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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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