Fine-tuning World Action Models (WAMs): From multimodal data to reliable robot behavior
Physical AI breakthroughs don’t come from new models alone; they come from better data. As robotics teams race to build model-based policies for embodied AI systems, they face a new challenge: managing massive volumes of multimodal data, improving data quality, and creating feedback loops that continuously improve real-world performance. Join Skander Fourati, ML Solutions Engineer […]
How to operationalize AI governance for production agents
As AI agents become more autonomous, engineering teams need more than static governance checklists and disconnected evaluations to ship safely. In this webinar, Karan Nisar, Staff AI Solutions Architect, Weights & Biases by CoreWeave, will demonstrate how to operationalize AI governance with a repeatable review workflow that combines automated evaluations, red-team testing, and human review […]
The new quant stack: Scaling alpha research with AI, simulation, and compute
As quantitative research evolves from small-scale backtests to large-scale, AI-driven experimentation, leading firms are rethinking how they build, track, and scale alpha generation. Modern quant teams are no longer constrained by ideas; they are constrained by their ability to run, evaluate, and iterate on experiments at scale. Compute, data, and experimentation infrastructure have become the […]
AI 에이전트 전 과정을 지원하는
유일한 플랫폼
AI 개발은 이제 “모델 학습”만이 아닙니다. 최근 몇 년 사이, AI 개발의 무대는 바뀌었습니다. 단일 모델을 학습시켜 배포하는 시대에서, 여러 모델과 도구를 엮어 Agent와 GenAI 앱을 만드는 시대로 옮겨가고 있습니다. ML 엔지니어와 AI 애플리케이션 개발자라는 새로운 두 갈래의 역할이 나뉘고, 각자에게 필요한 도구도 달라졌습니다. Weights & Biases는 이 변화에 맞춰 진화해 왔습니다. 실험 추적의 표준으로 자리 잡은 Models, GenAI 앱과 Agent의 동작을 들여다보는 Weave, 그리고 인프라 걱정 없이 파인튜닝과 추론을 가능하게 하는 Training과 Inference 까지 — 이 네가지 제품이 어떻게 하나의 개발 사이클로 연결되는지 살펴봅니다.
Scale Vision-Language-Action (VLA) pipelines with Anyscale and Weights & Biases
Simulation-based evaluations accelerate robotics development by orders of magnitude, replacing hardware evaluation constraints with simulated rollouts. A production Vision-Language-Action (VLA) model fine-tuning pipeline must independently scale three core components across heterogeneous hardware: data loading on CPUs, training on one class of GPUs, and policy evaluation on another. Each sim rollout is stochastic, so meaningful evaluation […]
What’s New Wednesdays
The Weights & Biases AI developer platform streamlines the full AI agent lifecycle so you can deliver reliable, self-improving agents to production. Join us on the last Wednesday of each month for live demos, fun conversations, and real-world advice for building models and agents using the latest product capabilities. Each session is interactive by design, […]
From scanned documents to trusted summaries: Building auditable OCR-to-RAG pipelines
Generative AI can accelerate document-heavy banking workflows, but OCR errors, retrieval gaps, and opaque LLM behavior make accuracy, cost, and compliance difficult to control. In this live webinar, DZone and Weights & Biases break down how to design auditable OCR-to-RAG pipelines built for regulated environments. Learn how to add end-to-end observability, governance, and evaluation so […]
From physics to intelligence: Accelerating the design of next‑generation products
Building reliable physical systems is too slow, too expensive, and too uncertain. Mainstream AI can’t solve this challenge alone because it is fundamentally ungrounded in physics. Meanwhile, traditional simulation and testing workflows can no longer keep pace with the growing complexity of modern robotics, vehicles, energy systems, and industrial automation. To break this bottleneck, companies […]
Migrating from Neptune to Weights & Biases
With Neptune sunsetting its AI developer platform on March 5, 2026, many AI teams need to migrate experiment tracking and model development workflows without losing data or slowing down delivery. In this technical webinar, Hesham Assabahi, Senior AI Solutions Engineer, Weights & Biases, and Uma Krishnaswamy, Senior AI Engineer, Weights & Biases, will walk through […]
本番で“使われ続ける”AI Agentをどう作るか：
Eval-Centric時代のLLM ObservabilityとW&B Weave
AI Agentは作れる時代になった。しかし、本番で“使われ続ける”Agentはまだ少ない。本ウェビナーでは、Eval-Centricという考え方を軸に、LLM Observabilityが本番運用で果たす役割と、進化したW&B Weaveを通じて「Agentを育て、守る」ための実践的アプローチを解説・デモします。