τTaosisTaoScale

Bittensor subnet news

Subnet teams' own channels, X posts, press, newsletters and events read from the chain — GitHub lives in its own tab

Taosis newsletters

Taosis News: the week’s articles from the subnet teams, the press and community newsletters, every Friday. Taosis Weekly: the week’s movers, best yields and chain events, with dollar values, every Monday. Past issues

Newsletters

Your address is used only to send the newsletters you tick, with your consent (double opt-in). Unsubscribe anytime · Privacy

CommunityX87SN871h ago
Will O'Brien@willobrien

From Bitcoin custody to assurance for AI agents: how do we know they did the right thing? Thank you @BitcoinNews and @2084Richardson for the conversation at @ExploitSummit on trust infrastructure, @provenonce_ai and SN87 on Bittensor.

Quoting @BitcoinNews

🤖 AI agents can do the work. But who checks the work? @willobrien, CEO of @provenonce_ai tells @2084Richardson at @ExploitSummit why the “assurance gap” could determine whether enterprises trust autonomous AI. If AI starts checking its own homework, who checks the checker? 👀

Full post on TaosisOpen on X ↗

OfficialX28SN281h ago

Using Claude, GPT or Gemini with client details in your prompts? Turn on guardrails in SayGM desktop. Detected emails and phone numbers are swapped for placeholders before the model sees them, and restored in your reply.

Full post on TaosisOpen on X ↗

OfficialX44SN441h ago

Old world: → Computer vision companies siloed their own data and tools, spending months or years solving niche problems. Progress was fragmented and negative-sum. New world (SN44): → Detectors and segmentation models are improved fully open-source, building the largest and most efficient computer vision model library in the world, available instantly, via app or on Hugging Face. The issue was never a lack of data, talent, or technology. It was misaligned incentives. Once those incentives align around open collaboration, the entire vision AI ecosystem compounds instead of competing.

Quoting @i_compounding

$TAO A few days ago I said the use cases were everything we can see in the viewable universe. The answer is everything we can view. Probably leading to almost everything we can’t see. @webuildscore twitter.com/oblock107/status/2117449213294280980

Full post on TaosisOpen on X ↗

Terza Inference now accepts images on text models. Send screenshots and photos to Claude, GPT, Gemini, DeepSeek, GLM, Kimi and Qwen through the same API, in both OpenAI and Anthropic formats. Works in Claude Code too. Models that can't read images now return a clear error. No charge for rejected requests.

Full post on TaosisOpen on X ↗

OfficialX7SN76h ago

Security on Allways: nobody holds your funds. You send from your own wallet and receive native assets in your own wallet. The operator filling your swap has collateral locked before you send. No wrapped tokens. No bridges. No custodian.

Full post on TaosisOpen on X ↗

byteleap.ai@byteleap_ai

Null consensus is a trade-off. Once a subnet opts in, the top-staked validator sets all weights. Others still earn dividends pro rata, and slots rise from 256 to 2,500. It trades weight competition for scale, at the cost of concentrated power. Best for deterministic scoring.

Full post on TaosisOpen on X ↗

Things are getting very interesting in the AI x engineering space 👀

Quoting @spisallyouneed

Very proud to showcase our latest demo of how our Engineering World Model SKY-001 can design a complex Jaguar car with 1000s of complex parts. In order to get us to Autonomous Manufacturing, we need to design systems that can think like a ‘AI General Engineer’: planning complex physical structures, long term sequences, and feasibility directly in the physical domain rather than approximating it through next-token prediction. Engineering design operates in the spatial reasoning domain through hierarchical decomposition, constraint satisfaction, and the sequential construction of complex physical objects. World models are going to be the next frontier in AI after LLMs and SKY-001 is just the beginning.

Full post on TaosisOpen on X ↗

OfficialX2SN210h ago
DaniLabs@danilabsai

Getting an AI application working is just the beginning. Keeping it practical as usage grows means keeping inference costs and response times in focus. Those priorities guide DaniLabs as we build AI inference on Bittensor.

Full post on TaosisOpen on X ↗

OfficialX65SN6510h ago
True Performance Network@TPN_Labs

TPN Labs episode with @ShizzyUnchained and @0xDutchmikel coming tomorrow🐰

Quoting @ShizzyUnchained

The AI you want. The hardware you actually own. Can TPN bridge the gap? Tomorrow I’m live with Mikel from @TPN_Labs, Bittensor SN65, to unpack model compression, benchmark tradeoffs and running AI yourself. Tuesday, November 3, 2026 11:30 AM ET / 8:30 AM PT Set a reminder and bring your questions: youtube.com/watch?v=1ajAfGr_dh0

Full post on TaosisOpen on X ↗