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.const believes Bittensor will outpace centralized machine learning labs, becoming the go-to hub for efficient problem-solving in data collection, benchmarks, and AI training. As competitors emerge, $TAO aims to remain the Schelling point for digital commodity systems.

102,100 次观看 • 1 年前 •via X (Twitter)

10 条评论

Grayscale 的头像
Grayscale1 年前

Watch the full $TAO Deeper Dive:

τauShaman | τ | ϙ | 的头像
τauShaman | τ | ϙ |1 年前

@const_reborn People should pay more attention to @BarrySilbert and @Grayscale @Grayscale have been bullish on $BTC before @saylor and anyone else and did a lot to push $BTC adoption... Now the same @Grayscale is bullish on $TAO !

τerenc3 的头像
τerenc31 年前

@const_reborn He’s not wrong.

Alex DRocks 的头像
Alex DRocks1 年前

@const_reborn he's most probably right about Bittensor

Kτinvesτor 的头像
Kτinvesτor1 年前

@CryptoMcDreamy @const_reborn $TAO is 👑. The $BTC of AI 🤖. It’s so obvious too.

OpenGPU Enthusiast Grid 的头像
OpenGPU Enthusiast Grid1 年前

@const_reborn Tao does not have enough scalability😏

Prabrorooo 的头像
Prabrorooo1 年前

@const_reborn Lord $TAO 👑

Crypto Ricky 💎 的头像
Crypto Ricky 💎1 年前

@const_reborn $TAO is the next big thing in this space!

Jesse Wright 的头像
Jesse Wright1 年前

@const_reborn Can someone explain to me how value accrues to the network from subnets? Subnets build the game, miners play it, validators confirm it. Subnets are running businesses off chain, so how does the value accrue back to $Tao holders?

Anon 的头像
Anon1 年前

@const_reborn Bullish $TAO

相关视频

For anyone trying to understand Bittensor from first principles, this lecture is a useful place to start. Presented by Bittensor co-founder const. Learn Bittensor > Start with Bitcoin, distributed systems, incentives, > How Bitcoin leads to Bittensor Subnets coordinating AI infrastructure. Topics: // Start - Bitcoin as more than a digital currency // Risks of AI centralization + closed systems // "The incentive computer" // How Bittensor subnets work (mining, validating) // How distributed AI infrastructure could scale globally // Impact on students, builders & future founders Recorded at the National University of Singapore Computer Science Club. NUS Computing Chapters - Bitcoin, AI, and Bittensor - Bitcoin history and decentralization - AI changes how engineers work - The danger of centralized AI power - Why most crypto visions fail - Bitcoin as the world’s largest compute network - Bitcoin as a market for compute - The idea of an “incentive computer” - Bitcoin compared to Bittensor - Classroom example of decentralized scoring - A simple subnet example - SN62 :: Ridges AI | SN62 SWE agents - SN3 templar :: Distributed AI Training - SN52 lium.io :: GPU rentals on Bittensor 128 subnets, some examples Why this matters for the future of work Q&A Subnet examples mentioned @ SN64 - Serverless + TEE Compute :: Chutes SN8 - Prop firm Vanta Trading SN52 - AutoML :: Gradients SN62 - SWE agents :: Ridges AI | SN62 SN51 - Compute / GPU rental lium.io SN4 - TEE compute for enterprise :: Targon SN3 - 72B Distributed Training run :: templar SN41 - Prediction markets :: Almanac SN44 - Computer Vision Score - Subnet 44 SN68 - Drug discovery :: METANOVA SN18 - Weather Forecasting Zeus | SN 18 SN50 - Bitcoin prediction data :: Synthdata SN61 - Quantum computing :: qBitTensor Labs SN14 - Bitcoin mining pool :: TaoHash SN34 - Perp Dex :: 0xMarkets SN17 - 3D model generation :: 404 SN33 - Data analytics :: ReadyAI SN19 - [Since relaunched] RPC infrastructure :

Openτensor Foundaτion

1,171,704 次观看 • 2 个月前