Rayah τensor τ_τ

Some partnerships scream Some just make sense The integration between Subnet 22 @desearch_ai and Subnet 93 @Bitcast_network falls into the second category Bitcast V2 on X now runs on Desearch’s API for real-time, structured X data Which means: • Replies verified properly • Retweets counted accurately • Engagement measured programmatically • Less scraping duct tape In simple terms: Bitcast pays creators in $Tao for real attention. To do that fairly, you need real data Not vibes Not inflated metrics Not "trust me bro, the scraper said so" Desearch provides structured, validator-level signals instead of brittle scraping pipelines. So campaigns become: • More auditable • Harder to game • Less dependent on centralized data providers It’s one of those upgrades that sounds boring Until you realize that “boring infrastructure” is what keeps incentives honest There’s also something very Bittensor about it Subnet 22 (AI-powered search & data infrastructure) feeds into Subnet 93 (decentralized creator marketing) Instead of paying external APIs forever, value loops inside the network Clean data → fair rewards → better campaigns → more demand → stronger subnets No fireworks No dramatic slogans Just decentralized search quietly powering decentralized marketing Sometimes the biggest flex isn’t hype It’s replacing fragile tools with infrastructure that doesn’t break every time X changes something.

This is actually impressive. $Tao subnet 51 @lium_io just hit $2.32M in GPU spend for October (up 74%), and daily volume doubled to around $100K Real momentum🚀

Buying $TAO today might look expensive to someone looking at the chart. So did buying SOL at $10 The market rarely gives you a comfortable entry into something that changes the game

AI has spent years moving into the browser. But running a capable model there, without sending every prompt to a remote server, is a different challenge. That's what makes @TPN_Labs 's Gratis launch interesting. 🔹 The distribution angle Gratis brings open-source AI models directly to the browser and desktop. No account is needed, and browser users don't need to install anything. Inference happens locally, so prompts stay on the user's machine. That removes several barriers between discovering an open model and actually using it. 🔹 The Bittensor connection is what makes this more interesting. $Tao SN65 focuses on compressing models while preserving their quality under strict memory constraints. Gratis puts that work closer to everyday users. The browser memory expansion to 16GB using 64-bit WebAssembly is an important part of making this practical. The interesting question isn't just how small an AI model can become. It's how easily people can access and run it. TPN is connecting model optimization with actual distribution. Because an open model is only truly accessible when people can run it.

If you're afraid of buying $TAO, drop your best dad joke in the comments below @Jason 's post and win $420. Then use that money to buy 2 $TAO 😂

$TAO subnets are quietly doing more interesting work than 90% of “AI coins” with bigger market caps It can easily do 10-20x from here

The longer $TAO stays quiet, the more interesting the next move gets

$TAO is being accumulated in silence

Bittensor $Tao subnets just reached an estimated $70M annualized revenue (+100% in two months). Compute and inference are leading the growth, with $100M+ expected by year-end.

Bittensor $Tao subnets just reached an estimated $70M annualized revenue (+100% in two months). Compute and inference are leading the growth, with $100M+ expected by year-end.

Bittensor $Tao subnets just reached an estimated $70M annualized revenue (+100% in two months). Compute and inference are leading the growth, with $100M+ expected by year-end

AI detection has a problem beyond identifying machine-written text. What happens when genuine human writing gets flagged as AI-generated? For a student, that false positive can be much more serious than a wrong percentage on a dashboard. That's the problem It's AI is trying to address on $Tao (Bittensor) SN32 🔹 Accuracy is only half the story. It's AI ranked first by average ROC-AUC in the MGTD benchmark (ICAIE 2025), evaluated across 15 datasets and approximately 2 million text samples. Its latest multilingual evaluation adds another interesting result: • Arabic: 99.8% accuracy • German: 99.5% • French: 99.4% • Spanish: 96.0% False-positive rates remained below 1% across these four evaluated languages. 🔹 The product goes beyond a single AI score. It provides sentence-level classifications, word-level highlights and Deep AI Scan to examine mixed human and AI writing. It also supports document uploads, Chrome Extension and Canvas LMS integration. The interesting part is that SN32 miners compete to improve the detection models, while the output powers a product used in real educational and professional workflows. Detecting AI writing is useful. Avoiding false accusations is just as important. That's the distinction worth watching with @ai_detection

Open-source AI has an interesting contradiction. The models are free to download, but running the good ones can require hardware most people don't own. @TPN_Labs is trying to change that with SN65. 🔹 The engine TPN runs competitions where miners compress AI models under fixed memory limits while maintaining quality. Submissions are tested against sealed benchmarks, and winning models are published openly. 🔹 Now comes Gratis. Launched on November 2, Gratis lets anyone run open-source AI models directly in a browser or desktop app. No account or installation required for browser use. Your prompts stay on your machine rather than being sent to a server. The technical detail is interesting: TPN extended browser inference memory from the usual 4GB ceiling to 16GB using 64-bit WebAssembly memory addressing. The bigger picture is what I like: $Tao SN65 works on making models fit accessible hardware. Gratis gives people a way to actually use them. A subnet producing models is interesting. A subnet producing models and shipping an app where anyone can run them is a much more tangible result. Try it: gratis.trueperformancenetwor…

Kill switch for agents? That’s why we need bittensor:native

One clean move on $Tao changes a lot of portfolios

Real Utility in AI is rare. $Tao has a shot

$Tao is one of the few alts with a real long term story