Radar · Beta
Who supplies AI compute, where the physical chokepoints are, and what's shifting in the fab, datacentre and power layers beneath the model layer.
incumbents vs new entrants · ranked by mentions in compute/infrastructure coverage
fab capacity · HBM · packaging · grid · export controls
The development indicates growing demand for AI accelerator manufacturing and could affect the allocation, pricing, and availability of advanced-node capacity.
Advanced packaging and HBM availability are important constraints on AI accelerator production, so persistent TSMC bottlenecks could alter supply-chain dependencies and foundry competition.
Coming soon
A timeline of announced compute capacity commitments — new fab, datacentre and cluster buildouts, tracked by announcement date.
Waiting for: A larger population of items carrying both a computeCategory and a verified announcement date; the fields exist but are not live yet (migration not applied).
Coming soon
Announced AI-related investment broken down by compute category — accelerators, datacentres, fabs, networking, energy, memory, cloud capacity.
Waiting for: The AI desk's own investment extraction (FR-613, shipped this sprint) to accumulate enough rows to chart — today's 155 investments rows are still almost entirely defence-desk.
Coming soon
The split between compute/infrastructure coverage that serves training workloads versus inference/deployment workloads, over time.
Waiting for: workloadPhase (FR-614, shipped this sprint) to be live and populated — its migration is written but not applied, so no item carries it yet.
Coming soon
Which countries are building, exporting, or restricting AI compute capacity — a measured pillar, not a hand-curated one.
Waiting for: Enough geo-tagged compute/infrastructure coverage to measure a posture per country rather than curate one — deliberately deferred rather than shipped as a guess (see the roadmap's excluded-scope note).
The development may reshape the geographic dependencies and supply-chain exposure of AI-server manufacturing, although the source provides no investment figures, company names, or details on specific components.
Sustained AI infrastructure growth could constrain the hardware, electricity and cooling inputs needed to expand compute capacity.
The reported diversification may help preserve near-term AI-compute supply-chain activity and reduce disruption during NVIDIA's platform transition, although the article provides limited operational detail.
The dispute indicates growing competition over where allied semiconductor capacity and capital are deployed, with implications for supply-chain resilience and technology sovereignty.
If Intel's products perform as intended, they could affect supplier competition and platform dependence in AI infrastructure, but the source provides no performance results, availability details, or deployment evidence.
The approaches could shape future HBM performance, customisation, thermal behaviour, and scalability for advanced compute systems, although the report provides no demonstrated performance results.
The reported 1.33x average throughput improvement, rising to 1.54x with matched calibration data, suggests a potentially material way to run reasoning-oriented MoE models under constrained GPU memory.
If reproduced, the approach could materially improve inference efficiency and reduce the compute required to deploy language-model systems, while exposing limitations in standalone kernel benchmarks.
