The silicon behind the system.
A chip specification can explain a capability. It cannot explain an entire deployment. Performance also depends on memory, networking, software support, and the work the system needs to do.
Our Chips coverage connects hardware developments to the infrastructure decisions facing enterprise teams.
Explore ChipsAI accelerators in context
Explore how different accelerator designs fit training, inference, and specialized workloads. Understand why a headline benchmark needs a clear workload and measurement method.
Memory and data movement
Look beyond raw compute to the capacity and bandwidth required to keep a workload moving. Examine the relationship between models, memory, interconnects, and serving architecture.
Hardware and software together
Follow the compilers, runtimes, libraries, and deployment choices that influence how much useful work a system can perform.
From component to capacity plan
Understand the questions behind availability, power, cooling, utilization, and total operating cost.
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Who should read this section?
Infrastructure leaders, AI engineers, architects, and anyone evaluating the computing resources behind enterprise AI.
Will chip coverage include buying advice?
Coverage can explain evaluation criteria and workload fit. Procurement decisions still require current vendor information, validated testing, and organization-specific requirements.