ai > concepts

Reinforcement Learning and RLHF in a nutshell

A very high-level summary of RL. Dall-e's somewhat inaccurate representation of RL state-space RL is an approach to efficiently search state-space of a well-defined system. We can think of the system as a graph with states (vertex) and actions (edges) that lead to change in state. In its

Transformers - Part 1 NLP

Transformer architectures have unlocked tremendous potential in the context of Machine Learning problems. It has become the basic building block for learning and generating all modalities: language, vision, speech. But what changed with Transformers? We had kernel methods available for decades. In short, transformers allows for efficient context-aware learning. A