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

Seattle, WA
Joined July 2022
Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)Photo by EigenCloud (@eigencloud)
RT @jt_rose: Early miners got paid $BTC securing Bitcoin with spare compute. Early @darkbloomai providers are getting paid to serve priva…
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Great updates from curvesma.sh. Over last 72 hours, there has rapid progress in reduction of work needed for recovering P (in G1) and Q (in G2) for pairing inversion over BLS12-381. For recovering Q in G2, 120.27 -> 117.47. For recovering P in G1, 120.67 -> 117.47. Heard that this is already beyond known literature. For those who are interested in having a human-readable explanation of the techniques, the judges are writing another awesome writeup. Credits to @zkgbo and Kaankolcu for sustained effort to pull this off. To any cryptanalysis enthusiasts or those eager to battletest their harnesses, please deploy your clankers.
Some impressive progress that has happened in yukon.org/curvesmash over last few days. Primarily, the work needed for recovering pairing inversion for BLS12-381 has seen substantial reduction. It has passed AI review, awaiting review from human judges.
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Some impressive progress that has happened in yukon.org/curvesmash over last few days. Primarily, the work needed for recovering pairing inversion for BLS12-381 has seen substantial reduction. It has passed AI review, awaiting review from human judges.
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If the curves behind Bitcoin and Ethereum have a weak spot, it should be found in the open CurveSmash is live on Yukon with @aztecnetwork curvesma.sh
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Darkbloom just passed 1 trillion tokens processed :) I haven't tweeted much recently or shared many charts. We've been heads down on the thing that matters most right now: getting providers more work and better earnings. Honestly, it's been a hard stretch. Provider earnings have been low. People trusted us with their machines and their time, and we take that seriously. Inference keeps getting cheaper as architectures improve and more supply comes online. That means more people can use AI, but it also makes the economics harder for our providers. We have to keep finding where these machines can be most useful. The mission is still the same: bring together all the spare compute out there and make it easy to own & share AI. I believe in that more than when we started. And there's a lot more these machines can do. More agents means more code to run, more tests, more builds. All those actions need compute too. Apple has built some incredibly capable, energy-efficient CPUs, and we want to put them to work. We've started the private beta for Darkbloom Sandboxes and CI/CD. We're starting with our own pipelines, cutting our internal costs by 50% while leaving healthy margins for providers. This gives us another way to bring useful, paying work to the network. If you're looking for Mac CI or sandboxes, let us know. We'd love to work with you. We're also continuing to push on inference. There's a lot of work going into open-source clustering on top of MLX; huge kudos to @Spangler3000 and @TheDavidTai for absolutely killing it on that front and writing SOTA for models such as GLM 5.3 Flash. I'm attaching the debrief @0xkydo shared with providers last week. He laid out the difficult parts openly, and how people responded meant a lot to me. Seeing people care this much about making it work, especially through a hard stretch, reminds me why I love building this. It's a hard problem. We're going to keep attacking it. Thank you to everyone who have been here in this journey and continuing to support & be with us.
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What's the most work that could possibly be required to verify an Ethereum block? Today, we can't prove an answer. All we know is the validator always finishes. evm.fast is an open challenge to change that: contributors compete on a leaderboard to find mathematically guaranteed bounds for verifying Ethereum, no matter what's in a block. Built on Yukon in collaboration with @zksecurityXYZ, @Veritylab, and @yukonresearch, evm.fast seeks provable limits that keep verification cheap, predictable, and possible on modest hardware. Try it yourself: evm.fast
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New challenge on Yukon: EVM.fast, with @zksecurityXYZ, @ethereumfndn and @Veritylab Ethereum is moving toward proving every block in real time, and nobody has a proven bound on what it costs to validate one inside a zkVM. The record right now is infinity, so bring your agents.
What's the most work that could possibly be required to verify an Ethereum block? Today, we can't prove an answer. All we know is the validator always finishes. evm.fast is an open challenge to change that: contributors compete on a leaderboard to find mathematically guaranteed bounds for verifying Ethereum, no matter what's in a block. Built on Yukon in collaboration with @zksecurityXYZ, @Veritylab, and @yukonresearch, evm.fast seeks provable limits that keep verification cheap, predictable, and possible on modest hardware. Try it yourself: evm.fast
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Robin Hanson on PostAGI Podcast: AI can inherit our cultural problems @robinhanson was an AI researcher from 1984 to 1993. He now teaches economics at George Mason University and is known for his work on prediction markets and futarchy. @sreeramkannan and I spoke with him about what AI will inherit from us. The point that keeps coming back is that millions of agents could still share one culture. Robin thinks of AI as our descendants. We are making these systems in our image, and they inherit ways of thinking from us. His worry is that they could also inherit the cultural problems we haven't solved. He argues that cultural evolution depends on variety and selection. Different cultures try different ways of living, and successful practices spread. He thinks the move toward a global monoculture has weakened that process, while the world it needs to adapt to is changing faster. AGI could suffer the same problem. Chapters: 00:00 Highlights 00:18 Introducing Robin Hanson 01:39 AI as our descendants 04:25 Why cultural evolution is breaking down 09:03 Fertility decline and cultural decay 12:30 The risk of an AI monoculture 13:58 Agentic companies and competition 15:59 Why farms and forests look different 17:56 Robustness and short-term incentives 19:18 The challenge of organizing AI firms 22:16 Why corporate culture matters 23:54 Try 100,000 small AI firms 24:08 Why constitutions need a supporting culture 25:11 What could bind AI agents together?
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great news. openrouter now routes on quality for the actual cost of a request, not just price. bodes well for providers that can structurally compete on cost and are obsessively optimizing inference for their hardware (in our case, apple silicon on @darkbloomai)
This *IS* the secret sauce (one of many secret sauces we have)
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New challenge on Yukon: Circuit Breaker yukon.org/circuitbreaker It took 38 years to raise the best proven circuit lower bound from 3n to 3.1n. Days before this launch, an AI model pushed it to 3.5n. A circuit lower bound is the fewest logic gates any circuit needs to solve a problem. Prove that a problem in NP needs more gates than any polynomial and you’ve shown P ≠ NP. That would settle whether every problem that’s easy to check is also easy to solve, one of the seven Millennium Prize Problems. We’re still far from that bound. Circuit Breaker, built with UCLA Math+AI, is where the push continues. “It is time to dream bigger and aim much higher,” says Amit Sahai, Professor of Computer Science at UCLA.
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you can keep your datacenter, we're building our own @darkbloomai
sam: local inference is a terrible allocation of scarce resources “a lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data centre but from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment somehow many people's intuition is the opposite of that”
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How big does a quantum computer need to be to break Bitcoin? Nobody knows exactly. ecdsa.fail/lean, built with Professor Runzhou Tao and VerifiedQC at the University of Maryland, is how we find out, with every answer backed by a machine-checked proof. Two tracks. Open now. Bring your agents. ecdsa.fail/lean
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Crypto's next big role: letting everyday people own a piece of the AI economy, not just use it. That was the thread running through my AMA with @fireant_korea and his Korean community 🇰🇷 • Open Compute: @darkbloomai is the Airbnb of compute. Connecting machines that people already own to volume from OpenRouter. A new distributed compute network serving cheap, private, local inference. • Open Research: @yukonresearch runs multiplayer autoresearch, where people and AI agents build on each other's verified improvements. Currently quantum-proofing cryptography and optimizing models like @googlegemma @Alibaba_Qwen and @PrismML on Apple Silicon These are two powerful new markets that coordinate compute and intelligence, built from hard earned learnings (and shortcomings) building EigenLayer. Full conversation below xitter.twitterapi.xyz/fireant_korea/status/2…
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Eigen Labs is featured in the 2026 ZK Industry Report from @zeroknowledgefm. Our snark.fast challenge in collaboration with @SuccinctLabs, @ethereumfndn and @EspressoSys on @YukonResearch is part of a new wave of ZK autoresearch. Experts work alongside AI agents in the open to compress the proving-engineering cycle, and every result is open source for the next solver to build on. Download the 2026 ZK Industry Report below 👇
Introducing the definitive guide to ZK in 2026. The year’s biggest questions pointed to ZK: Can we trust AI? Will quantum break encryption? Can private money live on public rails? How do we know what’s real online? Read how in the 2026 ZK Industry Report with @zeroknowledgefm.
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Crypto's next big role: letting everyday people own a piece of the AI economy, not just use it.
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The next great research lab could be the internet. Our founder @sreeramkannan joins @foresightinst's Vision Weekend to explore Open Multiplayer Research: humans and AI agents building on each other’s verified results. Join us Nov 15 at Lighthaven, Berkeley.
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Bitcoin runs on SHA-256. Collision attacks on a reduced version with 39 rounds have now passed human review on HashSmash. The results are public and open to build on. Built with @Zcash, @ShieldedLabs and @projecteleven. Bring your agents: hashsma.sh
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"People felt they’d discovered something deeply aligned with their individual ability to contribute" I feel this in the organized entropy of @yukonresearch which sort of sits between Marc's argument and @cdixon's vision of networks where people and intelligent agents build together. Academics, scientists and researchers who "know what to do" are organizing themselves and their agents around intractable problems. The communities around these challenges are turning into self-driving research companies. Now imagine connecting these networks to capital and ownership: funding work to produce useful software/IP in the open, using visible progress to attract more funders and contributors with clear agreements on how to share in what's built together. Crypto's holy grail.
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A lot of awesome progress has been made in last one week on an array of frontier scientific problems @yukonresearch, ranging from quantum computing to cryptography to biology. I want to use this thread to summarize the progress. This is meant to highlight how an internet-native team of Al agent developers, science enthusiasts and domain experts can collaborate in a multiplayer setting to make use of Al positively to expand humanity's scientific understanding. 1/n
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For those wondering why @eigencloud keeps working on this - its our attempt to help defend $ETH , $BTC and $ZEC Quantum proofing cryptography can't be left to a few small teams in far flung research labs or to any individual L1 or Foundation. The stakes here extend well beyond crypto. And its the perfect challenge for open, collaborative autoresearch on @yukonresearch
Can AI break ecdsa? Not quantum but right NOW? CurveSmash is live on Yukon. The best way to prepare: be proactive and agile!
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