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As AI demand surges and GPUs become the bottleneck, decentralized compute offers a new way forward. Could crypto provide the infrastructure for scalable, permissionless AI? Just finished reading researcher Shlok Khemani's incredible deep dive into decentralized compute capabilities in the AI space. Let’s explore the current state of decentralized compute and its future potential. 🧵 1. The GPU Bottleneck - Training GPT-4 required 25,000 A100 GPUs and cost $60M. - The next generation of models will demand $100B+ and over 1M GPUs by 2026. Current challenges in the GPU market: - Supply shortages - Months-long wait times - Price opacity As AI scales, traditional infrastructure is strained. This creates an opening for decentralized solutions. 2. Why Decentralized Compute? The compute market today is fragmented and inefficient as Idle GPU capacity in data centers and individual devices remains underutilized. Decentralized compute platforms aim to aggregate global supply, offering: Lower costs. Geographic diversity to reduce latency. Permissionless access for developers worldwide. Crypto projects leverage blockchain incentives to align supply and demand, creating robust network effects. 3. Which AI Workloads Can It Support? Decentralized networks cannot support ultra-large models like GPT-4, which require tens of thousands of GPUs and dedicated infrastructure. However, smaller models are viable. Projects like Nous Research’s DisTrO and Prime Intellect’s OpenDiLoCo have demonstrated training models with up to 1B+ parameters across global GPU clusters. With globally distributed GPUs, decentralized networks are well-suited for inference tasks that require low latency and high redundancy. 4. How Does Crypto Add Value? Token Incentives: - GPU providers and users are rewarded in tokens, encouraging participation and liquidity. - Dynamic reward structures address geographic and hardware imbalances (e.g., higher rewards for scarce GPUs or underserved regions). Trust and Verifiability: - Smart contracts enforce transparent agreements, preventing price hikes or contract changes. - Cryptographic proofs ensure developers receive the compute resources they pay for. Censorship Resistance: - Decentralized networks reduce the risk of service suspension due to policy or external pressures, creating a more resilient infrastructure. 5. The Road Ahead While decentralized compute cannot yet challenge Big Tech’s dominance in large-scale training, its value in fine-tuning, inference, and smaller-scale training is clear. As AI adoption accelerates, decentralized compute may evolve into a critical infrastructure for ensuring the technology’s openness and accessibility.

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吴说获悉，慢雾创始人余弦发推表示， FTM 上的借贷项目 Polter Finance 因为 “空市场” 问题导致被盗 1200 万美元，并对在审计说明上看到如下表述表示震惊： “As the smart contract used is identical to Geist, except for the removal of the flash-loan function in Lending Pool, we are providing…

以太坊研究员兼 Smart Transactions（STXN）联合创始人 Vlad Zamfir 推出新的智能合约“时间机器”，使用户能够在以太坊上撤销特定智能交易并设置交易执行条件。STXN 联合创始人 Anuj Das Gupta 表示，该功能解决了区块链中灵活性与不可篡改性之间的矛盾，让智能合约能根据未来变化调整执行方式。STXN 首席执行官 Boris Mamlyuk 将此功能类比为 Gmail 的撤回邮件按钮，旨在为 Web3 生态提供更多实用性。(Cointelegraph)

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