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Unpacks the hidden technical debt in GenAI systems by contrasting classical ML workflows with GenAI execution and outlining governance, observability, prompting, and tooling practices to manage traces, tool sprawl, and human feedback.

Modular 26.1 advances programmable, portable AI infrastructure by introducing the MAX Python API, strengthening Mojo, and expanding Apple Silicon GPU support to streamline building, debugging, and deploying GenAI models across heterogeneous hardware.

This post examines how Taisei Corporation leverages ChatGPT to shape the next generation of talent through AI-powered training and scalable upskilling.

A practical blueprint for scaling enterprise content review with a three-agent workflow (scanner, verification, and recommendation) powered by Strands Agents and Amazon Bedrock AgentCore to keep technical content accurate and up-to-date.

Modular 26.1 introduces the MAX Python API and Mojo language enhancements to simplify building and deploying GenAI models across heterogeneous hardware, improve developer velocity, and expand Apple Silicon GPU support for faster, portable AI inference.

Details the deprecation of GPT-4o, GPT-4.1, GPT-4.1 mini, and OpenAI o4-mini in ChatGPT and the practical implications for integrations.

Explores the architecture, governance, and operation of OpenAI’s internal data agent, highlighting how autonomous data pipelines enable AI-driven workflows.

Introducing Conversational Analytics in BigQuery enables natural-language data analysis via AI-powered agents that reason over your metadata and enterprise assets directly in BigQuery Studio, delivering precise, contextual insights and predictive capabilities without SQL.

Explores Project Genie and Genie 3, a real-time, general-purpose world model for generating infinite, interactive environments, including world sketching, exploration, and remixing via a prototype accessible to Google AI Ultra users.

Scale-aware, system-level rearchitecture of code review that reconstructs developer intent and enriches context to preserve trust and security under AI-assisted code growth, integrating with GitHub workflows.

A concise technical overview of the BigQuery AI Hackathon, its winning projects, and the latest BigQuery AI capabilities—including AI.IF with sublinear scaling, AI.SCORE, AI.EMBED, AI.CLASSIFY, and AI.SEARCH—alongside vector search and multimodal data features that empower faster, smarter AI-powered solutions.

A technical guide showing how to use Google.Cloud.VertexAI.Extensions for .NET to integrate Google Gemini models on Vertex AI through the Microsoft.Extensions.AI abstractions, with chat, embeddings, and image-generation samples in preview.