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Together AI VP: AI not hitting hardware wall, efficiency gains untapped

By PulseAugur Editorial · [1 sources] ·

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.

Read on Together AI blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Together AI VP: AI not hitting hardware wall, efficiency gains untapped

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The cluster contains an opinion piece from a company executive discussing the future of AI hardware utilization and AGI.
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opinion, infra
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295 days old
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COVERAGE [1]

  1. Together AI blog TIER_1 English(EN) ·

    Research POV: Yes, AGI Can Happen – A Computational Perspective

    Dan Fu, our VP of Kernels, has published a new post challenging the idea that AI is hitting a hardware wall. He argues that we are vastly underutilizing current chips and that better software-hardware co-design will unlock the next order of magnitude in performance.

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