Look up any term in AI.

Semiconductor Manufacturing

How an AI chip is actually made — wafers, process nodes, yield and the foundry model — and why supply cannot simply respond to a spike in demand.

Trust

Trust in AI is a person's willingness to rely on a system's output; the aim is calibration — trusting it as much as its real reliability deserves.

Quantization

Running a model in fewer bits — FP16, FP8, INT4 — to cut memory and cost, what accuracy it actually costs, and why a memory-bound model also gets faster.

AI for Good

AI for Good is an aspiration, not a technique, and nothing certifies the label. Here it is tested against named projects with published, measured results.

Disaggregated Serving (Prefill/Decode)

Disaggregated serving runs LLM prefill and decode on separate GPU pools because the two phases hit opposite limits: compute versus memory bandwidth.

Knowledge Representation

How you encode what a system knows fixes which conclusions are cheap, which are exponential and which are impossible. The expressiveness-tractability trade-off.