AI'S BIGGEST BOTTLENECK IS DATA MOVEMENT
I've been saying it all year: $ALAB is going to be one of the biggest winners from AI inference -- the tax on AI workloads.
The reality is simple: data isn't moving fast enough between compute, memory & storage to keep up with real-time inference. And that gap only widens as models become more interactive, decentralised & dynamic.
Every major AI hardware player is adapting:
• $NVDA Grace Hopper -- built around memory coherence
• $AMD MI300 -- optimised for high-bandwidth interconnects
• $MSFT AI data centres -- designed with custom networking topologies
They're all converging on the same challenge: compute is now a connectivity problem -- Astera Labs is my favourite way to play that bottleneck.
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