AI with Sally Ward-Foxton

As AI clusters scale, network reliability is becoming critical. In this episode, Credo’s Don Barnetson explains to Sally why the company is pursuing a “wide and slow” optical architecture, how its 2D emitter arrays could deliver 100× scalability, and how Active Light Cables could bridge the gap between copper and optics.

In this podcast, we chat with to Majestic Labs’ Sha Rabii about why AI's shift toward inference, long context, and agentic workloads could require a fundamentally different compute-memory architecture.

In this podcast, Sally talks to Amir BarNiv, VP of Strategic Marketing for Automotive Ethernet at Infineon. As AI becomes an increasingly important part of the software defined vehicle, a different architecture is needed in the car. So what does the AI-powered vehicle actually look like—and why is the industry moving toward centralized computing and zonal architectures?

In this podcast, Sally discusses how AI is lowering the barriers to finding security vulnerabilities, and how hardware could be the next frontier, with Arteris’ Andreas Kuehlmann. 

MIPS CEO Sameer Wasson explains why AI workloads should drive silicon design, and how MIPS, ARC and GlobalFoundries aim to lower the barriers to custom AI hardware.

On Axelera's fifth anniversary, CEO Fabrizio del Maffeo discusses funding, talent, RISC-V, edge AI and why Europe needs to think bigger.

In this podcast, Tensordyne’s Gilles Backhus explains why the company abandoned conventional arithmetic in pursuit of dramatically more efficient AI inference with the logarithmic number system.

In this podcast, Sally chats with Lightmatter CEO Nick Harris. As copper reaches its physical limits, Harris explains why photonics is moving from niche technology to AI infrastructure necessity, and why Lightmatter is expanding from optical interconnects into lasers to build the next generation of AI systems.

In this podcast, Lemurian Labs CEO Jay Dawani explains why system-level compilation, not faster chips alone, may determine the future of AI infrastructure.

What if hardware adapted itself to your code instead of forcing developers to optimize for the hardware? In this episode of AI with Sally, Sally Ward-Foxton speaks with NextSilicon CEO Elad Raz about the company’s radically different approach to compute architecture: a runtime-reconfigurable processor designed to optimize itself while applications are running.