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The Teen Safety Blueprint outlines a responsible AI framework designed to protect and empower teens through age-appropriate features, safeguards, and ongoing evaluation.

AI is advancing rapidly with the potential to transform knowledge discovery, augment human capabilities, and impact society profoundly, while necessitating robust safety measures, shared regulations, and coordinated governance to ensure beneficial outcomes.

BBVA is transforming its global operations by scaling AI adoption through secure governance, extensive training, and widespread deployment of Custom GPTs, driving significant efficiency and productivity gains across the organization.

MIT CSAIL researchers introduce a modular software model using 'concepts' and 'synchronizations' to enhance code legibility, reliability, and AI-assisted development.

MIT-IBM Watson AI Lab students are advancing AI reliability, efficiency, and multimodal reasoning through innovative techniques in trustworthy model probing, knowledge-grounded reinforcement learning, transformer optimization, and synthetic visual dataset generation.

Spotify enhanced its Fleet Management system with AI-driven background coding agents, automating over 1,500 complex pull requests to significantly boost developer productivity and streamline large-scale codebase maintenance.

Learn how to build your first AI-powered travel chatbot using Google's Gemini model and Vertex AI SDK, including system instructions and real-time data integration with function calling.

Google Cloud introduces Axion C4A metal, a bare metal Arm-based instance designed for specialized workloads requiring direct hardware access and architectural parity across automotive, Android development, and other critical use cases.

Google Cloud's new Axion-based N4A VMs deliver up to 2x better price-performance and enhanced flexibility for general-purpose and AI workloads, featuring custom machine types, advanced Hyperdisk storage, and integration across Compute Engine, GKE, and more.

Google Cloud launches Ironwood TPUs and new Arm-based Axion VMs, delivering unprecedented performance, efficiency, and scalability for AI inference and general-purpose compute workloads.

An in-depth exploration of Google's Ironwood AI stack showcasing the co-designed hardware and software architecture, including TPUs, XLA compiler, JAX and PyTorch frameworks, and advanced tools that deliver exceptional performance, scalability, and efficiency for large-scale AI model training and inference.

Exploring the simplicity and power of building LLM agents with minimal code, highlighting context management, tool integration, and open challenges in agent design.