Unveiling the Future of AI: Insights on AI Chips, Knowledge Graphs, and AI Regulations
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Subscribe • Previous Issues AI Chips: Past, Present, Future In a recent collaboration with Assaf Araki of Intel Capital, we delve into specialized hardware for Artificial Intelligence. The training of massive AI models has historically been dominated by Nvidia GPUs and Google TPUs. There is a significant challenge facing new entrants to the market: the lack of resources to develop a software stack comparable to CUDA or XLA makes other hardware accelerators less competitive. One notable advancement in this direction is the software stack centered around PyTorch 2.0 and Triton, that aims to simplify the implementation of non-Nvidia backends.
Unveiling the Future of AI: Insights on AI Chips, Knowledge Graphs, and AI Regulations
Unveiling the Future of AI: Insights on AI…
Unveiling the Future of AI: Insights on AI Chips, Knowledge Graphs, and AI Regulations
Subscribe • Previous Issues AI Chips: Past, Present, Future In a recent collaboration with Assaf Araki of Intel Capital, we delve into specialized hardware for Artificial Intelligence. The training of massive AI models has historically been dominated by Nvidia GPUs and Google TPUs. There is a significant challenge facing new entrants to the market: the lack of resources to develop a software stack comparable to CUDA or XLA makes other hardware accelerators less competitive. One notable advancement in this direction is the software stack centered around PyTorch 2.0 and Triton, that aims to simplify the implementation of non-Nvidia backends.