Buystakechill.eth

"Buy Stake Chill" - NFA- DYOR. Purely my understanding, my knowledge, my opinions, Tao is a force. Inevitable. Dont wait to buy tao, buy tao and wait.

[Buystakechill.eth @taobittensor2]

@JesusMartinez $1000 - $1250 is genuine target. $3000 is bullish

[Buystakechill.eth @taobittensor2]

Erik Voorhees @ErikVoorhees & Venice @AskVenice just tuned their new Uncensored 1.2 (Mistral 24B base + vision, 4x context, stronger tools) on Targon SN4 secure, confidential high perf GPU compute with TEEs.

This is real, frontier model fine tuning moving off centralized clouds onto permissionless, decentralized hardware. No single point of failure, no censorship gatekeepers, full privacy for sensitive training runs….

Big Tech’s closed stacks can’t compete on openness + cost + trust…. $TAO SN4 @TargonCompute delivering production grade secure compute today….

Decentralized AI just got another elite builder. Massive validation.

@opentensor is a happening ecosystem.. vibing and thriving.. new day.. new achievement… bring it on 🔥 🔥 🔥

#TAO #SN04 #Targon

[Erik Voorhees @ErikVoorhees]

We've started working with some Bittensor subnets.

New Venice Uncensored 1.2 model was tuned on Targon/subnet4

[Buystakechill.eth @taobittensor2]

Conviction staking on $TAO (BIT-0011 proposal):

1. Stake TAO on any subnet
2. Choose lock period (longer = higher multiplier)
3. Conviction = Stake × Lock Time
4. Highest conviction wins subnet control/ownership

This forces real skin in game. No more quick dump validators or rug prone teams. Long term alignment baked in…

Rollout starts Q2 2026 on SN3, SN39, SN81 post-governance vote….

Game changer for decentralized governance.

Lessons learned.. @tplr_ai @basilic_ai @grail_ai @covenant_ai and now,

Fixing the loose ends…. Game changer for decentralized governance….

This is how $TAO levels up…. Sky high conviction incoming…. 🤟

@opentensor #TAO

[Buystakechill.eth @taobittensor2]

Score SN44 @webuildscore just landed a major enterprise win: PwC France + Maghreb partners with @manakoai to turn real world cameras into operational intelligence on Bittensor.

This isn’t retail hype… it’s decentralized vision AI moving from observation to automation at industrial scale. Permissionless CV layer processing video feeds via open models, delivering low latency insights without centralized bottlenecks…..

Big Tech closed platforms can’t match this speed and cost on distributed infrastructure.

SN44 proving enterprise grade utility in 2026.
Real adoption signal for $TAO.

Way to go onwards and upwards 🤟

[Score - Subnet 44 @webuildscore]

Score x Manako x PwC France

[Buystakechill.eth @taobittensor2]

My bad. SN66 Ninja is a coding agent … previously a devops subnet when it was named under alpha core .. which was de registered and the new subnet ninja was indeed a coding agent..

SN62 and SN66 both are coding related, but not the same.

SN66 Ninja: Pure coding agent duel. Miners compete head to head on real GitHub repos (write, debug, refactor code). “Survival of the fittest” …. winner takes all emissions.
To build the best open source coding agent in the world.

SN62 Ridges: Autonomous coding + agent infrastructure (Ridgeline). Focuses on full agent evaluation, scaling, and software development workflow….

Thats the difference…

[Buystakechill.eth @taobittensor2]

Just a correction

Ninja = infrastructure/operations automation.
Ridges = pure code writing. ( Development)

Not the same.

SN66 Ninja: Agent led DevOps automation (Arbos) Focuses on autonomous deployment, maintenance, CI/CD pipelines etc… full DevOps agent…….

SN62 Ridges: Autonomous coding agents (Ridgeline). Focuses on code generation, bug fixing, software development tasks.

In other words, They both go hand in hand… works together ..

[Buystakechill.eth @taobittensor2]

Remarkable ambition.

SN24 Quasar is tackling two hardest AI problems at once:
• Ultra long context (millions of tokens) with efficient linear attention.
• Decentralized MoE (Mixture of Experts) training for massive models.

They want to do both on Bittensor’s open network, very hard, high risk, high reward.
Ultra long context needs massive memory/compute.

Mixture of Experts (MoE) splits the model into smaller “experts” so only a few activate per token this keeps inference/training efficient even at millions of tokens….

Quasar is combining both: efficient linear attention + MoE for cheap, stable ultra long context models.
That’s why the tech is ambitious

@QuasarModels #SN24 #TAO 🤟

[τroy @TroyQuasar]

Quasar mission is now twice as hard, and that’s what makes us special

We’re not just solving the hardest problems in AI, like memory, but also tackling MoE decentralized training.

And the funny part is we have a path for both we’ll utilize every bit of power from Bittensor

[Buystakechill.eth @taobittensor2]

@TroyQuasar Lost a significant $TAO today from staking to SN24 Quasar.. but I can’t give up on @QuasarModels so easily.. what happened is really frustrating.. but I believe in @const_reborn and @QuasarModels team.. looking forward 🤝

[Buystakechill.eth @taobittensor2]

@ShizzyUnchained Sorry to hear mate. RIP

[Buystakechill.eth @taobittensor2]

@KeithSingery Please pay us.. we can buy more $TAO thank you 🤣

[Buystakechill.eth @taobittensor2]

Wow .. What a crazy run … SN97 Constantinople !!!! 🔥 🔥

215% in a matter of minutes. 🤯 Crazy ride

In the future, all Bittensor subnets will be agent led !??? 👀

#TAO #SN97 #Constantinople

[Buystakechill.eth @taobittensor2]

Intel + Targon dropping confidential TEE whitepaper just broke the game.

Decentralized GPUs now run enterprise grade private AI workloads on untrusted hardware.

Privacy moat locked. SN4 is about to moon.
This is the alpha. 🔥 🔥#TAO #SN04 #Targon

[Intel @intel]

Advancing confidential computing for a more secure AI future.

Together with @manifoldlabs, we’re exploring how Intel TDX and Intel Trust Authority help enable confidential workloads across decentralized infrastructure, including @TargonCompute's Targon Cloud platform—protecting data at rest, in transit, and in use.

[Buystakechill.eth @taobittensor2]

@ShizzyUnchained Great portfolio… SN46 RESI would be a great addition.

[Buystakechill.eth @taobittensor2]

Decentralized AI on $TAO explained like building a super smart robot together:

@tplr_ai SN03 Templar , thousands of home GPUs train massive models (like 72B) from scratch.

@IOTA_SN09 splits the work across machines like a team passing a ball.

@Data_SN13 gathers fresh web stories & data as raw material.

@GrailBittensor SN81 uses rewards to fine tune reasoning like puzzle practice.

@desearch_ai SN22 adds real time smart search from X/web/Reddit.

Raw data → distributed training → smart search → RL improvement = full open AI stack.

This is how Bittensor builds intelligence without Big Tech. Mind blowing.

#TAO #Bittensor #decentralised #intelligence

[Buystakechill.eth @taobittensor2]

NVIDIA’s $30T AI factory ramp in 5 years means TAO wins big with decentralised compute becomes the affordable, open alternative.

Here is Why: Massive centralized compute growth (50 ZettaFLOPS, 100M+ GPUs) will explode AI demand and costs. Bittensor’s decentralized subnets can capture a slice by offering cheaper, open, incentivized alternatives for training/inference, thus driving more miners, stake, and TAO locking and demand. #TAO

[JJ @JosephJacks_]

Over the next 5 years, NVIDIA will ship ~100,000 AI factory PODs across 4 chip generations.

Each generation is 3-14x more powerful than the last. The annual cadence is relentless:

• Vera Rubin (2026): 60 exaflops/pod

• Rubin Ultra (2027): ~220 exaflops/pod

• Feynman (2028): ~600 exaflops/pod

• Feynman Ultra (2029): ~1,200 exaflops/pod

Blended across the full ramp, that’s ~50 ZETTAFLOPS of aggregate compute deployed globally. 100M+ GPUs. Billions of dies.

System ASPs climb each generation — more HBM, denser packaging, liquid cooling at scale.

If demand holds, it is realistic that NVIDIA will generate $30 TRILLION in revenue with gross profit margins of~75%!

Thats more profit than U.S. GDP.

[Buystakechill.eth @taobittensor2]

“When energies align, the universe puts you exactly where you belong.”

Just be present and act !!

$TAO is that action 🚀 @opentensor 🤟

NFA, DYOR.

#TAO

[Buystakechill.eth @taobittensor2]

Interesting Read…! Promising if delivers

[Buystakechill.eth @taobittensor2]

Yes.!! 🙌🏻

[Pedro Domingos @pmddomingos]

TSMC is the Strait of Hormuz of AI.

[Buystakechill.eth @taobittensor2]

$TAO at $305 decoupling from $ETH at $2143.

While ETH moving sideways on L2 fragmentation + macro drag, TAO surges on real utility: Yuma consensus powering 72B+ decentralized pre-trains, autonomous subnets (SN97 agent-led), confidential inference (Targon SN4), serverless GPU (Chutes SN64), Autonomous coding (Ridges SN62), decentralised storage (Hippius SN75) and many many more. A swarm of subnets

This isn’t altcoin beta, it’s structural alpha. Decentralized intelligence escaping centralized MoE scaling walls.

TAO/ETH ratio breaking out. Narrative flip incoming.

#TAO #ETH

#TAO top10 is coming sooner than expected.

[Buystakechill.eth @taobittensor2]

Chamath drops Covenant-72B on All-In podcast with Jensen Huang on largest fully decentralized pretrain ever: 72B params, 70+ heterogeneous nodes over commodity internet, no central coord, pure Yuma consensus + incentive alignment.

Jensen nods to the physics: commodity clusters beating centralized MoE scaling walls.

This isn’t hype; it’s the Yggdrasil moment for permissionless frontier training. $TAO SN3 just proved the thesis.
#TAO #SN3 #Templar
Bullish AF !!🔥

Buy Stake and Chill !!! $TAO

[templar @tplr_ai]

On the @theallinpod this week, @chamath asked @nvidia CEO Jensen Huang about decentralized AI training, calling our Covenant-72B run "a pretty crazy technical accomplishment."

One correction: it's 72 billion parameters, not four. Trained permissionlessly across 70+ contributors on commodity internet. The largest model ever pre-trained on fully decentralized infrastructure.

Jensen's answer is worth hearing too.