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Litestream has been revamped with advanced features like fast point-in-time restores, lightweight read replicas using VFS, and scalable multi-database synchronization by integrating transaction-aware techniques from LiteFS and leveraging modern object storage capabilities.

Highlights from the Modular GPU Kernel Hackathon showcasing groundbreaking Mojo-based GPU kernel innovations, collaborative problem-solving, and community-driven advancements in AI infrastructure.

Google DeepMind details how automated red teaming, model hardening, and multi-layered defenses enhance Gemini 2.5's resilience against indirect prompt injection attacks for secure and trustworthy AI agents.

SynthID Detector is a new portal by Google that identifies AI-generated content across multiple media types by detecting imperceptible SynthID watermarks to enhance transparency and authenticity verification.

Gemini 2.5 enhances AI capabilities with improved performance, advanced reasoning, native audio, security, and developer tools for more intelligent, efficient, and secure applications.

Gemma 3n introduces a mobile-first, efficient AI model with cutting-edge architecture and Per-Layer Embeddings for low-memory, on-device multimodal processing, enabling real-time applications and responsible development accessible now in preview.

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.