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Advancing AI with Gemini and Project Astra to create a universal, multitasking AI assistant that understands context, plans, acts, and enhances productivity across devices with a focus on safety and responsibility.

Discover the latest breakthroughs in generative media models and tools like Veo 3, Imagen 4, Lyria 2, and Flow that empower artists with advanced video, image, music, and filmmaking AI capabilities.

Pinterest reduced machine learning feature iteration times by up to 90x through an evolving multi-stage backfill system leveraging Spark, Iceberg, and Ray for efficient data processing, partitioning, and training-time joins.

Explore streamlined deployment of MCP servers on Fly.io, combining local simplicity with remote security and robust configuration management across multiple clients and environments.

A step-by-step guide to deploying machine learning models using MLflow on high-performance Lambda Cloud GPU instances, covering setup, configuration, and best practices for streamlined model lifecycle management.

An addendum providing additional details regarding the o3 and o4-mini system card named Codex.

An overview of Codex, a powerful AI model that translates natural language into code.

Explore how Stripe's Payments Intelligence Suite leverages advanced AI models to enhance payment authorization, reduce fraud and disputes, and provide actionable analytics for maximizing revenue.

Researchers from MIT, Harvard, and the Broad Institute developed PUPS, an AI-powered computational method that predicts the subcellular location of any protein within single human cells, enhancing disease diagnosis and biological understanding without extensive lab work.

AlphaEvolve leverages Gemini-powered large language models and automated evaluation to autonomously discover and optimize advanced algorithms, significantly enhancing computational efficiency and solving complex mathematical problems.

Exploring how AI technologies are transforming marketing strategies at Expedia.

MIT researchers reveal that vision-language models struggle with negation in queries, impacting accuracy in real-world applications but show improvement after retraining with negation-inclusive datasets.