these improvements also prevent heart attack and stroke, which Lilly’s dedicated cardiorenal trial will attempt to show, and which would be another massive win, but for now, we’ll just have to be happy with a drug that cuts weight, lowers heart disease risk, fights diabetes, cuts liver fat, makes our knees feel better, and replaces a CPAP.
Lilly, which crushed earnings this week and raised its full year revenue outlook by $5 billion, deserves every dollar of its $1.3T market cap.
(5) Neuralink Gives Voice Back to ALS Patients
From miracle drugs to downright miracles. Given the quantity and consistency of mind-blowing breakthroughs we cover here in the Dose, it’s easy to forget how miraculous some of them are, and how miraculous they must feel to those who benefit from them.
This week’s news out of Neuralink is one of those.
ALS, or Lou Gehrig’s Disease, is a fatal, progressive neurodegenerative disorder that destroys the motor neurons in the brain and spinal cord that control voluntary muscle movement. It takes away its victims’ ability to speak even though it leaves their mind intact, meaning they can think clearly but can’t verbalize those thoughts.
Neuralink has been working to fix that with VOICE. This week, it released early numbers from one participant who hit 75 words per minute with a 5.8% error rate across a 125,000 word vocabulary in their first week with the implant. Before VOICE, the best published result on the same vocabulary size, Stanford’s 2023 system, managed 62 words per minute with nearly a quarter of words wrong.
Natural conversation runs around 160 words per minute, so we’re about halfway there. Importantly, the system can also speak in the participant’s pre-ALS voice.
VOICE launched at UT Southwestern last October with FDA Breakthrough Device designation and plans to enroll up to six people with ALS, spinal cord injury, or stroke. That’s not a big group, and the one person in this study is just one-sixth of that. But every person who’s able to get their voice back through a BCI is a win, and the technology will only get better, faster, more accurate, and less invasive from here.
In related news, Elon Musk announced yesterday that its second product, Blindsight, which will restore sight to the blind, is ready engineering-wise.
Age of Miracles, pending regulatory approval.
EXTRA DOSES: The Commanding Heights, Science Breakthroughs, DoorDash Acquires Instacart, Thrive Holdings Acquires ADT, LIFE...
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