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For anyone trying to understand Bittensor from first principles, this lecture is a useful place to start. Presented by Bittensor co-founder @const_reborn. 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. @NUSComputing 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 SWE agents - SN3 @tplr_ai :: 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_ai SN8 - Prop firm @VantaTrading SN52 - AutoML :: @gradients_ai SN62 - SWE agents :: @ridges_ai SN51 - Compute / GPU rental @lium_io SN4 - TEE compute for enterprise :: @TargonCompute SN3 - 72B Distributed Training run :: @tplr_ai SN41 - Prediction markets :: @almanac_market SN44 - Computer Vision @webuildscore SN68 - Drug discovery :: @metanova_labs SN18 - Weather Forecasting @zeussubnet SN50 - Bitcoin prediction data :: @SynthdataCo SN61 - Quantum computing :: @qBitTensorLabs SN14 - Bitcoin mining pool :: @taohash SN34 - Perp Dex :: @0x_Markets SN17 - 3D model generation :: @404gen_ SN33 - Data analytics :: @ReadyAI_ SN19 - [Since relaunched] RPC infrastructure :