Hardware Podcasts

Fixing AI’s Bottlenecks: Memory, Scale, and Sparsity

EE Times Current · 23 Apr 2026 · 58m

What this episode covers

A panel of neuromorphic engineering experts, including Dr. Damien Querlioz, Dr. Julian Büchel, Professor Tamalika Banerjee, Dr. Maxence Ernoult, and Professor Steve Furber, discusses the bottlenecks in AI hardware at the Atoms to Bits conference. They debate the shift from scale-based emergence to engineered approaches, highlighting memory, connectivity, and sparsity as critical challenges. The discussion also covers the viability of emerging technologies, the role of public funding, and the potential for an AI market bubble.

Most relevant to

large enterprises and early-stage companies

Topics

Mentioned

Companies
IBM Research, Google DeepMind, iMchip, Intel, Micron, TSMC, Cerebras, Logitech, OpenAI, Microsoft Research, Extropic
Products
3D X Point, Spinnaker

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