Look up any term in AI.

CUDA

NVIDIA's software layer for GPUs — the programming model that turned graphics cards into AI hardware, and the real reason rivals with comparable silicon lose.

Data Augmentation

Making new training examples by transforming existing ones. Valid only when the label is indifferent to the transform — and it adds variety, not information.

One-shot Learning

Learning a new class from exactly one example — and the split that matters: one-shot prompting updates no weights; classical one-shot training does.

AI in Finance

Machine learning that approves loans and blocks card fraud — where you ship the most accurate model you can defend, not the best one you can build.

General Problem Solver (GPS)

The 1957 Newell-Shaw-Simon program that solved problems by means-ends analysis, and the b^d arithmetic that stopped it from scaling past puzzles.

Low-Rank Adaptation (LoRA)

LoRA freezes a model's weights and trains two thin matrices beside each one: 98,304 numbers instead of 151 million, and no added inference latency.