Host LG Doucet and Milk Road portfolio analyst Melvin examine where AI infrastructure spending could create fresh opportunities after major run-ups across semiconductors and data centers. Their focus shifts from raw compute to the constraints surrounding it, particularly networking, connectivity and memory.
Marvell and Credo stand out as plays on moving data between chips, racks and data centers as AI workloads become more complex. Samsung’s case rests on rising high-bandwidth memory demand, improving market share and the potential of its foundry business, while Cerebras offers a differentiated wafer-scale approach to fast AI inference.
Melvin identifies Marvell as his preferred name among the four, with Samsung close behind if the memory trade gains momentum. He remains interested but cautious on Cerebras, arguing that the company still needs to demonstrate broader customer adoption before earning a place in his portfolio.
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