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  • JULY 29, 2025 / AI

    A roboticist's journey with JAX: Finding efficiency in optimal control and simulation

    Max's journey introduces LQRax, a JAX-native LQR solver, which exemplifies the growing JAX robotics ecosystem that includes tools like Brax, MJX, and JaxSim, highlighting the benefits of JAX for computational efficiency in optimal control and simulation, and for seamlessly integrating model-based and learning-based approaches.

    JAX_meta
  • JULY 24, 2025 / AI

    People of AI podcast Season 5 is here: Meet the builders shaping the future

    Co-hosted by Ashley Oldacre and Christina Warren, People of AI podcast's Season 5 will focus on the builders in the space of AI, highlighting the unique journeys, challenges, and triumphs of these innovators.

    People of AI Podcast – Season 5
  • JULY 24, 2025 / AI

    The agentic experience: Is MCP the right tool for your AI future?

    Apigee helps enterprises integrate large language models (LLMs) into existing API ecosystems securely and scalably, addressing challenges like authentication and authorization not fully covered by the evolving Model Context Protocol (MCP), and offering an open-source MCP server example that demonstrates how to implement enterprise-ready API security for AI agents.

    The Agentic experience: Is MCP the right tool for your AI future?
  • JULY 24, 2025 / Google Labs

    Introducing Opal: describe, create, and share your AI mini-apps

    Opal is a new experimental tool from Google Labs that helps you compose prompts into dynamic, multi-step mini-apps using natural language, removing the need for code, allowing users to build and deploy shareable AI apps with powerful features and seamless integration with existing Google tools.

    Opal Metadata card
  • JULY 23, 2025 / Firebase

    Unleashing new AI capabilities for popular frameworks in Firebase Studio

    New AI capabilities for popular frameworks in Firebase Studio include AI-optimized templates, streamlined integration with Firebase backend services, and the ability to fork workspaces for experimentation and collaboration, making AI-assisted app development more intuitive and faster for developers worldwide.

    Unleashing new AI capabilities for popular frameworks in Firebase Studio
  • JULY 22, 2025 / Gemini

    Gemini 2.5 Flash-Lite is now stable and generally available

    Gemini 2.5 Flash-Lite, previously in preview, is now stable and generally available. This cost-efficient model is ~1.5x faster than 2.0 Flash-Lite and 2.0 Flash, offers high quality, and includes 2.5 family features like a 1 million-token context window and multimodality.

    Gemini 2.5 Flash is making it easy to build with the Gemini API in Google AI Studio
  • JULY 21, 2025 / Gemini

    Conversational image segmentation with Gemini 2.5

    Gemini's advanced capability for conversational image segmentation allows intuitive interaction with visual data by understanding complex phrases, conditional logic, and abstract concepts, streamlining developer experience and opening doors for new applications in media editing, safety monitoring, and damage assessment.

    Conversational image segmentation with Gemini 2.5
  • JULY 17, 2025 / Gemini

    Build with Veo 3, now available in the Gemini API

    Veo 3, Google’s latest AI video generation model, is now available in paid preview via the Gemini API and Google AI Studio. Unveiled at Google I/O 2025, Veo 3 can generate both video and synchronized audio, including dialogue, background sounds, and even animal noises. This model delivers realistic visuals, natural lighting, and physics, with accurate lip syncing and sound that matches on-screen action.

    Build with Veo 3, now available in the Gemini API and Google AI Studio
  • JULY 16, 2025 / AI

    Unlock Gemini’s reasoning: A step-by-step guide to logprobs on Vertex AI

    The `logprobs` feature has been officially introduced in the Gemini API on Vertex AI, provides insight into the model's decision-making by showing probability scores for chosen and alternative tokens. This step-by-step guide will walk you through how to enable and interpret this feature and apply it to powerful use cases such as confident classification, dynamic autocomplete, and quantitative RAG evaluation.

    logprobs_meta
  • JULY 16, 2025 / Cloud

    Stanford’s Marin foundation model: The first fully open model developed using JAX

    The Marin project aims to expand the definition of 'open' in AI to include the entire scientific process, not just the model itself, by making the complete development journey accessible and reproducible. This effort, powered by the JAX framework and its Levanter tool, allows for deep scrutiny, trust in, and building upon foundation models, fostering a more transparent future for AI research.

    Stanford Marin project in JAX