Design and operate a low-latency AI anomaly detection API for streaming data—architecture, models, thresholds, evaluation, and operations.
A practical guide to Reinforcement Learning from AI Feedback (RLAIF): how it works, key algorithms, design choices, pitfalls, and evaluation.
A practical guide to designing an AI churn prediction API—architecture, data/modeling choices, endpoints, MLOps, metrics, and code examples.
Learn how Constitutional AI aligns models using explicit principles, self-critique, and AI feedback, with recipes, code, and evaluation tips.
An up-to-date, practical comparison of Llama vs. Mistral open‑weight models: architecture, licenses, context windows, modality, and deployment tips.
A practical, modern guide to model compression via quantization—PTQ, QAT, calibration, mixed precision, and LLM-focused methods—with code and checklists.
