GPU to AI factory
Accelerators, Grace, NVLink, networking and full rack-scale system strategy.
Open heterogeneous compute
Instinct, EPYC, Infinity Fabric, ROCm and hyperscaler qualification dynamics.
CPU, accelerator and fabric portfolio
Xeon, Gaudi, Ethernet and the challenge of integrated platform execution.
TPU family
Generational architecture, matrix engines, memory systems, fabrics and XLA integration.
MTIA family
Inference-first silicon, production workload co-design, memory hierarchy and system integration.
Maia and Brainwave
Cloud accelerator evolution, workload partitioning and Azure fleet integration.
Trainium and Inferentia
Purpose-built training and inference economics inside a managed cloud stack.
Digital in-memory compute
Memory-centric inference architecture, low-latency serving and compiler co-design.
Deterministic execution
Compiler-scheduled compute, predictable latency and the tradeoffs of architectural specialization.
Wafer-scale systems
Scale-up through extreme integration, memory locality and system-level programming.
RISC-V and scalable AI compute
Chiplet-oriented compute, open software ambition and licensing strategy.
Custom XPU enablers
ASIC design, SerDes, networking, optical DSP and hyperscaler co-development.
Inside a modern AI accelerator.
Compute throughput is only one element of application performance.
Compute fabric
Matrix, vector, scalar and local SRAM.
HBM system
Bandwidth, capacity and energy.
Interconnect
Do not compare chips by peak FLOPS.
Workload stability
Custom silicon wins when models, operators and deployment volumes are sufficiently predictable.
Memory behavior
HBM capacity, bandwidth, locality and KV-cache pressure often dominate real inference outcomes.
Software friction
Compiler maturity, kernel coverage, observability and operational tooling determine usable performance.
System scale
Interconnect, host design, power delivery and cooling shape the value of the accelerator.
Fleet utilization
Scheduling, fragmentation, workload mix and failover decide whether theoretical efficiency becomes economic value.
Lifecycle risk
Roadmap cadence, portability, depreciation and supply concentration matter beyond first deployment.