Bittensor (TAO)

Kraken just put 7 Bittensor subnet alpha tokens on their official listings roadmap. Targon. Vanta. Score. Lium. Ridges AI. Chutes. Hippius. This is the first time a major CEX has moved beyond $TAO to offer direct access to individual subnet economies. Alpha tokens were built for on-chain participants. Kraken brings them to everyone else. The addressable market just got a lot bigger. Watch for the official announcement on @KrakenListings before moving. Roadmap inclusion is not a live listing yet. But the direction is clear. Save this post.

$TAO is one of the few AI projects where it’s really realistic it will become a Top 10 project. Hundreds of Teams and the most talented DEVs will build on Bittensor. Building the Decentralized AI Infrastructure.

🚨 BREAKING - TAO LISTING: OKX, one of the world’s largest CEX by trading volume, has announced it will list $TAO for spot trading. Trading is scheduled to go live on June 30 at 1:00 PM UTC. Another step toward broader institutional and retail access. https://t.co/XKYtsvfZXj

$TAO Bittensor SN32 It's AI is getting more specific than a generic AI detector. The interesting part is the product path. @ai_detection already has AI text detection, OCR support for scanned documents, a Canvas plugin for schools, and now a BitMind partnership that brings text detection into a platform already focused on image and video detection. Better than another broad "AI detection is important" pitch. Schools need it inside the LMS. Publishers need it inside their review process. Platforms need text, image and video checks closer together. The market question for SN32 is simple. Can AI detection become a layer inside normal workflows instead of a website people visit once? What do you think about that?

Everything you need to know about $TAO Bittensor SN91. SN91 is Cascade, a @bitstarterAI backed subnet aiming to train time series foundation models on Bittensor. The idea is simple enough to understand and hard enough to matter. - Time series are everywhere. Markets, public health, weather, infrastructure, energy, logistics. A lot of the world is time, sequence and change. - Current LLMs are strong at language, but weak at temporal structure. The missing ingredient is better time series data. - SN91 is built around that bottleneck. Miners are expected to generate synthetic time series data that can improve model training. - The pretraining process stays fixed. The competition is about producing better data for that process. - Validators score checkpoints on held-out windows and downstream performance. The practical question is whether the model actually gets better at forecasting. - The design is shaped by @const_reborn and follows a king-of-the-hill style competition. High pressure, clear scoring, no vague participation trophy. - The team is @tensorlink_dev on the core build and @macrozack on strategy and communications, with Bitstarter around the launch path. - Miner emissions are not active yet. Burn is currently 100%, which under the latest protocol means 0% emissions until the subnet is ready to use miners. - They intend to use Conviction and alpha buybacks, but want to calibrate tokenomics before announcing the on-chain commitments. - The crowdfund, if it happens, may be different from the usual discounted alpha model. The idea being discussed is shards of the Owner Key, giving pledgers exposure to future emissions. My read. SN91 is interesting because the market is not small. Better time series models could matter for trading, supply chains, climate, public health, grid demand, insurance, infrastructure and any system where the next state depends on the last thousand states. The risk is execution. Synthetic data has to improve the model, validators have to score it cleanly, and miners have to become useful from mainnet. If that loop works, SN91 becomes much more than a launch narrative. A universal forecaster built on $TAO Bittensor is a big ambition. This is the kind of ambition Bittensor should be testing. SN91 AMA is scheduled for Wednesday, July 1. If you care about subnets before they become obvious, this is one to study early.

🚨 @bitsecai #SN60 beats Mythos 🤯