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Google AI Releases Auto-Diagnose: An Large Language Model LLM-Based System to Diagnose Integration Test Failures at Scale

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If you have ever stared at thousands of lines of integration test logs wondering which of the sixteen log files actually contains your bug, you are not alone — and Google now has data to prove it. A team of Google researchers introduced Auto-Diagnose , an LLM-powered tool that automatically reads the failure logs from a broken integration test, finds the root cause, and posts a concise diagnosis directly into the code review where the failure showed up. On a manual evaluation of 71 real-world failures spanning 39 distinct teams , the tool correctly identified the root cause 90.14% of the time . It has run on 52,635 distinct failing tests across 224,782 executions on 91,130 code changes authored by 22,962 distinct developers , with a ‘Not helpful’ rate of just 5.8% on the feedback received. https://ift.tt/TCLkE2I The problem: integration tests are a debugging tax Integration tests verify that multiple components of a distributed system actually communicate to each other corre...

A End-to-End Coding Guide to Running OpenAI GPT-OSS Open-Weight Models with Advanced Inference Workflows

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In this tutorial, we explore how to run OpenAI’s open-weight GPT-OSS models in Google Colab with a strong focus on their technical behavior, deployment requirements, and practical inference workflows. We begin by setting up the exact dependencies needed for Transformers-based execution, verifying GPU availability, and loading openai/gpt-oss-20b with the correct configuration using native MXFP4 quantization, torch.bfloat16 activations. As we move through the tutorial, we work directly with core capabilities such as structured generation, streaming, multi-turn dialogue handling, tool execution patterns, and batch inference, while keeping in mind how open-weight models differ from closed-hosted APIs in terms of transparency, controllability, memory constraints, and local execution trade-offs. Also, we treat GPT-OSS not just as a chatbot, but as a technically inspectable open-weight LLM stack that we can configure, prompt, and extend inside a reproducible workflow. Copy Code Copi...