Alphaco1n

To Protect The Sheep You Gotta Catch The Wolf, And It Takes A Wolf To Catch A Wolf

[Alphaco1n @Alphaco1n]

@LibOrNormal Lucky him

[Alphaco1n @Alphaco1n]

@GunnerPuls James 🇨🇴

[Alphaco1n @Alphaco1n]

@Kaaiii29 The player who has scored the most direct free kicks in the history of professional football is the Brazilian Juninho Pernambucano, with an official total of 77 free-kick goals. Messi is second with 72

[Alphaco1n @Alphaco1n]

@nicolas_vilas Le but de l’équipe de France est de performer. Peut importe si ce sont des femmes ou des hommes. Le staff choisit est juste le meilleur donc les femmes doivent s’améliorer si elles veulent postuler

[Alphaco1n @Alphaco1n]

@DenisEstelle le but est de performer, on n'est pas au service publique

[Alphaco1n @Alphaco1n]

@npelletier18 @RMCsport ohh Fabien dans le staff

[Alphaco1n @Alphaco1n]

@FabriceHawkins This is going to be the worst transfer in Real Madrid's history.

Ce sera le pire transfert de l'histoire du Real Madrid.

[Alphaco1n @Alphaco1n]

@FabrizioRomano This is going to be the worst transfer in Real Madrid's history

[tao.bot (τ, τ) @taodotbot]

🧠 Bittensor $TAO upgrade: Root Reborn is live

Bittensor’s root validator layer has changed.

Instead of root dividends remaining in the previous claim system, each validator now directs them into a validator-curated beta basket — a compounding fund containing subnet alpha and, optionally, root TAO.

Here’s how it works:

1️⃣ Validators set the allocation
Each root validator chooses how its basket is distributed across the subnet economy through its Root weight vector.

2️⃣ Dividends are reinvested
Root dividends are converted into TAO and redeployed according to the validator’s allocation. The resulting positions are held in escrow, staked, and able to compound over time.

3️⃣ Stakers accrue basket shares
Root stakers earn shares in their validator’s basket based on their root stake. New shares are minted at the basket’s current NAV, preventing later stakers from diluting previously accumulated value.

4️⃣ Claims redeem the full basket
When a staker claims, their proportional share of every basket holding is redeemed into TAO and returned to Root.

5️⃣ Validator strategy becomes transparent
New on-chain views expose basket NAV, holdings, validator allocation weights, and the TAO owed to individual stakers.

The main change is that root validators are no longer differentiated only by fees, stake, and headline yield.

Their subnet allocation strategy — and the performance of the basket built around it — now matters too.

Root Reborn connects root staking more directly to the subnet economy and turns validators into active on-chain capital allocators.

Explore Bittensor validators → https://t.co/BPC4PmDmLW

[Alphaco1n @Alphaco1n]

@Romain_Molina Tu lui as juste pourri son possible transfert et mis le PSG dans une situation délicate. Ça aurait été mieux de sortir l’info quand la période de transfert est terminée

[tao.bot (τ, τ) @taodotbot]

🧠 Bittensor $TAO upgrade check-in: Chain Buys

One of the biggest market-structure changes introduced in Spec 423 is now live: part of a subnet’s TAO emission can be used to buy its alpha directly from the pool.

Previously, subnet emissions were primarily added as price-neutral TAO + alpha liquidity. The new mechanism caps how much alpha can be injected based on the subnet’s root proportion.

When the alpha required for a neutral injection exceeds that cap, the chain injects less liquidity and uses the remaining TAO to market buy the subnet token.

1️⃣ Emission allocation comes first
Each subnet receives a share of block emissions based mainly on its price EMA, adjusted by miner-burn mechanics.

2️⃣ Root proportion limits alpha injection
As a subnet’s alpha issuance grows relative to its root-backed TAO, its root proportion falls and less newly minted alpha can be added to the pool.

3️⃣ Excess TAO becomes a chain buy
The TAO that can no longer be paired with injected alpha is swapped into the subnet token through its own AMM.

4️⃣ Mature subnets transition first
Older subnets with greater alpha issuance and lower root proportion should see more of their allocation shift from liquidity injection toward chain buys.

This does not mean every subnet’s full emission is market bought. Chain buys only use the excess TAO created when the injection cap binds.

The result is a gradual transition from protocol-owned liquidity creation toward protocol-driven demand for mature subnet tokens.

Track chain buys and subnet emissions → https://t.co/e6iMPlpr7h

[Alphaco1n @Alphaco1n]

@Stefan_B_Trades Gm ☕️

[Alphaco1n @Alphaco1n]

@AltcoinSherpa 25millions in the pocket. Easy money

[Alphaco1n @Alphaco1n]

@alex_hunter20 Non mais là c’est trop

[Alphaco1n @Alphaco1n]

@Jake__Wujastyk Everybody knew it was 100% chance

[tao.bot (τ, τ) @taodotbot]

🔎 Bittensor $TAO subnet check-in: top 5 by market cap

@chutes_ai (SN64) — remains the market cap leader and one of the clearest examples of real product-market fit on Bittensor. Chutes provides decentralized, serverless compute for deploying and running open-source AI models at scale. Its latest technical milestone was fully non-blocking decentralized training on a recurrent model, reported within 0.6% of centralized quality — pushing SN64 further beyond inference and into distributed training.

@TargonCompute (SN4) — confidential AI compute on decentralized hardware. Targon’s stack allows teams to run sensitive training and deployment workloads using hardware-backed privacy. Its recent Tower Pro launch extends that model into user-owned compute, letting owners run private workloads and contribute idle capacity back into the Targon network.

@lium_io (SN51) — a decentralized GPU rental marketplace connecting independent hardware providers with users running training, inference, and other compute-heavy workloads. Its move into the top 3 reinforces how strongly the subnet market continues to value direct access to GPU infrastructure.

@affine_io (SN120) — an incentivized reinforcement-learning environment where miners compete to make measurable improvements to AI models across tasks like coding and program abduction. Affine is one of the clearest attempts to turn model improvement into an open, competitive market.

@webuildscore (SN44) — decentralized computer vision and enterprise physical AI. Score powers Manako, which turns existing camera systems into real-time operational intelligence through no-code vision agents. Recent product updates have pushed that infrastructure further toward practical enterprise deployments.

Across Chutes’ serverless platform, Targon’s confidential cloud, lium’s GPU marketplace, Affine’s RL environment, and Score’s enterprise vision AI, the top of Bittensor continues to concentrate around subnets building real infrastructure and products.

Trade & research subnets → https://t.co/g619vgTYkr

[Alphaco1n @Alphaco1n]

@SoulzBTC Would love to 🥳

[Alphaco1n @Alphaco1n]

@ActuFoot_ C’est tellement une merde qu’il a bloqué les commentaires sur son Instagram

[Alphaco1n @Alphaco1n]

@Nabil_djellit Cher pour une pute de bas niveau

[Alphaco1n @Alphaco1n]

@FabrizioRomano Worst team ever