Together AI's VP of Kernels, Dan Fu, argues that the pursuit of AGI is not hitting a hardware wall. He posits that current AI systems are significantly underutilizing existing hardware, with training runs often achieving only 20% Mean FLOP Utilization (MFU) and inference in the single digits. Fu suggests that advancements in software-hardware co-design and innovations like FP4 training could unlock substantial performance gains, and that future compute power from next-generation hardware has yet to be fully integrated. AI
IMPACT Argues that significant performance gains are achievable through software-hardware co-design, potentially accelerating AGI development.
RANK_REASON The cluster contains an opinion piece from a company executive discussing the future of AI hardware utilization and AGI.
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