Gyles | TAO.com retweeted
Bittensor unveils quantum-resistant wallets.
As AI renews debate over cryptographic security, the update gives users post-quantum signatures and the option to replace signing keys automatically.
Gyles | TAO.com retweeted
Introducing IOTA Decide 4B, our first public model.
Pareto optimal. Built different.
Trained across globally distributed GPUs with our SDK.
Open weights, Apache-2.0.
🤗 huggingface.co/macrocosm-os/…
Gyles | TAO.com retweeted
Bittensor bittensor:native ecosystem is on fire. Revenue run rate is growing 40% month over month
$35M → $50M → $70M.
Another month, another 40% MoM increase in annualized revenue across the Bittensor ecosystem.
When we published the first SubConnect Bittensor Revenue Index, we estimated that revenue-generating subnets were collectively doing around $35M in annualized revenue.
A month later, that number had grown to approximately $50M.
Today, we're estimating $70M in annualized revenue.
That's a 100% increase in just two months.
Of course, annualized revenue is a snapshot, and the real challenge is sustaining that growth while improving margins and reducing dependence on emissions, but the direction is clear.
Bittensor is growing from the inside out.
And our expectation of $100M+ in annualized revenue by the end of 2026 is getting closer.
We'll continue tracking the numbers every month through the SubConnect Bittensor Revenue Index.
Gyles | TAO.com retweeted
Mainnet update:
We have been working towards mainnet for quite some time, and we want to be transparent about what was happening behind the scenes.
Getting this right was always more important than getting it done fast. Forge is built to handle real capital, and that requires a strong foundation that has been fully reviewed and secured.
We worked closely with @taodotcom throughout this process. While Forge was being audited, tao.com conducted a broader audit on their wstAlpha wrappers and the underlying BittensorEVM stack, providing solid ground to build DeFi in the Bittensor ecosystem.
The audits flagged specific items, all of which were addressed before moving forward.
None of this would have been possible without the excellent work of the tao.com team. We’re glad to have them as partners.
Now, Forge is ready to start the countdown to mainnet.
Gyles | TAO.com retweeted
We have just repurchased and burned 1,772 TAO (~$445K) of SN4 alpha using organic revenues generated via Targon.com
We have also burned an additional 6,678 TAO (~$1.7M) worth of SN4 alpha, which also represents revenue generated via Targon
Gyles | TAO.com retweeted
If everyone has access to better AI models, what do contributors compete on?
How well they use them.
Models like GPT-6 Astra and NVIDIA’s Flora are getting much better at labelling robotics video. NVIDIA estimates inference compute costs below $1 per hour of footage for Flora.
But customer-ready data has to meet timing, description and quality requirements. Verification and rework carry costs too.
On Bittensor Subnet 112, THOR is designed to tie rewards to verified output, giving contributors an incentive to improve their models, tools and workflows. A better workflow raises the bar for everyone.
The test for THOR is whether that competition delivers reliable robotics training data at a lower total cost.
Better AI expands what’s possible. Competition makes it count.
Gyles | TAO.com retweeted
500,000+ hours of raw video behind one robotics model. A city subsidising companies' data purchases.
China's robotics data work is turning into a supply chain.
This is THOR Signals, our new series on the robotics data market, starting with China.
For context, China accounted for 59% of global industrial robot installations in 2025. Within that industry, three roles are taking shape:
• @beingbeyond_: model development
BeingBeyond builds models that help robots understand their surroundings and perform physical tasks. For Being-H0.8, the model behind those 500,000+ hours, raw video was filtered, reconstructed and reviewed before training.
• @PaXiniAI: specialist data supply
PaXini makes tactile sensors and training data combining vision, touch and movement. BeingBeyond names it an important data partner for Being-H0.8.
• @LightwheelAI: connecting training with deployment
Lightwheel supplies simulation, demonstration data and evaluation, and reported about $100M in Q1 2026 orders. At automaker Geely, factory demonstrations feed training, and testing shows where more data is needed.
Government is shaping demand too. Hangzhou's 2026–2027 action plan subsidises companies' purchases of data products and services (up to 30%, capped at RMB300,000). The national pilot base there invited outside data partners on 30 September across 25 task scenarios.
What we don't know yet: how much teams outsource, and which services they buy repeatedly.
For THOR, that's the question: which tasks do teams commission externally, and why choose a specialist over building in-house?
More from THOR in China to come.
THOR Signals · China
Gyles | TAO.com retweeted
The swarm just got faster.
We've eliminated one of decentralized training's biggest bottlenecks, speeding up merging by 5x.
We're redefining the shape of AI training.
Introducing the latest evolution of IOTA.
Gyles | TAO.com retweeted
Most startups don't make it to the 5 year mark
We have already been around for 3 years and are focused on building something that's useful for every day users, while being sustainable
"We've already gotten to a million networks... let's get to 10 million in the next year"
Our mission is to build a success story around privacy encryption infrastructure that works
Gyles | TAO.com retweeted
Robots have no equivalent of the internet to learn physical work from.
THOR’s mission is to build that foundation in the open.
Annotation is where that journey begins.
Read our manifesto:
thormachines.ai/manifesto/
Gyles | TAO.com retweeted
Bittensor shares many of our values at UR
Open source and self sovereignty are core beliefs
This is a big reason why we are excited to be building here
"the same energy and resources that go into controlling the people needs to go into the technology that helps the people"
Gyles | TAO.com retweeted
$NEAR made $2.2M in revenue last month which is $26M ARR
Market cap is $7B
SN51 lium made $1.4M in revenue last month which is $17M ARR
Market cap is $180M
$TAO is an ecosystem which has several subnets like lium earning millions in ARR and Bittensor as a whole has a total ARR of $50M+
Market cap is $3B
What am I missing here?
Gyles | TAO.com retweeted
NEW: @SynthdataCo has added Volatility CRPS to Bittensor Subnet 50’s Crypto 1h competition. It directly scores volatility implied by each model’s simulated price paths.
teapawt.net/SynthdataCo/status/210…
1/ Introducing Volatility CRPS Updated
As we continue our mission to build the world’s most accurate financial forecasts, we’re introducing a new scoring mechanism to our competition:
Volatility CRPS is now live in the Crypto 1h competition, directly scoring how accurately each model forecasts the volatility implied by its simulated price paths.
Read on to learn how this update directly improves Synth's trading performance
Gyles | TAO.com retweeted
Where does Bittensor go from here?
Live now on the OTF stage: @micaelabazo, @KibibyteMe, @gylez and @jon_durbin join moderator @GSchvey for “Where Do We Go From Here?” Watch the closing panel: stream.vidaio.io/?event=51cb…
Gyles | TAO.com retweeted
we will need compute (@lium_io, @TargonCompute)
we will need inference (@engyai, @chutes_ai)
we will need data (@Hippius_cloud)
we will need knowledge (@teutonic)
If we are going to have free intelligence (@affine_io)
Gyles | TAO.com retweeted
If you are reading this, the only possible resistance is to build decentralized, permissionless, and sovereign AI.
Open source, self-hosting tools, RL post-training, local inference, open harnesses, we must build it all.
We must fight overcentralization with an open stack.
