Category: Hardware & GPUs
Custom AI Chips Are Changing the Inference Race
Custom AI chips are moving from an experiment to a product strategy because inference has become the daily bill for modern AI.…
Emin Budak
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AI Agent Hardware: Why Efficiency Is the New Benchmark
AI agent hardware is becoming an efficiency problem, not only a scale problem. A useful agent can read a long context, reason…
Emin Budak
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On-Device AI in 2026: Why Neural Engines Are Growing Up
On-device AI has moved past the demo phase. Phones, laptops, and edge appliances now reserve silicon for local inference, but the useful…
Emin Budak
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Local AI Hardware in 2026: The Desk Is Becoming a Data Center
Local AI hardware is no longer a niche setup for people compiling kernels in a garage. In 2026, the desk can host…
Emin Budak
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Distributed AI Inference: Why One Benchmark Is Not Enough
Distributed AI inference does not reduce to a single tokens-per-second number. Production serving mixes prompt prefill, token-by-token decode, bursty traffic, long contexts,…
Emin Budak
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AI Inference Hardware: Why It Gets Its Own Computer
AI inference hardware is becoming its own product category, not a leftover use for training GPUs. Serving a modern reasoning model means…
Emin Budak
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Quantized AI Models: Matching Long Context to Hardware
Quantized AI models are the practical way to match a long-context model to the hardware budget that actually exists. Qwen3-Next-80B-A3B-Instruct is a…
Emin Budak
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NVIDIA Vera CPU: Why Agents Need More Than GPUs
NVIDIA Vera CPU is a signal that agentic AI is changing the shape of an AI server. GPU throughput is still essential,…
Emin Budak
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AI GPU Benchmarks: What Actually Matters
AI GPU benchmarks only help when they resemble the job a team plans to run. A chart that puts one accelerator ahead…
Emin Budak
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