Nidish Kamath

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Nidish Kamath is the director of product management for Silicon IP at Rambus. He previously held marketing and product management roles at AMD, Kioxia (formerly Toshiba Memory), Avalanche Technologies, Brocade and Qualcomm, where he worked on computational storage, SmartNICs and GPU cluster networking solutions. He has served in various standards and industry associations such as SNIA, Center for Open Source Software (CROSS), CXL Consortium, UEC and JEDEC.

Author's Latest Posts

HBM4E Raises The Bar For AI Memory Bandwidth
By Nidish Kamath - 12 Mar, 2026 - Comments: 0

The pace of AI innovation continues to expose a painful reality. Compute keeps scaling, but memory bandwidth remains one of the hardest bottlenecks to remove. As AI models grow larger and more complex, feeding data fast enough into accelerators has become just as critical as raw compute capability. High Bandwidth Memory (HBM) has been central to solving this challenge, and the next step in that... » read more

GDDR7 Momentum Accelerates As A Key Solution For AI Inference
By Nidish Kamath - 15 Jan, 2026 - Comments: 0

The AI hardware landscape continues to evolve at a breakneck speed, and memory technology is rapidly becoming a defining differentiator for the next generation of GPUs and AI inference accelerators. When NVIDIA introduced Rubin CPX, its new class of GPU tailored for massive context inference, it underscored a new industry reality: memory throughput and efficiency are now just as critical as ra... » read more

GDDR7 Tackles Massive-Context AI Inference
By Nidish Kamath - 16 Oct, 2025 - Comments: 0

The AI hardware landscape is evolving at breakneck speed, and memory technology is at the heart of this transformation. NVIDIA’s recent announcement of Rubin CPX, a new class of GPU purpose-built for massive-context inference, underscores this trend. Rubin CPX is designed to tackle workloads that require reasoning across millions of tokens. Use cases include long-form generative video, comple... » read more

HBM4 Elevates AI Training Performance To New Heights
By Nidish Kamath - 15 May, 2025 - Comments: 0

Generative and Agentic AI are pushing an extremely rapid evolution of computing technology. With leading-edge LLMs now in excess of a trillion parameters, training takes an enormous amount of computing capacity, and state-of-the-art training clusters can employ more than 100,000 GPUs. High Bandwidth Memory (HBM) provides the vast memory bandwidth and capacity needed for these demanding AI train... » read more

HBM4 Feeds Generative AI’s Hunger For More Memory Bandwidth
By Nidish Kamath - 12 Sep, 2024 - Comments: 0

Generative AI (Gen AI), built on the exponential growth of Large Language Models (LLMs) and their kin, is one of today’s biggest drivers of computing technology. Leading-edge LLMs now exceed a trillion parameters and offer multimodal capabilities so they can take a broad range of inputs, whether they’re in the form of text, speech, images, video, code, and more, and generate an equally broa... » read more

LPDDR Memory Is Key For On-Device AI Performance
By Nidish Kamath - 24 Jun, 2024 - Comments: 1

Low-Power Double Data Rate (LPDDR) emerged as a specialized high performance, low power memory for mobile phones. Since its first release in 2006, each new generation of LPDDR has delivered the bandwidth and capacity needed for major shifts in the mobile user experience. Once again, LPDDR is at the forefront of another key shift as the next wave of generative AI applications will be built into ... » read more

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