Search

103 results

Clear filters
  • NOV. 7, 2025 / AI

    Announcing the Agent Development Kit for Go: Build Powerful AI Agents with Your Favorite Languages

    The Agent Development Kit (ADK), an open-source, code-first toolkit for building powerful and sophisticated AI agents, now supports Go. ADK moves LLM orchestration and agent behavior directly into your code, giving you robust debugging, versioning, and deployment freedom. ADK for Go is idiomatic and performant, leveraging Go's strengths, and includes support for over 30+ databases and the Agent-to-Agent (A2A) protocol for collaborative multi-agent systems. Start building today!

    Agent Development Kit: Making it easy to build multi-agent applications
  • NOV. 4, 2025 / AI

    Agent Garden - Samples for learning, discovering and building

    Agent Garden is now available to all users to simplify AI agent creation and deployment using the Agent Development Kit (ADK). It provides curated agent samples, one-click deployment via Agent Starter Pack, and customization through Firebase Studio. It helps developers with complex business challenges and multi-agent workflows, with Renault Group cited as an early success story.

    Train a GPT2 model with JAX on TPU for free
  • OCT. 30, 2025 / AI

    Beyond Request-Response: Architecting Real-time Bidirectional Streaming Multi-agent System

    The blog post argues the request-response model fails for advanced multi-agent AI. It advocates for a real-time bidirectional streaming architecture, implemented by the Agent Development Kit (ADK). This streaming model enables true concurrency, natural interruptibility, and unified multimodal processing. ADK's core features are real-time I/O management, stateful sessions for agent handoffs, and streaming-native tools.

    ADK + Gemini CLI: Supercharge Your Agent Building Vibe
  • OCT. 8, 2025 / Web

    Own your AI: Learn how to fine-tune Gemma 3 270M and run it on-device

    This guide shows you how to fine-tune the Gemma 3 270M model for custom tasks, like an emoji translator. Learn to quantize and convert the model for on-device use, deploying it in a web app with MediaPipe or Transformers.js for a fast, private, and offline-capable user experience.

    OYOAI_Metadata_RD2-V01
  • OCT. 8, 2025 / AI

    Announcing the Genkit Extension for Gemini CLI

    The new Genkit Extension for Gemini CLI gives the command line deep knowledge of Genkit's architecture. It helps you build, debug, and iterate on AI apps with intelligent code generation, context-aware assistance, and tools to run flows and analyze traces directly from your terminal.

    Gemini-CLI-Extension-for-Genkit-Blog-Meta
  • OCT. 7, 2025 / AI

    Building High-Performance Data Pipelines with Grain and ArrayRecord

    To avoid data bottlenecks when training large models, this guide introduces Grain and ArrayRecord for building high-performance data pipelines.

    The Agentic experience: Is MCP the right tool for your AI future?
  • OCT. 3, 2025 / AI

    Level Up Your Dev Game: The Jules API is Here!

    Google has released the Jules API, a new tool for developers to automate and integrate the software development lifecycle. The API is based on "Source," "Session," and "Activity" concepts, and Google has provided a quickstart guide to help developers begin using it.

    Thumb_API
  • OCT. 1, 2025 / AI

    Gemini for Home: Expanding the Platform for a New Era of Smart Home AI

    Google Home is enabling new Gemini-powered features for our partners’ devices and launching a new program to help them build the next generation of AI cameras.

    Geminicomingtohome_Hero
  • SEPT. 30, 2025 / AI

    Introducing Tunix: A JAX-Native Library for LLM Post-Training

    Tunix is a new JAX-native, open-source library for LLM post-training. It offers comprehensive tools for aligning models at scale, including SFT, preference tuning (DPO), advanced RL methods (PPO, GRPO, GSPO), and knowledge distillation. Designed for TPUs and seamless JAX integration, Tunix emphasizes developer control and shows a 12% relative improvement in pass@1 accuracy on GSM8K.

    Tunix logo
  • SEPT. 29, 2025 / AI

    Gemma explained: EmbeddingGemma Architecture and Recipe

    EmbeddingGemma, built from Gemma 3, transforms text into numerical embeddings for tasks like search and retrieval. It learns through Noise-Contrastive Estimation, Global Orthogonal Regularizer, and Geometric Embedding Distillation. Matryoshka Representation Learning allows flexible embedding dimensions. The development recipe includes encoder-decoder training, pre-fine-tuning, fine-tuning, model souping, and quantization-aware training.

    Building-2-banner