Training and inference capacity continues to expand.
What changed
AI infrastructure demand is expanding beyond a single accelerator architecture. GPU platforms remain central, while custom silicon and system-level integration are becoming more important.
The constraint is increasingly the complete compute module: silicon, memory, packaging, substrates, power delivery and qualification must arrive together.
Why it matters
GPU and custom-ASIC roadmaps are advancing in parallel.
Advanced packaging remains a critical throughput variable.
Mapped companies
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