Retrieval & RAG
How retrieval quality, chunking, embeddings and reranking affect grounded AI answers.
Research Observatory
Research that starts with a question and ends with evidence.
Cortex Lab research is organized around testable questions, baselines, experiments, failure analysis and practical implications rather than complexity for its own sake.
AI Agents
How planning, tool use, state and evaluation change multi-step AI performance.
Model Evaluation
How to design baselines, test sets, error taxonomies and regression checks.
Reinforcement Learning
How agents learn from rewards, value functions and policy improvement.
Personalized Learning
How learning signals can adapt explanations, practice and recommendations without hiding the logic.
Recommendation Systems
How behavior signals can personalize products, content and learning paths.
Responsible AI
How uncertainty, safety, provenance, privacy and human review should shape product behavior.
Efficient Inference
How quantization, caching, batching and model choice affect latency and cost.
MLOps
How deployment, monitoring, versioning and drift detection keep models useful after launch.