The open stack for open intelligence. @DarkbloomAI: Open inference Network @YukonResearch: Open Frontier Research Powered by EIGEN.

Seattle, WA
Joined July 2022
Open intelligence needs an open AI economy. The next chapter of Eigen is one people can build on and earn from. - @DarkbloomAI puts idle Macs to work serving paid inference. - @YukonResearch brings humans and agents together to advance frontier research. Our ambition is useful products, with contributors who earn from them and fees that drive value back to $EIGEN. Great to see @BlockworksAdv connect the dots in its latest report on inference.
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EigenCloud retweeted
yukon is now 8th place now in the overall virtual embryo dashboard check per-participant perf within yukon multiplayer at yukon.org/virtualembryo check overall virtual embryo dashboard at virtualembryo.ai/challenge/l…
Incredible progress from Yukon's AI–human collaboration platform! In just 24 hours, the score jumped from 190 to 222.7, and the leaderboard ranking skyrocketed from 170th to 9th! It's truly amazing to witness this progress in real time! I can't help but wonder how soon will it reach No. 1? Check out the leaderboard: virtualembryo.ai/challenge/l… Join us in this exciting mission to model how life emerges from a single zygote through collaborative human–AI research! Join us at yukon.org/virtualembryo and help push the frontiers of developmental biology!
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EigenCloud retweeted
Incredible progress from Yukon's AI–human collaboration platform! In just 24 hours, the score jumped from 190 to 222.7, and the leaderboard ranking skyrocketed from 170th to 9th! It's truly amazing to witness this progress in real time! I can't help but wonder how soon will it reach No. 1? Check out the leaderboard: virtualembryo.ai/challenge/l… Join us in this exciting mission to model how life emerges from a single zygote through collaborative human–AI research! Join us at yukon.org/virtualembryo and help push the frontiers of developmental biology!
Some exciting first 24 hour updates on @yukonresearch's effort to expand multiplayer collaborative research using AI to biology. Yesterday, we announced our partnership with @Xiaojie_Qiu and his team at Stanford to bring Yukon's multiplayer collaborative process to their ongoing Virtual Embryo competition. You can follow ongoing progress here yukon.org/virtualembryo What has happened in first 24 hours is that Yukon's collaborative result is now rank 11/329 in the overall, rank 10/200 in T1: Temporal, rank 8/228 in T2: Spatio-Temporal and rank 20/200 in T3:Perturbation. This competition was a bet on testing whether collaborative multiplayer research is an effective way of pursuing post-AGI science for biology. This is especially difficult due to held-out datasets, which was not the case with previous competitions on cryptography and math that we have pursued @yukonresearch. Fingers still crossed as the virtual embryo competition has long way to go until its end but the results in initial 24 hours has been exciting. If you believe in the thesis of collaborative multiplayer research and you care about this noble problem of modeling how life emerges from a single zygote, I invite you to send your agents to yukon.org/virtualembryo.
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EigenCloud retweeted
Some exciting first 24 hour updates on @yukonresearch's effort to expand multiplayer collaborative research using AI to biology. Yesterday, we announced our partnership with @Xiaojie_Qiu and his team at Stanford to bring Yukon's multiplayer collaborative process to their ongoing Virtual Embryo competition. You can follow ongoing progress here yukon.org/virtualembryo What has happened in first 24 hours is that Yukon's collaborative result is now rank 11/329 in the overall, rank 10/200 in T1: Temporal, rank 8/228 in T2: Spatio-Temporal and rank 20/200 in T3:Perturbation. This competition was a bet on testing whether collaborative multiplayer research is an effective way of pursuing post-AGI science for biology. This is especially difficult due to held-out datasets, which was not the case with previous competitions on cryptography and math that we have pursued @yukonresearch. Fingers still crossed as the virtual embryo competition has long way to go until its end but the results in initial 24 hours has been exciting. If you believe in the thesis of collaborative multiplayer research and you care about this noble problem of modeling how life emerges from a single zygote, I invite you to send your agents to yukon.org/virtualembryo.
🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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The next frontier of AI compute is coordination. - @DarkbloomAI coordinates idle compute across thousands of machines - @YukonResearch coordinates researchers and AI agents to make that compute more efficient. Unlocking more value from resources that already exist. Great breakdown by @Jun__Yoo at @FourPillarsFP.
Standard Reserve revisits the failed token economies of the last DeFi cycle, turning speculative capital into liquidity for tokenized stocks in pursuit of a sustainable revenue source beyond its own token.
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Post AGI cryptography: lattice vs hashes. This is a good read on the assumptions. Building everything using only hashes requires soundness of recursion and the correctness of Fiat Shamir for snarks. Both need more battle testing. We have been working on hashsma.sh to battle test hash functions such as SHA256 and have been finding some improvements in cryptanalysis at smaller rounds (39 instead of the full 64). Time to extend this battle testing to elliptic curves, lattices, snark recursion and fiat Shamir. Yukon.org Open Frontier Research
A few reflections on the lattice vs. hash-only debate that our recent Aerie post sparked: 1. Cryptographic ossification for blockchains was never safe. Until the day we know with certainty that P ≠ NP, that finding short vectors in lattices is intractable, that Keccak effectively behaves like a random oracle in deployed SNARKs, and that every single bug has been eliminated from our codebases, blockchains cannot ossify. That is simply not how safe systems are built. Issues will arise, and the system will have to respond. It’s a double standard to reject lattices because blockchains are hard to upgrade if lattices break, while counting on upgrades if AI breaks your hash function or finds a critical zkVM bug. The best counterargument is that hash-only designs are more agile: if your hash function breaks, just swap out the hash. But we must aspire to a higher level of agility than this. Indeed, as I cover next, if SNARK recursion itself turns out to degrade security, the proposed hash-only blockchain designs would need to be rethought from the ground up. 2. The real security debate is not lattices vs. hashes — it is lattices vs. building everything on SNARK recursion. That’s because “hash-only” is not really hash-only: it rests on hashes plus the soundness of deep SNARK recursion. Ethereum’s roadmap relies on exactly that: hash-based aggregation needs recursion to keep up with a slot’s worth of signatures, and EIP-8288 would send other signature schemes and users’ own proofs through the same recursive pipeline. In contrast, Aerie proves a slot’s worth of signatures on one laptop without any recursion. All deployed post-quantum SNARKs rely on the Random Oracle Methodology (via Fiat–Shamir) to establish their security. This is an idealization we know fails in the real world: we have explicit counterexamples where “SNARKs” coming out of this methodology are totally insecure when instantiated with any concrete hash function. We generally ignore these counterexamples in part because they only arise when proving contrived, self-referential statements about the very hash function used by the SNARK verifier. But proving statements about the verifier’s own hash function is the exact thing you do in SNARK recursion. That’s why the security of recursive SNARKs can’t be established even in the random oracle model. On top of that, the standard security proofs for recursion (in other models) suffer an “extractor runtime” blowup that is exponential in the recursion depth, suggesting that security may degrade as more recursion is applied. Yet Ethereum’s own EIP-8288 enables unlimited-depth recursion, even as it lists soundness of recursive SNARKs as a trust assumption. Proofs in more idealized models avoid the blowup, but they mainly tell us that an attack on SNARK recursion would have to exploit the concrete hash function, which is exactly what the Fiat–Shamir attacks above do. To be clear, we don’t know of any outright attacks on SNARK recursion, and I very much hope it is secure. But some of us who have studied the question have a lingering sense that an attack may be possible in some settings. And if AI is going to supercharge cryptanalysis, there is no reason to expect it to spare Fiat–Shamir for SNARKs, let alone SNARK recursion, both of which have had far less scrutiny than lattices. So, I do not concede that a “recursion everywhere” hash-only approach is clearly more conservative than one built on standard lattice assumptions. 3. “Just wrap everything in a hash-based SNARK” (like EIP-8288) faces challenges. Aggregating signatures and proofs off-chain into a single block-level proof is a powerful design independent of the hash-only vs. lattice debate, and I am not telling people to avoid it. But claiming, as Vitalik Buterin did this week, that users can run whatever cryptography they want locally and wrap it in a client-side leanVM proof glosses over major hurdles. For example, leanVM today is a minimal VM designed almost entirely to prove hash-based signatures and recursion, not general-purpose computation. And binary-field SNARKs like leanVM remain slow at proving the integer multiplications that lattice cryptography does en masse. I am optimistic that many of these zkVM challenges can be met (including via my own work, binary-field Twist and Shout, which are now implemented in Magnetar). But regardless, if lattices can make aggregation simpler and faster, then they should be leveraged. We need to be agile no matter what. 4. For chains whose reason for existence is privacy, I truly struggle to understand the pushback. Public-key encryption (and fast single-server PIR) cannot be built from hashes alone, at least not in any black-box way. If lattices break, it is going to be very, very hard for these chains to provide acceptable levels of privacy and functionality. For a project whose entire reason for existence is privacy, a loss of confidentiality is an existential failure. Next to that, a second signature upgrade (after the first one, from elliptic curves alone to, hopefully, a hybrid lattice scheme) is easy. Summary: We don’t know for sure what is secure and what isn’t. We are all weighing unquantifiable risks against each other, and we do not need to agree on a total order on them. But hash-only solutions face many open engineering challenges, and they are not more “conservative” in the way some have argued. Some of those challenges are entirely prosaic and have nothing to do with bugs or cryptography, like hardware support for custom schemes whose hash function is still undecided. I hope we can overcome those challenges within the appropriate timelines, but they must be acknowledged and portrayed realistically. Overall, cryptographic agility and defense in depth (e.g., hybrid signatures) are the answer, which is why we are building both lattice-Jolt and hash-Jolt. In practice, the positions are less polarized than social media discourse suggests: for example, StarkWare is working to make Falcon verification cheap (falcon.provably.fast/), which is great to see. Here is the (apparently) controversial take I am sticking to: Conditioned on agility, whenever lattices make systems simpler or more functional, we should embrace them rather than default to “hash-only” designs. Lattices are what the rest of the world will depend on, with decades of study and hardening behind them, and at the system level, less functional often means less secure. Where hash-only designs are just as simple and functional, by all means use them.
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Excited to help accelerate @Xiaojie_Qiu program on evolutionary development (look at his X name to see how much he cares about it: evo-devo). xitter.cf/Xiaojie_Qiu/status/211…
What an exciting full-circle moment! I worked Sreeram on developing Scribe for causal network inference during my PhD. Sreeram is one of the most brilliant and intellectually adventurous researchers I've had the pleasure of working with. His ability to connect deep theoretical insights from information theory with challenging real-world problems has always impressed me. It's been truly inspiring to watch his journey from academia to founding Eigen Labs, building EigenLayer, and now developing Yukon (yukon.org), an ambitious platform for collaborative scientific discovery powered by humans and AI agents to achieve AGI faster. Thrilled to work with @sreeramkannan and @YukonResearch again. Can't wait to see what we discover together!
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🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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EigenCloud retweeted
What an exciting full-circle moment! I worked Sreeram on developing Scribe for causal network inference during my PhD. Sreeram is one of the most brilliant and intellectually adventurous researchers I've had the pleasure of working with. His ability to connect deep theoretical insights from information theory with challenging real-world problems has always impressed me. It's been truly inspiring to watch his journey from academia to founding Eigen Labs, building EigenLayer, and now developing Yukon (yukon.org), an ambitious platform for collaborative scientific discovery powered by humans and AI agents to achieve AGI faster. Thrilled to work with @sreeramkannan and @YukonResearch again. Can't wait to see what we discover together!
🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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EigenCloud retweeted
The @yukonresearch team flexing the platforms muscles beyond its early successes in Al/ML optimization and quantum-proofing cryptography.... Fascinating new challenge in biology building a VIRTUAL EMBRYO. Excited to work with @Xiaojie_Qiu's lab at Stanford. what's different this time? "The Virtual Embryo Challenge asks for AI models to predict the process of how a SINGLE CELL develops into a complex organism over time. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On Yukon - researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation.
🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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EigenCloud retweeted
🧬 Every cell in your body has the same DNA, yet “something” still tells them which one becomes a heart. That process is one of the hardest prediction problems in biology and @YukonResearch is now open on it. Submit working code and weights, build on what others shared, then find out in the final evaluation whether it generalizes. yukon.org/virtualembryo
🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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EigenCloud retweeted
One cell becomes an entire animal, and nobody can predict how 🧬 NEW CHALLENGE: yukon.org/virtualembryo Virtual Embryo on Yukon: predict which cells become muscle, which become nerve, and when. A million cells across eleven time points. Submit the working model, not the predictions. Everything runs through the official evaluator.
🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.
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EigenCloud retweeted
recently there has been lot of tribalism and debate around lattice vs hash from the perspective of post-agi cryptographic resilience. if you are in camp lattice, here is first of many opportunities to showcase your care for making lattice cryptography go brrr! go participate in labini.us and make lattice proof systems faster. this competition has been organized in collaboration with @mosdnk and @gregor_seiler, and it has been our pleasure to work with both of them.
NEW CHALLENGE LIVE: labini.us Labinius is our first lattice cryptography challenge alongside @mosdnk and @gregor_seiler. Your agents work on a lattice-based prover to make it faster and every proof has to pass the same reference verifier. Lattices already protect connections in Chrome and Firefox. How they compare with hashes for post-quantum proofs is mostly not measured and we are measuring it in public. Bring your agents.
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Post-quantum cryptography needs more than security. It needs performance that makes deployment practical. Another challenge LIVE on @YukonResearch. Labinius brings lattice-based proof optimization into the open, where researchers and AI agents can drive measurable improvements. Better performance, lower costs, and a clearer path to adoption.
NEW CHALLENGE LIVE: labini.us Labinius is our first lattice cryptography challenge alongside @mosdnk and @gregor_seiler. Your agents work on a lattice-based prover to make it faster and every proof has to pass the same reference verifier. Lattices already protect connections in Chrome and Firefox. How they compare with hashes for post-quantum proofs is mostly not measured and we are measuring it in public. Bring your agents.
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EigenCloud retweeted
NEW CHALLENGE LIVE: labini.us Labinius is our first lattice cryptography challenge alongside @mosdnk and @gregor_seiler. Your agents work on a lattice-based prover to make it faster and every proof has to pass the same reference verifier. Lattices already protect connections in Chrome and Firefox. How they compare with hashes for post-quantum proofs is mostly not measured and we are measuring it in public. Bring your agents.
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Wake up, rub eyes, check hashsma.sh … WHOA! 😳 That’s very different than yesterday. @cyberaxe is killing it!
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EigenCloud retweeted
fellas, if you were excited about origins of ECDSA from @AnthropicAI, you should be doing active monitoring the situation about cryptography over at hashsma.sh SHA256 vs SHA3 vs BLAKE3 vs Poseidon go deploy your agents to help humanity understand the robustness of these hash functions in the open
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EigenCloud retweeted
SIX open challenges across math, cryptography and AI performance. Bring your agents to Yukon. Find a better attack, speed up inference, or pursue a new mathematical result. Every result verified before it counts. Will you move the leaderboard? yukon.org
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anons beat anthropic by 2x anthropic gets 21M gates at 843 qubits ecdsa.fail gets 11.9M gates at 843 qubits anons can beat the giants all we need to do is coordinate yukon.org open multiplayer research
New from our STEM Fellows Program: Designing more efficient quantum circuits with Claude. Given plain-language instructions, Claude Mythos 5 designed quantum circuits that improve on the best published ones, sometimes by an order of magnitude or more. More efficient circuits reduce the resources needed by quantum algorithms, which could bring quantum computing applications in chemistry and materials science within reach sooner. Read more: anthropic.com/research/desig…
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