Bittensor Bungalow $TAO nitter.net/i/spaces/1RJjpbrVrlBKw

I remember being on @markjeffrey’s The Palace thinking it was awesome circa 1996 FFW 3 decades and we are both doing Bittensor. Trippy, man And @stillcorecap has been a great addition to the ecosystem. Their investment is badge of honor for any subnet $TAO

“Bitcoin is the most efficient market in history. We built the same thing for intelligence.” Const left Google Brain to build something Big Tech wouldn’t touch: open, permissionless AI that can be mined like Bitcoin. On a special TWiST deep dive, Bittensor’s co-founder breaks down the subnet economy, how subnets are making open models even cheaper to run, and why he doesn’t sell a token, but participation. cc: @const_reborn, @opentensor, @jason, @lons 0:00 The origin of Bittensor (and the name Const) 10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at northwestregisteredagent.com… 13:55 From Bitcoin mining to mining intelligence 19:33 DigitalOcean - Head to do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:17 Odoo - The all-in-one business platform. Get started for free at Odoo.com/twist 32:37 What is a subnet? 33:35 Forcing honest inference from bad actors 37:14 Building a subnet is harder than it looks 40:42 Understanding dTAO 51:57 Where the registration TAO actually goes 1:02:57 All about the Conviction "rug pull" 1:15:19 How Const is making himself irrelevant 1:17:33 The "Buy One TAO" philosophy 🎥 Watch the full episode here 👇

RT @Jason: Predict bittensor:native models will consistently be top 20 vs their contemporaries over the next 12 months, while being cheaper…

RT @markjeffrey: @RaoulGMI Use ENGY.ai Pay HALF. Kimi K3 (close to Fable) - GLM 5.2 - Deepseek Flash Powered by Bittens…

RT @rob_svrn: @RaoulGMI @RaoulGMI felt this one too. worth a look at engy.ai (TAO SN 53) kimi k3 is close enough to fable…

I am pleased to announce that Stillcore Capital @stillcorecap has invested in @engyai (Bittensor Subnet 53).

I am pleased to announce that Stillcore Capital @stillcorecap has invested in @actualinc (Bittensor Subnet 95).

incentives explain outcomes @elonmusk

I'm so obsessed with the @bittensor model, where competing for prizes is vetted by validators... open source, OPEN COMPETITION, is the future! Please explain to me how you're using this stuff fam

Hash Rate - Ep. 180: Stillcore 'State of Subnets' Report 🧙 Guest: @markjeffrey of @stillcorecap A guided walk-through of the latest Stillcore report on Bittensor $TAO Subnets.

Presenting: The Stillcore Capital - STATE OF SUBNETS July 2026 Report Download: docsend.com/view/562fmtieyi2…

RT @Jason: Need. More. Tokens. Testing a secret new sub on @bittensor network running GLM 5.2 and it’s mind blowing 🤯 when your token cos…

I am pleased to announce that Stillcore Capital @stillcorecap has invested in Minos @theminos_ai (Bittensor $TAO Subnet 107)

Exciting to see Chamath and J-Cal discussing the power of Targon distributed confidential compute on @theallinpod “I do think this idea of distributed inference has a real place in the American ecosystem.” We appreciate the mention, and are excited to watch the continued growth of the permissionless compute space.

A more detailed answer to @travisk's objection on the latest @theallinpod that decentralized training of AI is not doable because of bandwidth: Traditional data-center training uses high-bandwidth interconnects (NVLink/Infiniband) and keeps everything co-located because communication is a huge bottleneck. IOTA (Bittensor Subnet 9) makes decentralized training feasible through several innovations: - Memory scaling: No single device needs the full model in VRAM. Capacity scales with the sum of participants’ memory, not limited by the weakest one. - Communication efficiency: Heavy activation compression + efficient all-reduce + concurrent compute/communication + stochastic routing for fault tolerance. The run achieved >30% MFU (peak sustained ~38%), roughly 65% of comparable co-located datacenter speed. - Fault tolerance & decentralization: Handles churn, variable bandwidth/latency, and unreliable peers via thresholds, redundancy in all-reduce, and randomized pathways. An orchestrator coordinates high-level triggers, but actual compute and much of the data flow is peer-to-peer. - Incentives: Bittensor’s blockchain layer rewards contributors fairly and granularly based on verifiable work, discouraging hoarding or free-riding. - Practical results: Orion-100B trained ~1.1 billion tokens over ~2 days on these 48 distributed GPUs at a much lower cost than centralized. This demonstrates that frontier-scale training over commodity internet is becoming technically and economically viable.

Excited to announce that Stillcore Capital @stillcorecap has invested in Aurelius @AureliusAligned (Bittensor Subnet 37)

Hash Rate - Ep. 176: Macrocosmos IOTA (9) + APEX (1) 🧙 Guests: @WSquires and @macrocrux of @IOTA_SN9 and @Apex_SN1 Download SN9's Home Mac Miner: iota.macrocosmos.ai/ 00:00 Orion 100B Model 03:27 Comparing Training Approaches 10:15 Liquid Training 12:17 IOTA: One-Click Mining 25:58 The Journey of IOTA: A Year in Review 33:04 Training Models: The Lifecycle and Challenges 36:06 Balancing Training and Inference in AI 37:56 AI: Scaling and Diminishing Returns 43:00 Aurelius: New Partnership 58:55 Upcoming Events and Community Engagement

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bittensor:native is the printing press of intelligence. 21 million tokens mined with useful ai work. the world will tap into Bittensor’s decentralized compute & intelligence like a faucet intelligence will be commoditized the way information was after gutenberg this is one of the greatest asymmetric opportunities of all time