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Arm’s Open Source Leader on Meeting the AI Challenge

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Manage episode 480044443 series 75006
Content provided by The New Stack Podcast and The New Stack. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The New Stack Podcast and The New Stack 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://ppacc.player.fm/legal.

At Arm, open source is the default approach, with proprietary software requiring justification, says Andrew Wafaa, fellow and senior director of software communities. Speaking at KubeCon + CloudNativeCon Europe, Wafaa emphasized Arm’s decade-long commitment to open source, highlighting its investment in key projects like the Linux kernel, GCC, and LLVM. This investment is strategic, ensuring strong support for Arm’s architecture through vital tools and system software.

Wafaa also challenged the hype around GPUs in AI, asserting that CPUs—especially those enhanced with Arm’s Scalable Matrix Extension (SME2) and Scalable Vector Extension (SVE2)—are often more suitable for inference workloads. CPUs offer greater flexibility, and Arm’s innovations aim to reduce dependency on expensive GPU fleets.

On the AI framework front, Wafaa pointed to PyTorch as the emerging hub, likening its ecosystem-building potential to Kubernetes. As a PyTorch Foundation board member, he sees PyTorch becoming the central open source platform in AI development, with broad community and industry backing.

Learn more from The New Stack about the latest insights about Arm:

Edge Wars Heat Up as Arm Aims to Outflank Intel, Qualcomm

Arm: See a Demo About Migrating a x86-Based App to ARM64

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

892 episodes

Artwork
iconShare
 
Manage episode 480044443 series 75006
Content provided by The New Stack Podcast and The New Stack. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The New Stack Podcast and The New Stack 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://ppacc.player.fm/legal.

At Arm, open source is the default approach, with proprietary software requiring justification, says Andrew Wafaa, fellow and senior director of software communities. Speaking at KubeCon + CloudNativeCon Europe, Wafaa emphasized Arm’s decade-long commitment to open source, highlighting its investment in key projects like the Linux kernel, GCC, and LLVM. This investment is strategic, ensuring strong support for Arm’s architecture through vital tools and system software.

Wafaa also challenged the hype around GPUs in AI, asserting that CPUs—especially those enhanced with Arm’s Scalable Matrix Extension (SME2) and Scalable Vector Extension (SVE2)—are often more suitable for inference workloads. CPUs offer greater flexibility, and Arm’s innovations aim to reduce dependency on expensive GPU fleets.

On the AI framework front, Wafaa pointed to PyTorch as the emerging hub, likening its ecosystem-building potential to Kubernetes. As a PyTorch Foundation board member, he sees PyTorch becoming the central open source platform in AI development, with broad community and industry backing.

Learn more from The New Stack about the latest insights about Arm:

Edge Wars Heat Up as Arm Aims to Outflank Intel, Qualcomm

Arm: See a Demo About Migrating a x86-Based App to ARM64

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

892 episodes

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