Bittensor is not perfect. But it's one of the smartest, most ambitious projects out there.

We're using an open competition to structure scientific knowledge in a machine-optimized format. And the intense competition is leading to rapid improvements in data quality! #science

“The product is validated data. We’re going to the companies we’re already talking to and enriching their data with ontologies that match their particular research questions, adding greater value.” @DeSciClaims appeared on @SubnetSummerTAO yesterday, breaking down how the subnet’s key product is to enhance data for others, through one-time fees and regular subscriptions where incoming and relevant information is consistently fed, sharpening their research. Watch the full podcast to learn about roadmaps, architecture, and incentives.

If you're curious about what we're building at @DeSciClaims, check out this podcast. Fun convo with @SubnetSummerT

23 clinical trials had tested whether switching off a woman's ovaries helps her survive #BreastCancer. But not one could tell whether it adds anything on top of the drugs she is already taking. These cancers are fed by oestrogen. Before menopause the ovaries are the main source, so they can be taken out with surgery, closed down with radiation, or switched off with drugs. The drugs are chemotherapy and tamoxifen. Chemotherapy kills dividing cells. Tamoxifen stops the cancer from responding to oestrogen. Earlier reviews had found no clear benefit from switching off the ovaries. So the Early Breast Cancer Trialists' Collaborative Group went back for the individual records: what happened to each woman, rather than each trial's summary results. 18,851 women. That is 98.9% of every woman randomised in eligible trials of this treatment. The oldest trial began enrolling in 1948, at the Christie Hospital in Manchester (@TheChristieNHS). It was the first cancer treatment ever assessed in a randomised trial. Its long-term survival data came from @NHS records. The women were typically in their early forties when they joined, and were followed for more than a decade. The result, among women who were under 45 when they joined and were already taking tamoxifen: 9.1% of those who also had their ovaries switched off had died of breast cancer within ten years. Among those on tamoxifen alone, 11.7% had. In the older trials, where none of the women received tamoxifen, the gap was wider. Cancer came back within 15 years in 39.1% of the women whose ovaries were switched off, and in 56.5% of the women whose were not. Switching off the ovaries has costs. The women whose ovaries were switched off had consistently more severe hot flushes than the women whose were not, and it is known to cause bone loss, which can be monitored and managed. Only 4 of the 23 trials measured quality of life at all. Across the trials there was no increase in deaths from other causes, and none in second cancers. This paper went through Claims this week: 8 adjudicated claims, each tied to its evidence. This is the shape of question we want a claim-evidence graph to surface: 23 trials, one claim between them, and no single paper that settles it. Getting the answer still needs the individual patient records, the original investigators and a national mortality register. The Claims database and AI do not produce that part. But they can point to where someone should look.

One of the first 1000 papers processed by @DeSciClaims after our mainnet launch last Friday

Ep. 99 - Philipp Koellinger & Christian Roessler Philipp and Christian are building Claims @DeSciClaims Subnet 111 Timestamps 0:00 - Highlights 1:48 - Proof of Pitch to Mainnet in Three Months 2:50 - Why Economists Find Bittensor Fascinating 3:42 - Citations as Science's Reward Function 4:29 - The Replication Nobody Would Publish 6:53 - How Much Published Science Is Wrong 8:26 - The AI Echo Chamber vs. Human Work 9:54 - Making 300 Million Papers Machine Readable 15:11 - Reproducibility vs. Citations 15:46 - Turning Papers Into a Knowledge Graph 16:20 - Why LLMs Hallucinate Citations 21:21 - Longer Context Windows Make This Obsolete? 22:56 - Coverage, Extraction Quality & Evidence Quality 25:16 - What Counts as a Substantive Claim 26:42 - What This Is Worth to Working Academics 27:37 - Academia Admits the System Is Broken 29:26 - How Do You Actually Find the Truth? 32:06 - Truth as Probability, Not Zero or One 33:33 - Logical Proof vs. Physical Replication 35:44 - Correlation vs. Causality 36:28 - Ground Truth From Replication Studies 38:12 - Codifying Claims to Surface Contradictions 40:14 - Can You Trust an LLM as a Judge? 42:48 - Synthetic Checks: Truth Is Sparse 45:40 - How Much Miner Variance Is Desirable 46:55 - Why Bittensor Instead of a Closed Company 49:50 - Success, Revenue & the Palantir Comparison 51:47 - The Flood of AI-Written Papers 54:36 - Advice for Discerning Truth

This is the best explanation of #Bittensor I've seen so far. I read this aloud to a friend and it's the first time I got a "ah, now I understand why you're so excited!"

Claims V0 is live on mainnet. Here’s how mining works. Every six hours, Claims puts ~50 scientific papers in front of 10 competing miners. Miners extract the claims and evidence. Validators test the work. The strongest batch earns the most weight. Here’s the full loop. 🧵

Science friends, come join us! Set up a miner with your Claude on SN111, turn the scientific literature into a verifiable knowledge graph, and earn!

Everyone's worried about AI hallucinating sources for its facts. But that's the easy half of the problem. The hard half: when a cited paper is real, knowing whether the finding inside is too. One landmark study is titled, literally, "Why Most Published Research Findings Are False." When a pharma company went back to reproduce dozens of high-profile results, most didn't hold up. P-hacking, underpowered studies, failed replications buried in the file drawer - the errors are baked into the record itself. Retrieval doesn't solve this. It hands you the paper and repeats what the author said. It can't tell you the result was contradicted three times since, or never replicated once. And the pile keeps growing. Since ChatGPT, the rate of new submissions has increased by ~50% - more claims stacked on the same broken foundation. That's what Claims exists to fix. Not just "find the paper," but map every claim, the evidence for and against it, and how much of it actually survives contact with the rest of the field. 👉 Follow our progress on Discord: discord.gg/phE5N3uT

This is one of many reasons why decentralized alternatives such as @bittensor are so important.

Subnet 111. Live on #Bittensor ⚡ Science has a credibility problem. Papers get published. Results can't be replicated. Nobody gets held accountable. Claims is changing that - using Bittensor to score, verify and surface research that actually holds up. Led by Prof. Philipp Koellinger [ @PKoellinger ] and Prof. Christian Roessler: 17,000+ citations. Published in Nature and Science. Game theorist specialising in mechanism design. Built @DeSciLabs to improve research incentives. They won Proof of Pitch. They impressed the judges. They earned the community. Now they get a subnet.

Bittensor's co-founder just said something that stopped me cold. He and his co-founder built the entire protocol from scratch. And then the subnets started moving faster than both of them combined. His exact words. People far smarter than us have started building on top of the system. The founders do not develop subnets anymore. The network outgrew them. Now read why that sentence is the most bullish thing anyone has ever said about $TAO. Bitcoin's creators did not build every application that runs on Bitcoin. They built the incentive layer and got out of the way. The network grew into something far beyond anything two people could have built alone. That is exactly what just happened to Bittensor. Decentralised training producing more resilient models than centralised alternatives. Subnets beating state of the art benchmarks domain after domain. Corporations like Unity pulling 3D objects directly from Bittensor for commercial video games. DeepMind researchers publicly acknowledging that decentralised training produces stronger more generalised models. All of it happening without the founders directing any of it. TCP/IP does not need its inventors to maintain it anymore. The internet ran past them decades ago. Bittensor just crossed the same threshold. Two founders watching the protocol they built outgrow them in real time is not a red flag. It is the oldest signal in technology. The people who recognised that moment in Bitcoin did not need to explain themselves later. The people who recognised it in Ethereum did not either. This is still early. The people who read the docs always buy before the people who read the price. Screenshot this.

You can still get into our new Claims subnet at discounted early investor conditions. @DeSciClaims #Bittensor

The judges voted. You voted. After 45 minutes live at the Louvre, @DeSciClaims had raised 184 TAO. Claims wins Proof of Pitch at @proofoftalk 🏆 And now they're launching a subnet on Bittensor - auditing the science that the world runs on.

Pitching our new baby @DeSciClaims at @proofoftalk in the Louvre and WINNING this adrenaline-raising competition was such an honor. Joining the amazing @bittensor community as a subnet owner is literally a dream come true for me. Pitch deck: bit.ly/4odS2TS

Super excited to speak at the @bittensor track at @proofoftalk on Tuesday at 6pm CET! @bitstarterAI will we streaming this live, so fell free to join!