Term tag: Foundation Models

Embodied AI

AI that learns by acting on the physical world: why robot data cannot be scraped, why a 76 ms model cannot run a 20 ms loop, and what sim-to-real costs.

Foundation Models

Not a marketing word for a big AI model: a foundation model is trained once on broad data and reused as the base for many downstream tasks.

Pre-trained Models

A neural network someone else already trained on a huge general dataset, which you download and adapt to your task instead of training from scratch.

Synthetic Data

Data generated by a model instead of collected from the world: what synthetic data is, where it helps, and why recursive use triggers model collapse.

World Models

A world model learns an environment's dynamics — given a state and an action, predict the next state — letting an agent plan or train in imagination.