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This post explores building a RAG-based code knowledge assistant using three chunking strategies and evaluating them with MLflow.
This post provides a technical guide for developers on optimizing AI model training using Google's seventh-generation Ironwood TPU within the JAX and MaxText ecosystems.
This post explains how to build an intelligent personal finance assistant by combining LlamaParse and Gemini 3.1 Pro to extract structured data from complex financial PDFs.
This post outlines the safety-first approach taken in building Sora 2 and the Sora app as a video generation model and social creation platform.
This post introduces coSTAR, Databricks' methodology for reliably testing and iterating on AI agents using MLflow.
Mazda built a GenAI-powered service assistant on Databricks Lakehouse to help hotline agents diagnose vehicle issues faster and more accurately.
IBM Research releases Mellea 0.4.0 and three Granite Libraries for building structured, verifiable, and safety-aware AI workflows on IBM Granite models.
This post explains how to monitor AI agents end-to-end using the OpenLIT SDK and Grafana Cloud for distributed tracing, metrics, and cost visibility.
This post explains how to set up end-to-end observability for LLM applications in production using Grafana Cloud, OpenLIT SDK, and OpenTelemetry.
Cloudflare's Workers AI now supports large frontier open-source models, launching with Moonshot AI's Kimi K2.5 to power agentic workloads on a unified platform.
Databricks announces the Public Preview of AI Runtime (AIR), a serverless training stack enabling on-demand distributed GPU training on NVIDIA A10s and H100s.
Pinterest describes how they built a production MCP (Model Context Protocol) ecosystem to enable AI agents to safely automate engineering tasks.