Grok 4 tutorial: A step-by-step guide to using xAI’s Grok 4 for code generation and debugging, including OpenRouter setup and W&B Weave integration.

Getting set up and running Kimi K2, MoonShot AI's advanced long-context language model, in Python using W&B Inference. We'll be working with the moonshotai/Kimi-K2-Instruct model.

Humanloop is shutting down. Meet your alternative: Weights & Biases. Discover how to seamlessly migrate your LLM workflows for tracking, evaluation, and monitoring.

Learn how to debug, trace, and monitor your LLM applications with W&B Weave. Gain visibility into performance, errors, and safety for reliable AI.

Explore LLM evaluation and benchmarking essentials - ethical, factual, and performance assessments - with a step-by-step W&B Weave tutorial for AI leads.

Save 70-80% on AI coding costs by integrating Claude Code with W&B Inference. Complete guide using official APIs - no complex proxy setup required.

Learn how Amazon Bedrock AgentCore enables secure, scalable AI agent deployment with built‑in observability—and how integrating W&B Weave enhances traceability and performance insights for developers.

Build a powerful RAG system with Gemini embeddings (gemini-embedding-001) and monitor queries, retrievals, and outputs using W&B Weave.

Deep dive article about OpenPipe ART and training agents.

Learn how to implement MUVERA with Weights & Biases to build fast, scalable multi-vector retrieval systems. This hands-on tutorial covers theory, code, and performance tracking.

Trace your CrewAI application with W&B Weave: Apply guardrails, visualize every agent decision, and debug multi-agent workflows for better performance.

Kimi K2 is Moonshot AI's 1T-parameter open model excelling in coding and reasoning. Explore its features, API deployment, and monitoring with W&B Weave.

Deep dive article about RTX PRO 6000

The NVIDIA GB300 NVL72 is delivered as a fully liquid-cooled, rack-scale system (CoreWeave's first GB300 rack shown above). Its dense design unifies cutting-edge GPUs, CPUs, and networking to push AI performance to new heights.

Deploying LLM applications into production is complex. This guide explains LLM observability - why it matters, common failure modes like hallucinations, key tool features, and how to get started with W&B Weave.

Blackwell GPU: NVIDIA’s next-gen architecture with multi-die design, FP4 precision, NVLink-5, and GB200 Superchip powering unparalleled AI training and real-time inference.

Explore the essentials of LLM observability, key challenges, and how tools like W&B Weave help AI teams monitor, debug, and optimize large language models for performance, reliability, and ethical compliance.

Learn how to evaluate Large Language Models (LLMs) effectively. This guide covers automatic & human-aligned metrics (BLEU, ROUGE, factuality, toxicity), RAG, code generation, and W&B Guardrail examples.

A comprehensive guide on LLM evaluation, exploring key metrics, human and automated methods of evaluation, best practices, and how to leverage W&B Weave for continuous improvement.

Evaluate your AI agents effectively with a comprehensive guide on key metrics, evaluation strategies, and a beginner-friendly W&B Weave tutorial.