Why AI needs a new kind of supercomputer network - Episode 18

Why AI needs a new kind of supercomputer network - Episode 18

From OpenAI Podcast by OpenAI

May 6, 2026 · 38 min · Episode 18

About this episode

Mark Handley and Greg Steinbrecher discuss the need for a new supercomputer network design for training AI models.

Training frontier models isn’t as simple as adding more GPUs—one small problem and the whole coordinated dance falls apart. OpenAI’s Mark Handley and Greg Steinbrecher discuss how a new supercomputer network design, used to train some of the company’s latest models, keeps the whole system moving in lockstep, even with record numbers of GPUs. They break down Multipath Reliable Connection, a new protocol OpenAI developed with AMD, Broadcom, Intel, Microsoft, and Nvidia, and why they’re making it available for the whole industry to use. Chapters 00:00 Intro 00:39 Greg and Mark's paths to OpenAI 04:34 Why training AI stresses networks differently 10:05 Bottlenecks, failures, and the cost of waiting 15:19 How Multipath Reliable Connection works 18:59 A protocol to route around failures 25:05 Why OpenAI is making MRC an open standard 35:09 Could AI compute move to space? Hosted on Acast. See acast.com/privacy for more information.

People in this episode

Guests: Mark Handley, Greg Steinbrecher

Topics covered

  • AI training
  • supercomputer networks
  • Multipath Reliable Connection
  • protocols
  • technology collaboration
  • open standards

Keywords

  • AI
  • supercomputer
  • Multipath Reliable Connection
  • protocol
  • network design
  • training models
  • OpenAI

Mentioned in this episode

Organizations: OpenAI, AMD, Broadcom, Intel, Microsoft, Nvidia

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