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Digests from Weights & Biases — Weights & Biases videos for AI developers and ML practitioners.
CoreWeave Agent Lens delivers intelligent agent observability at enterprise scale, providing a single view of every trace to turn production issues into proven fixes.
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Simile's AI agents predict human behavior with 85%+ accuracy by simulating complex social interactions and RCTs, moving beyond simple reasoning models.
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The future of AI requires a shift from pull-based web search to proactive, agent-driven systems. CoreWeave and Parallel Web Systems discuss building the necessary GPU-native infrastructure to handle this massive scale.
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CoreWeave Forge unifies the AI loop (Run, Observe, Curate, Improve, Evaluate) into one connected environment. The keynote detailed how to move AI agents from demo to production, featuring the NVIDIA Vera Rubin NVL72 and advanced evaluation techniques.
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CoreWeave announced CoreWeave Forge, a unified platform for the entire AI loop (Run, observe, curate, improve, evaluate). Key launches include Vera Rubin NVL72 and tools like Agent Lens and Model Distillation, streamlining LLMOps.
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The future of enterprise AI lies in long-running agents that automate document workflows. We explore the advanced document context layer, covering specialized OCR, agent harnesses, and optimizing models for cost and accuracy.
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NASDAQ is adapting its infrastructure and software offerings to meet the demands of high-performance compute and agentic capabilities. The key is building a trusted 'intelligence layer' over existing financial systems.
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Liquid AI details how to build proactive Personal AI agents by creating a 'Personal Context Layer.' This layer ingests fragmented, real-time device signals (audio, location, motion) to enable intelligent, privacy-preserving routing between edge and cloud models.
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MasterClass details its multi-agent AI system, NCX, and the advanced observability stack built on CoreWeave. Learn how tracing, MCP servers, and an AgentOps loop enable self-improvement in complex AI applications.
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CoreWeave details its AI partnership with Aston Martin F1, showcasing how advanced data platforms and ML models are used to process everything from live telemetry to noisy radio chatter, enabling critical decisions in a high-stakes environment.
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IBM details its journey deploying sensitive AI workloads on CoreWeave, focusing on scaling H100/GB200 clusters and implementing 'federation first' identity controls to meet stringent security and compliance needs.
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The key goal was within this three-week sprint being able to have a measurable lift in performance and accuracy on this benchmark using the Neotron model postrained with the core weave dedicated inference platforms and .com web search team.
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Learn how to optimize AI compute capacity, control costs, and scale economically using CoreWeave's advanced capacity plans, Spot Instances, and the Mission Control platform.
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The economics of AI inference are dominated by agentic workflows, which use significantly more tokens than basic chat. Scaling requires co-design across model, system, and software layers to minimize cost per token.
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Building AI-native apps requires a unified data layer. We explore how ClickHouse handles vector search, real-time event ingestion, and complex agentic workflows, making it a single platform from first feature to complex agent.
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AI is accelerating the threat landscape, making traditional security metrics like 'breakout time' obsolete. Securing AI requires deep observability, architectural resilience, and leveraging massive compute power to train defensive models.
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This talk covers the systems and algorithmic challenges behind making globally distributed RL work at scale. We will discuss how we decouple training from inference, propagate compressed weight updates across datacenters, and design the infrastructure to tolerate frequent hardware failures.
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NVIDIA introduces the Vera Rubin platform, an integrated AI factory designed for extreme co-design. Learn how advanced networking (Spectrum-X) and specialized CPUs enable reliable, scalable AI infrastructure for the next generation of Agentic AI.
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The session details how CoreWeave uses the NVIDIA Vera Rubin NVL72 platform to scale AI workloads. Innovations like Racky and Valve, combined with RLCC automation, ensure reliable, high-density, liquid-cooled compute environments.
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Physical AI is moving from the lab to industrial sites. Success requires a closed-loop data flywheel, combining multimodal data, advanced simulation, and edge computing to solve the sim-to-real gap.
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