Uploaded August 2026 | Updated September 2026, 2 weeks ago
The compute curve is exploding, but memory is not, and that gap is now one of the biggest constraints in AI infrastructure. We unpack the “memory wall” and why it shows up so clearly in AI inference, where time to first token, token throughput, and unpredictable demand can make yesterday’s architectures feel suddenly brittle.
We’re joined by Dr. J Metz, Chair of the SNIA Board of Directors, and Jack Guedj, one of three co-chairs of the new SNIA Compute, Memory and Storage Community MRAM Alliance Special Interest Group to talk about MRAM (magnetoresistive random access memory), and why the MRAM Alliance joined forces with SNIA. The goal is straightforward: bring persistent memory conversations into the same room as storage standards, system design realities, and the messy trade-offs that appear at scale. When a “medium” cluster can mean 100,000 GPUs, you cannot treat memory, storage, networking, protection, and security as separate puzzles.
We dig into what makes MRAM interesting for modern systems: very low latency reads, strong performance potential for inference, persistence without power, and the possibility of reducing power draw by eliminating refresh overhead. Hear how to connect the dots between the memory wall, AI inference performance, and discover why persistent memory is becoming a system-level priority.
Presented by Dr. J Metz, Chair of the SNIA Board of Directors, and Jack Guedj, one of three co-chairs of the new SNIA Compute, Memory and Storage Community MRAM Alliance Special Interest Group.
Learn More:
• SNIA Experts on Data Podcast: snia.org/podcasts
• SNIA Website: snia.org
• SNIA Educational Library: snia.org/library
• X: twitter.com/SNIA
• LinkedIn: linkedin.com/company/snia
The compute curve is exploding, but memory is not, and that gap is now one of the biggest constraints in AI infrastructure. We unpack the “memory wall” and why it shows up so clearly in AI inference, where time to first token, token throughput, and unpredictable demand can make yesterday’s architectures feel suddenly brittle.
We’re joined by Dr. J Metz, Chair of the SNIA Board of Directors, and Jack Guedj, one of three co-chairs of the new SNIA Compute, Memory and Storage Community MRAM Alliance Special Interest Group to talk about MRAM (magnetoresistive random access memory), and why the MRAM Alliance joined forces with SNIA. The goal is straightforward: bring persistent memory conversations into the same room as storage standards, system design realities, and the messy trade-offs that appear at scale. When a “medium” cluster can mean 100,000 GPUs, you cannot treat memory, storage, networking, protection, and security as separate puzzles.
We dig into what makes MRAM interesting for modern systems: very low latency reads, strong performance potential for inference, persistence without power, and the possibility of reducing power draw by eliminating refresh overhead. Hear how to connect the dots between the memory wall, AI inference performance, and discover why persistent memory is becoming a system-level priority.
Presented by Dr. J Metz, Chair of the SNIA Board of Directors, and Jack Guedj, one of three co-chairs of the new SNIA Compute, Memory and Storage Community MRAM Alliance Special Interest Group.
Learn More:
• SNIA Experts on Data Podcast: snia.org/podcasts
• SNIA Website: snia.org
• SNIA Educational Library: snia.org/library
• X: twitter.com/SNIA
• LinkedIn: linkedin.com/company/snia
