Openτensor Foundaτion
@opentensor
Incentivizing intelligence
1 Following 171.1K Followers
.@openroboto just built a decentralized alternative to @Figure_robot’s Index for collecting robot training data, with real-world capture hardware.
Open robotics on Bittensor now has its data network to challenge the industry’s biggest labs.
Bittensor is coming for physical AI.
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Today we’re launching OpenRoboto Shift, opening a new chapter for OpenRoboto.
Shift is a decentralized network for collecting egocentric robotics data: first-person video of real people doing real work.
Only Possible on Bittensor.
Explore Shift →
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A Harvard research team and @chutes_ai just released a public dataset covering one year of real-world LLM inference on Chutes: 6.12B requests across 9,174 models.
Technical usage data from a Bittensor subnet is now open to the wider AI research community.
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Announcing one year of LLM inference metadata traces, with 6.12 billion requests.
We hope this dataset can support research on real-world LLM serving workload understanding, system design and infrastructure optimization. Explore the dataset and learn more:
Driven by our great graduate student William Nixon and
in collab with @jon_durbin @airesearch12 @chutes_ai
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Welcome to the era to decentralized post trained models that beat the frontier in their classes.
Introducing Reliquary-4B.
A 4B math & code model trained with reinforcement learning. Anyone could join the network and contribute rollouts.
Independent miners chose the prompts and generated the rollouts. The protocol verified them and trained the model.
Here’s the model and the research behind it.
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This Thursday on Novelty Search :: SOMA, SN114
@SomaSubnet is building a decentralized marketplace for AI services, starting with context compression.
Miners compete by submitting compression algorithms that make AI workloads more efficient. Validators test & score miners on the balance between compression and retained performance.
Thursday :: 5PM EDT / 9PM UTC
Live via Youtube and X
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.@near_ai’s confidential models are now available through @say_gm_ on Bittensor.
GM is becoming a gateway for private AI across ecosystems.
NEAR AI Cloud's confidential inference is now live on @say_gm_'s confidential tier.
SayGm reaches dozens of models through one API key, and runs its own routing inside an Intel TDX enclave rather than on ordinary servers.
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The Hippius mobile app is live on Android.
Your photos and files, backed up automatically and end-to-end encrypted on your phone before they ever upload.
The same account and storage you already use on desktop and web. Your whole cloud, now in your pocket.
iOS is coming next.
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Novelty Search // Bittensor Subnet 105 Beam :: The Bandwidth Subnet
Pareton miners found it, vLLM merged it.
An optimization from our Qwen campaign on #Bittensor# SN10 is now upstream in @vllm_project: ~4% more throughput at batch 4–8 for Qwen3.8 with MTP speculative decoding.
Open competition → open-source wins.
PR:
1/5
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Today, we’re announcing a solution found by our miners to both parts of Erdős Problem 14, open for over 34 years.
The result proves a square-root lower bound on exceptions to unique representation as a sum of two elements of any set of natural numbers.
Verified in Lean through Conjectures. Full proofs below.
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RedTeam is working toward integrations with three banking companies in the top 10% of the Fortune 500.
On the latest Novelty Search, @_redteam_ explains how #SN61# miners strengthen Innerworks’ cybersecurity products.
They also demo their Immune System, where AI agents created three new attacks from a miner’s submission and wrote the code to stop all three.
Hosted by @const_reborn
Full episode in the first comment
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Novelty Search :: Subnet 61 :: @_redteam_
RedTeam turns Bittensor miners into a 24/7 network of ethical hackers.
We’ll discuss how SN61 uses that competition to stay ahead of evolving bot attacks, its five new enterprise pilots, and what comes next with RedTeam’s upcoming Immune System.
Live on Thursday :: 9PM UTC :: on X + YouTube
Hosted by @const_reborn
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Recently, 5 more enterprise platforms worth $22B+ combined have been testing @_redteam_’s technology. They reach 900M+ accounts and handle 1B+ weekly transactions.
RedTeam is set to unveil a new immune system built to anticipate cyber threats.
Here’s how Bittensor powers it:
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.@theminos_ai, the team behind Bittensor SN107, co-authored a new field report with @OpenAI on agentic scientific computing.
It features HelixForge, the GPU-native engine powering the subnet’s open competition to improve mutation detection.
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This Thursday on Novelty Search :: Bittensor SN54 Yanez
@yanez__ai shows how #SN54# uses Bittensor miners to generate synthetic adversarial identity data for financial crime prevention, helping compliance teams stress-test sanctions screening, fraud detection, and KYC systems before criminals do.
Join live via Bittensor Discord.
Hosted by @const_reborn
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“All that takes is just the right incentive.”
Reliably identifying the mutations that matter for disease risk, drug response, and personalized medicine remains one of the hard problems in genomics.
On the latest Novelty Search, @theminos_ai explained how SN107 uses Bittensor to improve variant calling, the step that turns raw genome data into a reliable list of mutations.
Today, most labs run existing tools with default settings. Minos miners are already finding better configurations that improve mutation detection accuracy, while independent validators rerun and check the work every 72 minutes instead of waiting months or years for traditional scientific validation.
Hosted by @const_reborn
Full episode in the first comment
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Added to the roadmap:
Chutes, Hippius, Lium, Score, Targon, Ridges AI and Vanta.
See the full roadmap:
A Bittensor subnet just reached SOTA in open-weight AI safety.
@trishoolai’s HaloGuard 1.0 is a Qwen3.5-based model family built to catch unsafe prompts before they reach an AI model, agent, or application.
Across 7 prompt-safety benchmarks, its 0.8B and 4B models outperform much larger open guard models, with HaloGuard-4B ranking first overall among all evaluated models.
Trishool proves that with the right incentives, Bittensor can produce competitive models for some of AI’s hardest safety problems.
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We’re excited to announce that Trishool’s HaloGuard 1.0 𝐡𝐚𝐬 𝐚𝐜𝐡𝐢𝐞𝐯𝐞𝐝 𝐒𝐎𝐓𝐀 prompt-safety performance among open-weight guard models.
Today, we present HaloGuard 1.0, a constitutional input classifier for multilingual AI safety.
It is built as a first-layer input guard that checks user prompts before they reach a downstream LLM, agent, or application.
This is part of the safety infrastructure being built through @trishoolai , our decentralised AI red-teaming subnet on Bittensor SN23.
Full arXiv paper goes live soon.
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Half Zen. Half Code. Welcome to Bittensor AI Hacker House 🏯
Build where ideas become deployed subnets:
🍵 Co-live and co-code beside Lingyin Temple
🐉 Turn your @opentensor subnet into a deployed MVP
🤝 Work with top teams + on-site mentors
🏠 Selected hackers stay free | Day 1 dinner + Day 3 BBQ included
📍 Jul 7–10 | Hangzhou
Apply to build 👇
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Getting your hands on $TAO just got a whole lot easier.
#AlchemyPay# is proud to support @opentensor by adding $TAO to our fiat-crypto On-Ramp. Through our extensive global network, whether you use Apple Pay, Visa, or local mobile wallets, you can now power the future of decentralized AI with local fiat payments.
$ACH
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