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RISC-V Adoption Growth, plus AI Needs Brain-Inspired Computing

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Manage episode 382903230 series 3527547
Content provided by AspenCore. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AspenCore 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 of the embedded edge with Nitin podcast, we talk to the CEO of RISC-V International, Calista Redmond, on the growth in adoption of the RISC-V instruction set architecture, underlining the Intel announcement earlier this year as being the pivotal point in the history of RISC-V. Our second guest, Steve Pawlowski, who leads Micron’s advanced computing solutions group, talks about brain-inspired computing, underlining the limitations of modern computing systems which consume far too much energy to deliver the artificial intelligence-based systems we desire. He said that to truly scale, AI needs to be much more efficient, and should take our cues from the human brain.

  continue reading

35 episodes

Artwork
iconShare
 
Manage episode 382903230 series 3527547
Content provided by AspenCore. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AspenCore 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 of the embedded edge with Nitin podcast, we talk to the CEO of RISC-V International, Calista Redmond, on the growth in adoption of the RISC-V instruction set architecture, underlining the Intel announcement earlier this year as being the pivotal point in the history of RISC-V. Our second guest, Steve Pawlowski, who leads Micron’s advanced computing solutions group, talks about brain-inspired computing, underlining the limitations of modern computing systems which consume far too much energy to deliver the artificial intelligence-based systems we desire. He said that to truly scale, AI needs to be much more efficient, and should take our cues from the human brain.

  continue reading

35 episodes

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