The Rise of Alternative Memory Technologies Driven by AI Workload Demands

The surge in artificial intelligence (AI) workloads is reshaping the data center landscape, bringing about not only challenges but also opportunities for innovative memory technologies. According to industry expert Chuck Sobey, founder of ChannelScience and a leading figure at the Chiplet Summit, the expansion of AI is creating a demand for a redesign of existing data center infrastructures. This transformation is coupled with critical memory shortages that might catalyze new advancements in memory technologies.

A Shift in Workload Dynamics

Sobey argues that the new AI workloads are fundamentally different from traditional enterprise tasks. While legacy applications often burden CPU, network, and storage systems, AI tasks like deep learning and inference require significantly higher memory bandwidth. This means that the speed and efficiency of memory access have become paramount. Modern AI models may demand memory access rates of up to 10 terabytes per second (TB/s)—a vastly higher threshold compared to the standard DDR5 memory bandwidth. This disparity indicates a shift in how data is accessed and processed, emphasizing the role of memory systems in AI performance.

The Memory Crisis

The growing demands of AI have resulted in a crisis within the memory sector. Sobey notes that many data centers operate in a power- and memory-limited state, rather than being constrained by computing capacities. Today, the architecture of an AI-specific data center resembles more of a ‘token factory,’ where profitability hinges on processing tokens efficiently. Current challenges include power density requirements soaring to new heights, exceeding previous benchmarks by up to 100 times. Consequently, organizations risk falling behind if they cannot adapt their infrastructures accordingly.

Sobey highlights a stark shortage in the availability of high-performance server memory, characterized by a mere 70% fulfillment rate for orders—leading to noticeable price increases of up to 50%. Only the largest hyperscalers, which have significant resources, can secure necessary memory supplies, leaving smaller entities vulnerable.

Alternative Memory Technologies

Against this backdrop of shortages and high demand, Sobey identifies a rare opportunity for alternative memory technologies such as magnetoresistive RAM (MRAM), resistive RAM (RRAM), and phase-change memory (PCM). Unlike traditional memory manufacturers that require extensive fabrication facilities, these alternative technology avenues allow for innovation without the hefty infrastructure investments.

The chiplet architecture model has emerged as a critical enabler for this shift. By breaking down assets from monolithic ASICs into smaller, functional chiplets, designers can integrate diverse materials needed for alternative memory solutions. This method not only supports performance improvements but also introduces unique advantages, such as radiation tolerance—qualities that are essential for the evolving demands of AI workloads.

New Economic Realities

Sobey also discusses how the operational metrics in data centers are accelerating. The traditional ‘five-minute rule’—where data is stored in DRAM if accessed within five minutes—has morphed into a more urgent ‘five-second rule.’ This new reality dictates that if data remains unaccessed for five seconds, it must be removed from the expensive, high-speed memory, underscoring the pressing need for speed in AI applications.

In light of the current situation, Sobey asserts that the surge in AI represents a significant shift—not a mere ripple effect. He emphasizes that companies must act promptly to secure their places in the memory supply chain, lest they risk falling behind in both pricing and availability as the market stabilizes.

Sobey will delve further into the transformative impact of chiplets on memory technologies during the upcoming DIGITIMES webinar on December 5, 2025, and at the anticipated Chiplet Summit in Santa Clara, California, scheduled for February 17-19, 2026.