Pat Gelsinger wants to save Moore’s Law, with a little help from the Feds https://t.co/Pw68gMuAFo ...

AI Compute Demand & GPU Market - AI compute demand is growing at twice the rate of efficiency growth, potentially leading to GPU shortages [1] - To meet current AI compute demand, an estimated $500 billion must be invested in data centers annually until 2030 [2] Crypto Protocols Benefiting from GPU Demand - Livepeer, a decentralized video streaming network, benefits from GPU resources for video transcoding and processing [1] - Several crypto protocols are positioned to capitalize on GPU demand, including GPU-backed lending protocols like USDai_Official, enterprise GPU yield tokenization platforms like gaib_ai, DePIN GPU clouds like AethirCloud, and GPU compute providers for 3D rendering like Rendernetwork [2] - Other protocols include ionet (compute provider), 0G_labs (modular L1 with GPU clusters), SpheronFDN (compute marketplace), akashnet_ (cloud computing marketplace), and Theta_Network (decentralized video rendering and AI inference) [2] TAO + Subnets - TAO subnets like chutes_ai (SN 64), lium_io (SN51), neural_internet (SN27), and ComputeHorde (SN12) are relevant in the context of GPU compute [2]

Computing Acceleration - Moore's Law 的放缓促使行业寻求新的加速计算方法 [2] - 公司通过算法重构和并行处理，实现了计算加速，提高了成本和能源效率 [3] - 这种加速使得在计算领域进行机器学习和人工智能成为可能 [4] Technological Innovation - 公司致力于通过 CUDA 来增强应用层 [1] - 公司通过极端的计算方式，让计算机能够自主发现洞察 [4]