Tag: Google

Gemini 3 is available via API with updates for developers: new `thinking_level` for depth control, `media_resolution` for multimodal processing, and enforced `Thought Signatures` for agentic workflows, especially with function calling and image generation. It also introduces combining Google Search/URL Grounding with Structured Outputs and new usage-based pricing for Grounding. Best practices, like using default temperature, are advised for optimal results.

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!

Coral NPU is a full-stack platform for Edge AI, addressing performance, fragmentation, and user trust deficits. It's an AI-first architecture, prioritizing ML matrix engines, and offers a unified developer experience. Designed for ultra-low-power, always-on AI in wearables and IoT, it enables contextual awareness, audio/image processing, and user interaction with hardware-enforced privacy. Synaptics is the first partner to implement Coral NPU.

Google is releasing Veo 3.1 and Veo 3.1 Fast, an updated video generation model, in paid preview via the Gemini API. This version offers richer native audio, greater narrative control, and enhanced image-to-video capabilities. New features include guiding generation with reference images, extending existing Veo videos, and generating transitions between frames. Companies like Promise Studios, Latitude, and Whering are already using Veo 3.1 for various applications.

We're excited to announce an enhancement to Gemini CLI that makes your workflow more powerful a...

Introducing the Jules extension for Gemini CLI, an autonomous sidekick for developers. It accelerates coding workflows by offloading tasks like asynchronous work, bug fixes, and changes in new branches to Jules, while you stay in flow with Gemini CLI. Get started by installing the extension and using the /jules command to initiate and check task statuses.

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.

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.

The new **User Simulation** feature in the Agent Development Kit (ADK) replaces rigid, brittle manual test scripts with dynamic, LLM-powered conversation generation. Developers define a high-level `conversation_plan`, and the simulator handles the multi-turn interaction to achieve the goal. This dramatically reduces test creation time, builds more resilient tests, and creates a reliable regression suite for AI agents.

Metrax is a high-performance JAX-based metrics library developed by Google. It standardizes model evaluation by offering robust, efficient metrics for classification, NLP, and vision, eliminating manual re-implementation after migrating from TensorFlow. Key strengths include parallel computation of "at K" metrics (e.g., PrecisionAtK) for multiple K values and strong integration with the JAX AI Stack, leveraging JAX's performance features. It is open-source on GitHub.