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What are Subnets? Bittensor is the Olympic Games of intelligence 🥇 Bittensor Sub-Networks (subnets) solve big problems in AI: • Decentralized training • Fine-tuning models • Fraud detection • Protein folding & more (+ it's open source) Subnet owners design games (challenges) to solve specific problems. Miners are the athletes of Bittensor who do the work, Validators are the judges who score the winners according to the subnet’s rules (Incentive mechanism) The best contributors are rewarded in $TAO, creating measurable output of digital goods. Bittensor subnets transform human ingenuity into measurable, decentralized digital commodities, redefining the economy of intelligence.
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SN19 - Inference faster than almost all web2 (all but Grok) - Training simplified—train LLMs with zero coding skills - Deploy your own serverless, decentralized model powered by network miners All in this weeks episode: https://t.co/IbWXtQ3fR5 https://t.co/6kOzeUJBFF @namoray_dev @mogmachine @const_reborn
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The Holy Grail of Bittensor: Permissionless, trustless, Incentivized >> Distributed Training. Dive into how two subnets in Bittensor are pioneering this frontier in a world-first effort. Full episode on YT+ Spotify: https://youtu.be/IHSotxGHP70
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"Intelligence at the edge of chaos" — A maxim for Bittensor. SN36: Formed at the crossroads of groundbreaking research and mysterious computational phenomena, driven by the potential of Rule 30 and cellular automata. @WOMBO @KeithSingery Full Episode on Spotify & YT:
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Preview: New Subnet Analyzer Tool by @WOMBO in our latest episode with @KeithSingery, @benzion_b and @const_reborn Topics in this episode: - Cellular automata in AI and the potential of Rule 30 - Model compression for affordable AI on consumer hardware: SN39 - The trillion-row dataset initiative in SN36 - Validator diversity and decentralized ecosystem growth
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