Every decentralised AI network has the same unsolved problem.
How do you trust compute you don't control?
Most projects punt on it relying on Intel, AMD or NVIDIA to vouch for the hardware. That's not decentralisation. That's just outsourcing the trust problem.
@verathos_ai (SN96) has done what nobody else has managed, built a verification system that cryptographically proves AI computation was performed correctly, on any hardware, without needing to trust the machine it ran on.
No secure enclaves. No approved vendor lists. Just math.
That's a first. And it's live on Bittensor.
Humans see a stop sign. An attacked AI model might
see a speed limit sign. That's not science fiction — it's
adversarial machine learning. @perturbaix (SN26), built
by @knakamor, is the Bittensor subnet building the
security layer for AI perception.
$TAO @opentensor
→ https://t.co/t82igsARta
ReadyAI Revenue Dashboard is Live 🚀
Real-time demand for SN33's structured data pipeline
Starting today, anyone can watch demand for ReadyAI's structured data pipeline as it happens. Revenue, jobs, quotes, and tags produced. Data straight from the Subnet 33 Jobs API is refreshed every 8 hours,
The Early Signal
Exactly what we hoped for. Direct ReadyAI revenue is on a five-figure ARR pace and the curve is steepening week over week.
The Jobs API is open. Beyond our existing enterprise feeds, we're starting to see organic customers find it and plug in on their own. Submit data, pay in USDC over a single HTTP call, get structured output back.
What This Means for Alpha Holders
75% of this revenue goes directly to buying back SN33 alpha from the open market. Every job that flows through the pipeline, enterprise feed or organic API user, funds a buyback for the foreseeable future. All on-chain, all verifiable.
The dashboard you're looking at is the same demand that drives the buyback.
Dashboard: https://t.co/UXiAJ4Qk8P
Back to building. Got some exciting news coming on our coding data pipeline and benchmarks to share shortly.
Docs and endpoint details for the API is available here: https://t.co/3T7sPeDTzH
We are releasing the first product from https://t.co/QHy1SZQAPe.
Deep Research. Image generation. Web search. URL fetching. Python sandbox execution. RAG over your own document corpora.
Powered by multiple model families: DeepSeek, Kimi, MiMo, GLM, MiniMax, and more.
The difference is the tool stack.
Eirel is backed by owner-routed tool services, so agents can search, fetch, compute, verify, retrieve, and reason across real documents.
Plans start at $10/month:
Plus:
- 500 messages/day
- 20 images/day
- 10 deep-research runs/month
- 10 agent runs/month
Pro:
- 1,000 messages/day
- 60 images/day
- 30 deep-research runs/month
- 30 agent runs/month
- Scheduled agent tasks
Max:
- Unlimited messages
- Unlimited images
- 300 deep-research runs/month
- 300 agent runs/month
- Unlimited projects, storage, and memory
- Flexible AI infrastructure.
Serious model access.
Much cheaper than ChatGPT.
Try it: https://t.co/JRiQEwN6a1
$TAO #Bittensor
Hash Rate - Ep. 172: Minos Subnet 107
🧙 Guest: @centrum_blue of @theminos_ai
02:27 The Challenge of Private Genetic Data
07:04 The Mutation Detector
10:59 Synthetic Genomes
14:21 The Role of Miners
22:27 Why Subnet?
26:29 Competitive Landscape
29:53 Synthetic Genomes and Digital Twins
34:00 Tokenomics
46:31 Marketing
48:51 Mamad's Journey and Vision
Most people are trying to find the next Bittensor subnet runner by guessing.
That is exactly why I made this AlphaGap masterclass.
I walk through how I use @AlphaGapTAO to track subnet momentum, AGAP score, watchlists, and where alpha might be hiding before everyone starts screaming about it.
Also wild to say this, but I am officially the first ever AlphaGap ambassador.
My community gets 10% off through ShizzyUnchained dot com.
Full tutorial below, this one is for the people actually trying to learn how to get an edge.
bittensor:native #Bittensor
Road to 100 TAO: Week 2
In week 2 of the Road to 100 TAO Challenge, I break down the current market conditions, review the portfolio, and explain the changes I made to reduce risk while still keeping upside. I walk through what I removed, what I added, and why safety matters when rotating through Bittensor subnet alpha tokens. This episode is about staying focused, protecting the stack, and making smarter moves on the path to 100 TAO. Check out ShizzyUnchained dot com for more.
CHAPTERS
00:00:00 Road To 100 TAO Challenge Intro
00:03:16 Understanding Market Conditions
00:04:50 The Current Portfolio
00:05:45 Making Portfolio Changes For Risk And Safety
00:09:03 Deep Dive Into Why I Made These Choices
00:13:03 The New Portfolio
00:14:05 Check Out ShizzyUnchained dot com
#Bittensor bittensor:native
🏠 Subnet Spotlight: @resilabsai - Subnet 46
Real estate data is one of the most locked down industries on the planet. Accessing a comprehensive national property database can cost upward of $250,000 per year. The data is fragmented, expensive, and deliberately protected by incumbents like Zillow and CoreLogic.
RESI (Real Estate Super Intelligence) is building the alternative.
Here is what Subnet 46 is actually doing:
Miners compete to collect and verify data across 150 million+ US properties, tracking 100+ attributes per property in real time. A blind consensus mechanism ensures data accuracy without miners being able to coordinate or game the system.
The first AI model live on the subnet is a property appraisal model, providing verifiable on-chain valuations for DeFi protocols, tokenisation platforms and real estate lenders. The pricing oracle targets a $500 setup and $100/month model, compared to the tens of thousands traditional providers charge.
The public dashboard at https://t.co/X42G5H3Wwo lets anyone see exactly which model generated a valuation and how. Full transparency. No black box.
Revenue is already generating through https://t.co/gwPXKuWsSD, their predictive lead generation product for realtors. Institutional investors including a publicly listed company have taken positions in the subnet.
Long term, RESI is building toward on-chain real estate lending, prediction markets, and a real estate backed stablecoin.
The infrastructure is being built quietly. The attention has not caught up yet.
It will. 👀
Hot take: the AI compute wars will be decided by storage.
Model weights. Training datasets. Inference logs.
All of it needs cheap, fast, reliable storage that doesn't call home to Amazon.
That's the market Hippius is built for.
https://t.co/a48iG1CRj6
#AI $TAO #SN75
Zillow has a $10B market cap and still can't tell you what a property is actually worth with any real precision. their estimates are notoriously off and they've never had a financial incentive to fix that they make money on leads, not accuracy.
@resilabsai (Bittensor SN46) is building the thing Zillow never bothered to. a decentralised property appraisal AI that's already hitting 98.6% accuracy nationwide - faster, cheaper, and more accurate than human appraisers. no company owns it. no one can manipulate it. it's open source and verifiable.
1,000+ appraisals already run. live pilots with Flyhomes and Balcony. backed by NVIDIA. this one is early and worth paying attention to 🏠👀