ScholarLens guides
Start with the shape of a field.
Build useful context before you dive into the literature. These concise guides explain the ideas, open questions, and applications behind major research areas.
Artificial Intelligence
The broad field of building systems that perceive, reason, learn, and act in ways that support human goals.
Read guideMachine Learning
Methods for learning patterns from data so models can predict, classify, rank, or choose actions.
Read guideDeep Learning
Representation learning with multilayer neural networks, applied across language, vision, speech, and science.
Read guideLarge Language Models
Large neural language models that learn broad linguistic patterns and can be adapted for many text tasks.
Read guideTransformers
Attention-based neural architectures that model relationships among elements in sequences and other structured inputs.
Read guideNatural Language Processing
The study of computational methods for understanding, generating, and interacting through human language.
Read guideRetrieval-Augmented Generation
Systems that retrieve relevant external information before generating an answer or other response.
Read guideGenerative AI
Models that produce new text, images, audio, video, code, or structured outputs from learned distributions.
Read guideComputer Vision
Methods for enabling computers to interpret images, video, 3D scenes, and visual measurements.
Read guideReinforcement Learning
Learning to make sequential decisions through interaction, feedback, and long-term objectives.
Read guide