# Biological Moonshots **Entity class:** Research architecture **Domain:** Artificial intelligence / science / political economy **Maturity:** Developed ## Definition **Biological Moonshots** convert large biomedical ambitions into explicit targets that are hard to solve, easy to state, and practical to verify through standardized experiments. ## Mechanism and Consequence Targets, benchmarks, experimental harnesses, open records, and parallel AI agents turn biological discovery into an organized search process rather than an indefinite aspiration. ## Relationships - [[wiki/AI-Driven Biology|AI-Driven Biology]] - [[wiki/Accelerated Science|Accelerated Science]] - [[wiki/Age Reversal|Age Reversal]] - [[wiki/Cellular Digital Twins|Cellular Digital Twins]] ## Source Dossiers - [[research/AI Is Now So Good They Will Pay You to Quit|AI Is Now So Good They Will Pay You to Quit]] - [[research/Super Intelligence Week Index of Statements from the White House Luncheon|Super Intelligence Week Index of Statements from the White House Luncheon]] - [[research/Jensen Pushes Back on Doomers Moonshots Live|Jensen Pushes Back on Doomers Moonshots Live]] ## Simple Reminders, Quotations, and Thoughts > The Millennium Problems for Biology apply the method: pick your targets, build your harnesses, establish your benchmarks, and go. The targets include the origin of life, cryopreservation, and regrowing limbs. The proposed problems should be hard to solve but easy to verify in a standard wet lab within a couple of days. > **— Adapted from Peter Diamandis**, *MOONSHOTS Live, September 25, 2026* [[reminders/Biotechnology/Biology Needs Hard Problems That Are Easy to Verify by Peter Diamandis|Biology Needs Hard Problems That Are Easy to Verify by Peter Diamandis]] > "The beauty of the Millennium Problems for Biology is that they are easy to verify and, for now, hard to solve. That structure turns every hard biological problem into a mathematical conjecture and a target. With cellular digital twins, biology becomes a search problem, which makes it tractable for the first time in history." > **— Alexander Wissner-Gross**, *MOONSHOTS Live, September 25, 2026* [[reminders/Simulation/Cellular Digital Twins Turn Biology Into a Search Problem by Alexander Wissner-Gross|Cellular Digital Twins Turn Biology Into a Search Problem by Alexander Wissner-Gross]] > Anthropic announced that it had built its own life-science research group and wet labs. Claude, reportedly working autonomously from one prompt, searched a massive DNA database for interesting reverse transcriptases—enzymes that copy RNA or DNA. Nine hundred fifty Claude agents searched for twenty-one hours and found a repeating DNA pattern similar to CRISPR. It has been named the array-associated reverse transcriptase. Researchers do not yet know exactly what it does, but believe it may be related to programmable transcriptases and gene editing. > **— Adapted from Peter Diamandis**, *MOONSHOTS Live, September 25, 2026* [[reminders/Biotechnology/Nine Hundred Fifty AI Agents Searched DNA for New Biological Machinery by Peter Diamandis|Nine Hundred Fifty AI Agents Searched DNA for New Biological Machinery by Peter Diamandis]] > Let us have a hundred Millennium Problems for Biology, put a thousand AI agents on each one, and open-source everything they are doing. That is what the AI laboratories should collaborate on. > **— Adapted from Emad Mostaque**, *MOONSHOTS Live, September 25, 2026* [[reminders/Scientific Literacy/Put a Thousand AI Agents on Every Biological Moonshot by Emad Mostaque|Put a Thousand AI Agents on Every Biological Moonshot by Emad Mostaque]] > "Somatic limb regeneration: Demonstrate the ability to regenerate lost limbs in adult wild-type mice." > **— Edison Scientific and FutureHouse**, *MOONSHOTS Live, September 25, 2026* [[reminders/Biotechnology/Regrow Lost Limbs in Adult Mammals by Edison Scientific and FutureHouse|Regrow Lost Limbs in Adult Mammals by Edison Scientific and FutureHouse]] > What OpenAI did is they put 10,000 [AI] agents for 88 hours on [two qualifying conditions of the Navier–Stokes Millennium Prize problem in fluid dynamics], which is a hundred years of talented human time, and then they had a formal proof. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Ten Thousand AI Agents Compressed a Century of Mathematical Work Into Eighty-Eight Hours by Emad Mostaque|Ten Thousand AI Agents Compressed a Century of Mathematical Work Into Eighty-Eight Hours by Emad Mostaque]] > "There’s a theorem called Fermat’s Last Theorem. The official proof of that is 127 pages. Anthropic formalized that proof. It’s 13 million lines of code." > **— Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Formalizing Fermat Required Thirteen Million Lines of Code by Emad Mostaque|Formalizing Fermat Required Thirteen Million Lines of Code by Emad Mostaque]] > As of the last month and a half, the models have gone beyond their training data definitively. Before Navier–Stokes, OpenAI released ten proofs of famous math problems, and at least two of them — [one] conjecture being the main one — [are] definitively novel, elegant, and never seen before, the way they did that proof. [AI solved] Navier–Stokes in a bit of a more mechanical way, but again in an incredibly novel way. [The Navier–Stokes proof] is quite difficult to read because it’s like AI slop Claudism when you’re reading it. It took three days for me to even read the paper, and I haven’t gone through the formal stuff. I’ve talked to enough of my mathematician buddies to say: yeah, a human could have done [the AI-generated Navier–Stokes proof] given twenty or thirty years. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/AI Has Begun Producing Novel Mathematics Beyond Its Training Data by Emad Mostaque|AI Has Begun Producing Novel Mathematics Beyond Its Training Data by Emad Mostaque]] > The fact that [OpenAI] could scale [its work on the Navier–Stokes fluid-dynamics problem] by attacking it with 10,000 [AI agents] means that formally verifiable mathematics can absorb enormous amounts of parallel computation: you can literally chuck compute at [the search for a proof]. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Formal Mathematics Can Absorb Enormous Parallel Computation by Emad Mostaque|Formal Mathematics Can Absorb Enormous Parallel Computation by Emad Mostaque]] > "We’ve reached this point where [the latest AI] models have suddenly gained another capability, which is the capability to conceptualize. There’s something internal going on within them." > **— Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/AI Models Have Begun to Conceptualize by Emad Mostaque|AI Models Have Begun to Conceptualize by Emad Mostaque]] > "When we first came out with the first video models, [we said,] “Do gymnastics.” … Now they do it flawlessly, and they’ve learned physics." > **— Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Video Models Learned Enough Physics to Perform Gymnastics by Emad Mostaque|Video Models Learned Enough Physics to Perform Gymnastics by Emad Mostaque]] > "[Math is] one of the most formally verifiable [domains], but even outside of that we’re seeing human-level performance drop. Two days ago, the AIs tied the best humans in superforecasting. There are some humans who are better than others at forecasting things like outcomes of political campaigns [and] who’s going to win elections. Every year [Metaculus has] a superforecasting championship where the best human teams come together and forecast stuff. AI has just tied the best human, and obviously it will beat the best human now. [Forecasting] is something that’s open-ended, because math is kind of deterministic. You’d think a computer should be able to do math better than a human. This high-level conceptual math is a bit different, but [AI has] got there, and now it’s got there in open-ended domains." > **— Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/AI Has Tied the Best Human Superforecasters by Emad Mostaque|AI Has Tied the Best Human Superforecasters by Emad Mostaque]] > I am deeply empathetic to people who have an existential reaction to AI entering their profession, but mathematics is the computation upon which the universe runs. There are few achievements that would unlock more real-world capability than solving mathematics. > **— Adapted from Tom Bilyeu**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Solving Mathematics Unlocks the Computation of the Universe by Tom Bilyeu|Solving Mathematics Unlocks the Computation of the Universe by Tom Bilyeu]] > [Solving great technical problems often produces valuable secondary inventions:] we get to the Moon, and then we have pens that can write upside down. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Moonshots Create Valuable Inventions Around the Main Goal by Emad Mostaque|Moonshots Create Valuable Inventions Around the Main Goal by Emad Mostaque]] > "The potential for these new discoveries is huge. If you’re a pure mathematician, then math would be solved. I think a lot of physics problems will be solved, and that will be great for humanity. The tools that come out will again be great for humanity." > **— Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Solving Mathematics and Physics Will Be Great for Humanity by Emad Mostaque|Solving Mathematics and Physics Will Be Great for Humanity by Emad Mostaque]] > Across mathematics, forecasting, media generation, software, agentic work, and robotics, AI is reaching a new level of capability at the same time. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/AI Is Reaching New Capability Across Six Domains at Once by Emad Mostaque|AI Is Reaching New Capability Across Six Domains at Once by Emad Mostaque]] > I understand what is happening in AI. We reached a level of optimization, and the internals of the models reached a scale at which progress became predictable. Now several exponential trends are overlapping and making the combined rate of progress even more exponential. > **— Adapted from Emad Mostaque**, *Impact Theory with Tom Bilyeu, 2026* [[reminders/Scientific Acceleration/Overlapping Exponential Trends Are Accelerating AI Progress by Emad Mostaque|Overlapping Exponential Trends Are Accelerating AI Progress by Emad Mostaque]] > "It is phenomenally cool to put a framework around progress in biology because the Nobel Prize is going to become irrelevant—in fact, as of now, it is completely irrelevant. Putting a framework around progress in this field is incredibly important." > **— Dave Blundin**, *MOONSHOTS Live, September 25, 2026* [[reminders/Biotechnology/Biology Needs a Framework for Progress Beyond the Nobel Prize by Dave Blundin|Biology Needs a Framework for Progress Beyond the Nobel Prize by Dave Blundin]] > "We believe that biohybrid robots powered by living muscle could one day perform delicate jobs like exploring environments too fragile or unpredictable for conventional hardware, because living tissue is soft, responsive to its surroundings, and can heal itself." > **— Ritu Raman**, *Powered by muscle cells, a paper-thin robot swims through watery maze, September 29, 2026* [[reminders/Biotechnology/Living Muscle Can Power Robots That Heal Themselves by Ritu Raman|Living Muscle Can Power Robots That Heal Themselves by Ritu Raman]] > "AI is already changing how we discover and develop medicines at Novo. With Claude Science in our R&D workflows, Anthropic's frontier models in our software development, lab in the loop research in drug discovery, and Anthropic engineers working alongside our scientists, we have seen what is possible when frontier AI meets deep scientific expertise. We're excited to join the Claude Frontier Academy and the FDE Residency, giving our engineers the same hands on training and expertise behind Anthropic's most successful deployments, so together we can bring the next generation of medicines to patients faster." > **— Loic Giraud**, *Anthropic invests $100 million to train 10,000 engineers and tackle the enterprise AI talent gap, October 2, 2026* [[reminders/Biotechnology/Frontier AI and Deep Scientific Expertise Can Bring Medicines to Patients Faster by Loic Giraud|Frontier AI and Deep Scientific Expertise Can Bring Medicines to Patients Faster by Loic Giraud]]