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Daily · Sunday, January 11, 2026

SRAM's Limitations in AI Inference Highlight HBM's Continued Dominance

Today’s big story: SRAM isn’t cutting it for AI inference, and HBM is still king. As companies pivot to optimize performance, understanding these memory technologies is crucial for staying ahead in the semiconductor race. You’ll want to pay attention as the industry grapples with these evolving demands.

Key Stories

A Close Look at SRAM for Inference in the Age of HBM Supremacy

Summary

The article critiques SRAM's effectiveness in AI inference tasks while reaffirming HBM's significance.

Why this matters

• Highlights the performance limitations of SRAM, prompting reevaluation of its role in AI applications.
• Reinforces HBM's status as a critical component for high-performance computing, particularly in AI workloads.
• Signals a shift in design strategies as companies seek optimal memory solutions for next-gen chips.

Editor's Picks

A Close Look at SRAM for Inference in the Age of HBM Supremacy

Summary

The article critiques SRAM's effectiveness in AI inference tasks while reaffirming HBM's significance.

Why this matters

• Highlights the performance limitations of SRAM, prompting reevaluation of its role in AI applications.
• Reinforces HBM's status as a critical component for high-performance computing, particularly in AI workloads.
• Signals a shift in design strategies as companies seek optimal memory solutions for next-gen chips.