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In this episode, Ben Bajarin, Jay Goldberg, and Austin Lyons discuss the rapid evolution of AI technology and its implications for hardware and software. They explore the challenges faced by AI accelerators, the role of hyperscalers, and the investment landscape in AI startups. The conversation highlights the disparity between the fast-paced development of AI software and the slower advancements in hardware, particularly in the context of GPUs and dedicated AI accelerators. The speakers also delve into the future of real-time training and inference, emphasizing the need for integrated systems over disaggregated ones.
By Ben Bajarin and Jay Goldberg4.7
3838 ratings
In this episode, Ben Bajarin, Jay Goldberg, and Austin Lyons discuss the rapid evolution of AI technology and its implications for hardware and software. They explore the challenges faced by AI accelerators, the role of hyperscalers, and the investment landscape in AI startups. The conversation highlights the disparity between the fast-paced development of AI software and the slower advancements in hardware, particularly in the context of GPUs and dedicated AI accelerators. The speakers also delve into the future of real-time training and inference, emphasizing the need for integrated systems over disaggregated ones.

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