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Episode 88: AI Accellerators, Startup graveyard? With Special Guest Austin Lyons

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Manage episode 444031894 series 3428472
Content provided by Ben Bajarin and Jay Goldberg, Ben Bajarin, and Jay Goldberg. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Bajarin and Jay Goldberg, Ben Bajarin, and Jay Goldberg or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.

  continue reading

92 episodes

Artwork
iconShare
 
Manage episode 444031894 series 3428472
Content provided by Ben Bajarin and Jay Goldberg, Ben Bajarin, and Jay Goldberg. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Bajarin and Jay Goldberg, Ben Bajarin, and Jay Goldberg or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.

  continue reading

92 episodes

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