![]() With LLMs there are also a host of new metrics that organizations need to track. Common metrics for any production system are typically about availability, latency and performance. Lewis explained that the production monitoring service is customizable to help organizations track the metrics that matter to them. That’s where the Weights & Biases’ production monitoring service fits in. Building a model is one thing, monitoring it quite anotherīuilding and deploying an ML model isn’t the only part of the AI lifecycle. It is also integrated into the Weights & Biases platform so that enterprise customers can build visualizations as a part of their overall AI development workflow. Weave is being made freely available as an open-source LLMOps tool, so anyone can use it to help build AI tools. ![]() W&B Weave uses state-of-the-art techniques and visualizations, making it easy for developers to explore data, evaluate models and experiment with ML building blocks seamlessly. It is the foundation that enables the new production monitoring tools as well. In fact, Weave is the tool that Weights & Biases used internally to develop the Prompts tools that were announced in April. “It helps us internally bring tools to market really fast, as we can make visual experiences on new data types really easily.” “Weave is a toolkit for composing UIs together, hopefully in a way that’s extremely intuitive to our users and software engineers working with LLMs,” Lewis said. Weave is also about user experience it can help data scientists develop interactive data visualizations. He described Weave as a toolkit containing composable UI primitives that a developer can put together to make an AI application. Lewis explained that Weave was originally conceived as a tool for understanding models and data in the context of a visual, iterative user interface (UI) experience. Register Now AI isn’t just about models, it’s about visualizing how to use them ![]()
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