Look up any term in AI.

Gradient Boosting

Each tree is fitted to the negative gradient of the loss, not to the residuals — a boosting round worked by hand, and what changes under log loss.

Application-Specific Integrated Circuit (ASIC)

A chip wired for one job. Why Google builds TPUs and bitcoin abandoned GPUs — the volume-and-time bet behind custom silicon, with the break-even maths.

Cross-Validation (CV)

How cross-validation turns one lucky train/test split into a stable estimate, why 5 or 10 folds, and the leakage that quietly inflates every score.

Watermarking (SynthID)

AI watermarking hides a detectable signal inside model-generated text and images. How SynthID works, its robustness limits, and the EU AI Act rules.

Reward Model (RM)

The scorer that stands in for a human during RLHF: how reward models are trained, why their absolute scores mean nothing, and how they break.

Computer Vision (CV)

How computers turn a grid of pixel values into labels, boxes and masks — the task ladder, the 2012 hinge, and where vision is reliable versus brittle.