$ZEC climbed ~4x to ~$1,250 in roughly a year You're probably thinking the privacy ship has already sailed, but you'd be mistaken Beyond Zcash, emerging protocols are bringing privacy to payments, trading & internet access Three names on our watchlist: 1) @NullMaskio $MASK Brings shielded transfers and swaps that obscure the trader’s identity to existing EVM wallets such as MetaMask and Rabby through a custom RPC Founded by Tomas Krnak, whose team developed shielded transaction support for Trezor, it reported $50m+ in combined deposit, withdrawal and swap volume between 1–19 October Using familiar wallets makes adoption easier, although deposits, withdrawals and swap amounts remain public, and the operator can read private balances and history 2) @UmbraPrivacy $UMBRA Supports private balances, payments and swaps on Solana, helping users protect financial information such as holdings, salaries and commercial transactions Its October 2025 MetaDAO token sale attracted ~$155m in commitments against a $3m cap, followed by its public wallet launch in March 2026 Payroll and treasury management offer practical applications, where public transactions can expose compensation, counterparties and business relationships Deposits, withdrawals and network metadata still carry privacy limitations 3) @urnetwork on Bittensor SN25 Encrypts and routes internet traffic through distributed connections, founded by former Palantir engineer Brien Colwell The existing URnetwork has reported 350K+ monthly users, with 100K+ providers being transitioned into Bittensor miners following October’s mainnet launch Bittensor adds incentives for supplying connectivity and validators that check delivery, building on an existing network and user base Each addresses a different privacy need, with different trust assumptions and token economics Our comparison looks at adoption, who pays for each service and how that activity benefits the token Follow @KhalaResearch for research on emerging crypto protocols

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.

UR is partnering with @Persistent_AI. Through its product @P_Inference, Persistent AI is joining UR as our newest Network Operator. Every AI request exposes three things about the person sending it: 1. Their identity 2. What they asked 3. Where they are connecting from Private Inference has been building private AI that solves the first two. It gives people access to leading models such as GPT and Claude without storing their chats, and lets them pay privately. UR solves the third. As a Network Operator, Persistent AI will route Private Inference's traffic over UR, where it is encrypted and sent out through connections shared by people globally, keeping users' IP addresses private. Network Operators are where demand for SN25 alpha comes from. They pay for the traffic they use in alpha, so every new operator brings new demand to the subnet. Both teams are passionate about AI and privacy, and the network is the first thing we are working on together. Keep the internet private

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

Building a world where users can protect their traffic is the right thing to do That is why UR (SN25) replaces identities with integer counters in its anonymised data exports, carrying nothing across blocks and nothing back to a real user, and verifies every route with four Ed25519 signatures that prove a live egress without ever revealing who stood at either end Self sovereign currencies and identities are congruent and unstoppable

Robotics training data needs to reflect the environments where robots will work. @haitzu on THOR’s open data marketplace at Exploit Summit: “If these robots need to be everywhere, what we need to do is to get as many people from around the world contributing that data.”

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Great piece from Shayon TL;DR: - training data is a one-off purchase per model run - agents search the web every time they act, so retrieval is the far bigger market - a lot of that traffic gets through more reliably on residential connections That's the network we've been building for the last 3 years. We have over 100k providers, giving us a diverse range of residential IPs around the world, and each one makes the network stronger Agents can already use it too, with the same benefits people get, and our MCP server makes it easy to plug in Usually, what an agent reads can be traced back to whoever is running it. On UR, that traffic is encrypted across the network, and sites see a provider's connection, not who's behind the request Privacy for humans and agents alike

Shenzhen is the home for hardware AI

Thanks OTF. The first of many wins we plan to deliver to Bittensor.

SCORE (SN44) remains one of the stand out MONSTER subnets which has been unstoppable over the last 12 months for Bittensor investors There were many who liked the name last year, but many who didn't; if everyone thought they were the best, then it would be fairly priced I find that divisive subnets are often the best investments I met Max and co last year and they had a massive chip on their shoulder he wanted to show the world what he was capable of, and he's showing it today God speed team SN44 P.S. SN44 price is up, so is our data & design capability at Khala!

“We must defend our own privacy if we expect to have any. We must come together and create systems which allow anonymous transactions to take place.” Eric Hughes, A Cypherpunk’s Manifesto (1993)

The Age of Machines Should Belong to All of Us.

In the UR (SN25) September Letter to Tokenholders, we outlined some core observations + objectives: 1) privacy is crypto's best-performing corner and the strongest moat (A16z: "privacy will be the most important moat"), UR's goal is to make privacy a seamless internet default for 1 billion people built on Bittensor 2) UR is live on mainnet, and we will be scaling our "Network Operator" franchise model, whereby SN25 token holders will have an ever increasing utility as demand scales 3) UR will grow miners ~10x (100k → 1M) via Bittensor, and we will ~50x active miners on Bittensor via our existing 100k fleet of miners. More people participating in the movement for privacy via Bittensor ur.xyz/investors/letter-to-t…

Subnet 25 @urnetwork will have more miners than the rest of Bittensor combined by a long shot (50x+) and they all strengthen the product ever so slightly. Ingenious incentive design by @xcolwell, truly a gifted builder. $TAO

No matter what they say, privacy is not the refuge of people who have something to hide, nor a premium feature to be granted to the deserving few. It is the ordinary condition of a free human life, which is why technologists have an obligation to make privacy first the mandate for the people. With Bittensor, we found a home of the people dedicated to the movement for open source software It is the worthy place to chase the dream of individual ownership and freedom via new privacy first protocols At UR (SN25), I will help the team shape further products dedicated to this mission