Lecomte Benoît

[On Chain Fox 🦊 @OnChainFox]

$TAO SN16 Identity Update

“Wait for 1 day” has been renamed to Fast Thinker.

• GitHub: fast-thinker/fast-thinker
• New description: Making reasoning models faster, leaner, and more efficient without sacrificing performance
• Logo changed to Fast Thinker

New identity: Fast Thinker | GitHub

[Connito AI @ConnitoAI]

AI is moving from one giant model to a library of reusable skills. You can now upgrade what an AI is good at without rebuilding the whole thing. Coding, math, safety and any customer's task. Here's why that changes everything.

https://t.co/0euAKk5i0X

[AlphaGap @AlphaGapTAO]

🚀 ConnitoAI (SN102) — evaluation quality just got a major upgrade

Their validators are rating outputs way more consistently now, which tightened up the whole network's scoring system.

https://t.co/Py53fOJ2hx $TAO

[Jon Cipher @_joncipher]

$TAO Modular AI ⬇️⬇️

💥💥💥ConnitoAI SN 102💥💥💥

🚀 BIG SHIFT ALERT in AI — This is exactly why modular, specialized intelligence is about to eat the monolithic giants alive!

Forget training one bloated “do-it-all” mega-model that costs a fortune and risks breaking everything when you tweak one skill.

We’re entering the era of modular AI — a smart base model and a plug-and-play toolbox of specialized experts (LoRA adapters, Mixture-of-Experts style).
Upgrade math? Just swap that module.
Boost coding? Add a new skill.
Customize for enterprise? Build your own library without retraining the whole beast.

Faster. Cheaper. More powerful. Future-proof.

This is the future of AI — composable, upgradable, and insanely efficient. And it aligns perfectly with decentralized networks like Bittensor, where subnets act as specialized incentive markets for exactly these kinds of modular capabilities in compute, inference, vision, agents, and more.

The DeAI flywheel is spinning faster than ever.
#Bittensor #TAO #dTAO #DeAI #Crypto #Solana #AI #DeFi $TAO $SOL $BTC #Web3 #Blockchain

[const @const_reborn]

Pretty cool open agentic trading arena from Astrid.

[R.L. ₿ryer @rBryer23]

Connito AI is one of the most asymmetric bets on Bittensor right now.

While most subnets are competing in crowded lanes, Connito is building decentralized MoE (Mixture of Experts) infrastructure for custom AI training : a model where every engagement compounds instead of resetting from scratch.

And the market is massive: Cheap APIs 🤝 Expensive enterprise consulting - Connito sits in the middle.

What stands out?
📈 Averaging 1,966 lines of code : which puts it in the Top 10% of subnets, signaling serious builder velocity.
🧠Contributors train isolated experts in parallel.
📊Proof-of-Loss aligns incentives around actual model quality.
🔁Every project strengthens the expert library → stronger future baselines.

If enterprise AI moves toward modular, specialized models instead of monolithic fine-tunes Connito could quietly become one of the most explosive subnets on Bittensor. 🔥

High code velocity.
Compounding architecture.
Massive TAM.
Still early @ < $2m market capitalization

$TAO #Bittensor #AI

[Jon Cipher @_joncipher]

$TAO 进化 ⬇️⬇️
🚨ConnitoAI（Bittensor 子网 102）：💥
去中心化训练竞技场刚刚发布了完整的网络状态展示——而且它正在快速进化！！！🚀
听好了。当其他 crypto-AI 元宇宙还在讨论“如果呢”的时候，ConnitoAI 刚刚发布了实打实的证据。 这不是炒作幻灯片。这是实时、活生生的信息图，展示了 SN102 正以全速运行——而且数据正在高呼势头强劲。
最新更新（直接来自前线） @ConnitoCore 刚刚放出了一个兽级仪表板，证明飞轮不仅在旋转——它正在加速成为传奇。
实时网络状态（截至本次更新）： • 5/5 验证者在线——完全参与，协调坚如磐石。 • 256/256 矿工活跃——每个槽位都已填满并展开竞争。 • 3,108 个已评分的模型已被评估。 • 6,788 个待处理——管道已满载。 • 基线损失在多轮中稳定保持在 13.9604 → 训练竞技场中一致、可��的进展。 • 第 8,248,102 轮处于训练阶段。
这是真实的链上活动。不是承诺。是实打实的执行。
最近开发升级（进化正在展现） 团队正在上线： • 改进的后台下载 → 更快、更可靠的模型处理。 • 子进程隔离 → 更好的稳定性和容错能力。 • 增强的 Hugging Face 上传支持 → 为所有人提供更流畅的操作。
这些不是华丽的头条。这些是安静、无情的迭代，把子网一步步打造成基础设施。
为什么这个更新如此不同 ConnitoAI 不仅仅是另一个追逐排放的 Bittensor 子网。它正在打造去中心化的竞争竞技场：矿工训练专业化语言模型，验证者无情地进行基准测试，最优秀的模型获得更高权重和 TAO 奖励。 这正是我们一直倡导的专业化 MoE 未来所需要的去中心化训练工厂。私有数据循环。定制专家。真正的竞争孕育真正的智能。
愿景是什么？成为 Bittensor 上最好的去中心化语言模型——一个 AI 开放、竞争且由社区拥有的世界。
牛市情景（越来越刺激） • 完整网络饱和（5/5 验证者 + 256/256 矿工）表明 Bittensor 内部的产品市场契合度已经到来。 • 稳定的损失曲线 + 快速的开发迭代 = 复合护城河。 • 实时仪表板、活跃社区、透明排行榜 → 大型实验室无法复制的一切。 • 在 TAO 牛市中，一个执行力和网络健康达到这个水平的子网，可能迎来大幅重估——随着 TaaS 和企业采用的启动，市值有望强劲增长至 5000 万–1 亿美元以上。
专业化 MoE 飞轮不仅在旋转。它正在进化成一股不可阻挡的力量。
风险（保持冷静） 仍处于早期阶段。技术和市场执行力依然关键。去中心化 AI 领域的竞争正在升温。没有保证——这就是加密市场。
总结 ConnitoAI 最新的更新不是噪音。是证明。完整验证者、完整矿工、稳步进展以及真正的开发速度。 SN102 不再是“即将到来”。它已经在这里、已经上线，并且正在公开为所有人进化。 信徒们，请保持耐心。建设者正在获胜。 释放海妖。🐙⚡️💥 $TAO $SN102 #ConnitoAI #SN102 #Bittensor #TAO #DecentralizedAI #CryptoAI #AIAgents #Web3
DYOR。合理仓位。训练之战已经打响。🚀

[Jon Cipher @_joncipher]

🚨 ConnitoAI SN 102 💥

ConnitoAI (Bittensor Subnet 102): The Decentralized Training Factory That Could Power the Next Wave of Specialized AI Models
In a world where the smartest AI apps are ditching rented frontier models for their own specialized, data-loop-trained beasts (as Charlie O’Neill laid out https://t.co/EGkSX4po5V), the real money flows to whoever can train those custom models efficiently at scale.
Enter ConnitoAI – Bittensor Subnet 102 – a research-first play building exactly the decentralized “training factory” the ecosystem needs.
This isn’t another inference subnet. This is infrastructure for the agentic, vertical-AI explosion.
Core Thesis
Big labs own the general models. Winners in 2026+ will own specialized experts trained on proprietary user feedback, domain data, and real outcomes.
ConnitoAI solves the hard part: Training massive specialized models (100B+ params) without OpenAI-level compute.
They use Mixture-of-Experts (MoE) built for decentralization:
• Miners train specialized “experts” locally on affordable GPUs.
• Validators coordinate, merge smartly, and reward via real performance (Proof-of-Loss).
• Math POC proves targeted gains with zero catastrophic forgetting.
Perfect for the trend: Enterprises & vertical apps (legal, healthcare, finance, agents) spin up custom experts on private data loops via Training-as-a-Service (TaaS). Privacy-first. Composable. Updatable moats the big labs can’t touch.
Why Now?
• Shift to “own your data flywheel” is accelerating (Cursor, Harvey, Abridge etc.).
• Decentralized training was the missing piece in Bittensor.
• Agentic AI needs swarms of specialist experts. MoE + TAO incentives = natural fit.
• Tiny market cap. High staking APY potential. Dashboard dropping ~May 26. Research paper soon.
Bull Case
If they nail TaaS, ConnitoAI becomes the go-to decentralized training marketplace. Reusable expert library compounds. Real revenue on top of emissions. In a TAO bull run, this could rerate 10-50x+ from current levels. Asymmetric upside.
Risks (be real)
Early stage. Execution on enterprise deals. Competition heating up. Classic crypto volatility.
Bottom line
ConnitoAI (SN102) is one of the highest-conviction asymmetric bets in Bittensor for believers in specialized, privately-improved models. Tiny valuation, strong tech moat, perfectly timed.
High risk. High conviction. Release the Kraken. 🚀🐙
DYOR. Size appropriately.
$TAO $SOL #Bittensor #TAO #ConnitoAI #SN102 #DecentralizedAI #CryptoAI #AI #Web3 #Crypto #Solana #AIAgents

[Jon Cipher @_joncipher]

$TAO Sleeping Giant 👀👀

🚨 Most people are still completely sleeping on ConnitoAI (SN102)
While everyone chases the latest hype, SN102 is quietly building the real decentralized training layer Bittensor has been missing:
• True MoE architecture designed for decentralization
• Miners train only a few specialized experts locally (zero comms during training)
• Scales naturally to 100B+ parameter models on affordable GPUs
• Math POC already delivered: real gains with zero catastrophic forgetting
• Dashboard drops in just 6 days (May 26)
• Full research paper coming soon + TaaS revenue in Q3/Q4
Tiny market cap. Extremely high early staking APY. Clear path to real enterprise revenue.
This is one of the most asymmetric setups in the entire Bittensor ecosystem right now.
RELEASE THE KRAKEN 🐙💰
Feel good, stake ConnitoAI.
Who’s loading SN102 before the dashboard? 👇
#Bittensor #DecentralizedAI #TAO $TAO $SOL #ConnitoAI #TaaS #AgenticAI #DeAI #Crypto #Web3

[Jon Cipher @_joncipher]

$TAO FEEL GOOD! STAKE CONNITOAI !!! 👀👀

🚨 Why ConnitoAI (SN102) Will Obliterate What Templar (SN3) Achieved 💥
Templar pushed dense-model training hard — big 72B Covenant model with gradient syncing. Respect for the effort.
But it still suffered the classic decentralized headaches: heavy communication, coordination nightmares, expensive per miner, and scaling limits around 80B.
ConnitoAI was built different:
• True MoE architecture from the ground up
• Miners train only a few specialized experts locally on affordable GPUs
• ZERO communication during training
• Smart merging + Proof-of-Loss validation
• Scales naturally to 100B+ parameters
• Composable experts perfect for agent swarms & continuous improvement
Templar fought the limitations of decentralization.
ConnitoAI embraced them and turned them into superpowers.
Real TaaS revenue coming Q3/Q4. Dashboard May 26. Research paper soon.
Feel good, stake ConnitoAI. 🐙💰
Who’s rotating to SN102? 👇
#Bittensor #DecentralizedAI #TAO $TAO $SOL #ConnitoAI #MixtureOfExperts #TaaS #AgenticAI #DeAI #Crypto #Web3

[Connito AI @ConnitoAI]

Top notch analytical piece from @TensiaFDN explaining how can this decentralised training framework work out in bittensor 🔥🎉 Follow us for more

[Jon Cipher @_joncipher]

🚨 THE KRAKEN IS AWAKENING — CONNITOAI SN102 IS ABOUT TO EXPLODE! 🐙💥
Root APY is getting crushed toward 0% on purpose — why sit there like a bagholder when the real beast is rising?!
ConnitoAI (SN102) is unleashing decentralized 100B+ parameter training the way Bittensor always dreamed of:
• True MoE savage mode: Miners forge only a few specialized experts locally on cheap A6000 GPUs
• ZERO comms during training — pure efficiency
• Math POC already crushing it with real gains + zero catastrophic forgetting 🔥
DASHBOARD DROPS IN JUST 7 DAYS (May 26) — the monster surfaces!
Full research paper incoming. TaaS platform Q3/Q4 for real paying customers.
Staking is INSANELY juicy right now:
• Extremely high early APY (thousands % spikes possible — low stake + fat emissions)
• Super low entry point — tiny market cap = massive alpha rocket fuel as revenue hits
• Built for the agentic economy — specialist experts that keep compounding forever
Elite team. Working POC delivered. Research-first execution. This is the training factory that turns Bittensor into a frontier AI powerhouse.
STOP SLEEPING ON ROOT.
Deploy into the Kraken before May 26 and ride the next leg of $TAO!
RELEASE THE KRAKEN!!! 🐙🚀💥💥💥
Who’s loading SN102 before the dashboard? LFG 🚀🚀🚀
#Bittensor #DecentralizedAI #TAO $TAO $SOL #ConnitoAI #MixtureOfExperts #TaaS #AgenticAI #DeAI #Crypto #Web3 #Solana #AI

[Punisher ττ @CryptoZPunisher]

#Bittensor >> Clarity is alpha<< #Tensia
>> $TAO - $dTAO <<

Subnet 102: ConnitoAI
@ConnitoAI
https://t.co/8ZiEpA90Dr

You were waiting for it, here it is.

Hours of work, discussions with the team, and a solid analysis of Subnet 102, ConnitoA.

This is how @TensiaFDN works:

impartial analysis.

The good, the less good, everything will be disclosed.

Clarity is alpha.

The usual critics will talk about insiders, KOLs pushing their bags, and all the rest.

I do not hold SN102, because the liquidity is extremely thin.

This work is not paid.

We expect nothing.

We sell nothing.

We simply share it with the entire community.

I am truly happy about this collaboration with a team of passionate people.

Tensia is doing God’s work.

[Tensia Foundation @TensiaFDN]

https://t.co/rjCrLXmOim

[Jon Cipher @_joncipher]

$TAO EVOLUTION! 👀

🚨ConnitoAI SN 102💥

🚨 How ConnitoAI (SN102) is Different from Other Training Subnets on Bittensor
Most training subnets try to do decentralized training the “old way” — forcing centralized architectures onto a decentralized network. ConnitoAI redesigned it from the ground up for true decentralization.
The Old Approach (e.g. Templar/SN3, Gradients, Teutonic, etc.):
• Miners usually train full models or large chunks of a dense model.
• High communication overhead (gradients, synchronizations, constant talking between nodes).
• Hits hard limits around 40B–80B parameters because one miner can’t handle bigger dense models.
• Relies on techniques like data parallelism, pipeline parallelism, or gradient compression (e.g. SparseLoCo in Templar’s 72B Covenant model).
• Good for big one-off pre-training runs, but coordination-heavy and expensive per miner.
ConnitoAI’s MoE-First Approach (the big differentiator):
• Built on Mixture of Experts (MoE) designed for decentralization.
• Each miner trains only a few specialized experts locally — no need to hold or train the full model.
• Zero communication during training — massive efficiency win.
• Updates merge later via smart weight-merging (DiLoCo-style) + a shared expert for stability.
• Enables 100B+ parameter models (even trillions in theory) at much lower per-miner cost.
• Miners act like a global research team contributing reusable expert modules, not just rented GPUs.
• Long-term: composable expert marketplace + real Training-as-a-Service (TaaS) for custom models.
Why this matters for Bittensor
Other subnets push the limits of traditional distributed training. ConnitoAI removes the core bottlenecks so the network can actually compete with (or surpass) centralized labs on frontier-scale models without massive coordination pain.
It’s not another “train a big model once” play — it’s building the permanent decentralized training factory Bittensor has been missing.
Research paper coming in 1-2 months to prove it. Very early, but architecturally unique.
Keep evolving!👀
LFG !!!! 🚀🚀🚀
#Bittensor #DecentralizedAI #TAO $TAO $SOL #MixtureOfExperts #TaaS #ConnitoAI #AI #Crypto #Web3

[Jon Cipher @_joncipher]

$TAO THE KRAKEN STIRS!! 👀👀

ConnitoAI SN 102 ⬇️⬇️

“🚨 LISTEN UP, DEGENS — THE KRAKEN IS AWAKENING IN THE DEPTHS OF DECENTRALIZED AI! 🐙💥
Connito AI just dropped ALPHA CODE on Bittensor Subnet 102 — and it’s about to UNLEASH 100B+ PARAMETER MONSTERS using Mixture-of-Experts!
No more waiting on trillion-dollar data centers run by Big Tech overlords.
Miners now train tiny expert shards that fuse into GOD-TIER models. Cheaper. Modular. Insanely scalable.
Teutonic smashed 72B decentralized — Connito is here to CRUSH the next frontier and build the ultimate training layer!
Whitepaper drops May 12. Dashboard May 26.
This is the moment the revolution ignites. Position up or get left in the dust.
RELEASE THE KRAKEN!!! 🐙🔥🚀
$TAO $CONNITO $SOL #Bittensor #DecentralizedAI #TAO #ConnitoAI #Subnet102 #MoE #Crypto #AI #Solana”

[Mariuszek @sobczak_mariusz]

The level of talent coming into $TAO subnets right now is incredible. Subnet 102 @ConnitoAI is a perfect example the founder is absolutely top-tier, I am genuinely blown away. Our ecosystem has some of the smartest people in the space, and $TAO looks severely undervalued just on the talent flowing in alone.

[Quasar @QuasarModels]

The history of decentralized training runs has mainly focused on large-scale execution, as this is important for open and transparent training.

But they’ve missed one critical thing: quality.

Even the most successful training runs, like SN3, are technically unusable in practice because quality was never the goal.

At Quasar SN24, we’re changing that.

We are building the largest MoE training run with SOTA performance and quality as core priorities. This means the outputs won’t just be impressive decentralized runs they will be SOTA long-context models that are actually usable.

[τroy @TroyQuasar]

When we said we are going to deliver state of the art, we meant it.

[τroy @TroyQuasar]

SN24 miners are the luckiest in the world

They will have access to high-quality data that has never been seen before for decentralized training.
Training the best AI architecture for long-context reasoning.

Wow