2732 results
MARCH 31, 2026 / AI
The newly introduced continuous checkpointing feature in Orbax and MaxText is designed to optimize the balance between reliability and performance during model training, addressing issues with conventional fixed-frequency checkpointing. Unlike fixed intervals—which can either compromise reliability or bottleneck performance—continuous checkpointing maximizes I/O bandwidth and minimizes failure risk by asynchronously initiating a new save operation only after the previous one successfully completes. Benchmarks demonstrate that this approach significantly reduces checkpoint intervals and results in substantial resource conservation, especially in large-scale training jobs where mean-time-between-failure (MTBF) is short.
MARCH 31, 2026 / AI
The launch of Agent Development Kit (ADK) for Go 1.0 marks a significant shift from experimental AI scripts to production-ready services by prioritizing observability, security, and extensibility. Key updates include native OpenTelemetry integration for deep tracing, a new plugin system for self-healing logic, and "Human-in-the-Loop" confirmations to ensure safety during sensitive operations. Additionally, the release introduces YAML-based configurations for rapid iteration and refined Agent2Agent (A2A) protocols to support seamless communication across different programming languages. This framework empowers developers to build complex, reliable multi-agent systems using the high-performance engineering standards of Golang.
MARCH 30, 2026 / AI
Google has released version 1.0.0 of the Agent Development Kit (ADK) for Java, introducing powerful new features like Google Maps grounding, built-in URL fetching, and a standardized Agent2Agent protocol for cross-framework collaboration. The update enhances agent control through a new "App" and "Plugin" architecture, which allows for global logging, automated context window management via event compaction, and "Human-in-the-Loop" workflows for action confirmations. Additionally, the release provides robust session and memory services using Google Cloud integrations like Firestore and Vertex AI to manage long-term state and large data artifacts.
MARCH 25, 2026 / AI
To bridge the gap between static model knowledge and rapidly evolving software practices, Google DeepMind developed a "Gemini API developer skill" that provides agents with live documentation and SDK guidance. Evaluation results show a massive performance boost, with the gemini-3.1-pro-preview model jumping from a 28.2% to a 96.6% success rate when equipped with the skill. This lightweight approach demonstrates how giving models strong reasoning capabilities and access to a "source of truth" can effectively eliminate outdated coding patterns.
MARCH 24, 2026 / Mobile
The provided workflow streamlines motion-controlled game development by using Gemini Canvas to rapidly prototype mechanics like the MediaPipe Pose Landmarker through high-level prompting. Developers can refine these prototypes in Google AI Studio by optimizing for low-latency "lite" models and stable tracking points, such as shoulder landmarks, to ensure responsive gameplay. The process concludes by using Gemini Code Assist to refactor experimental code into a modular, production-ready application capable of supporting various multimodal inputs.
MARCH 23, 2026 / AI
This blog post introduces a workflow for extracting high-quality data from complex, unstructured documents by combining LlamaParse with Gemini 3.1 models. It demonstrates an event-driven architecture that uses Gemini 3.1 Pro for agentic parsing of dense financial tables and Gemini 3.1 Flash for cost-effective summarization. By following the provided tutorial, developers can build a personal finance assistant capable of transforming messy brokerage statements into structured, human-readable insights.
MARCH 18, 2026 / AI
This blog post introduces a suite of six protocols, such as MCP and A2A, designed to eliminate custom integration code by standardizing how AI agents access data and communicate. Using a "kitchen manager" agent as a practical example, it demonstrates how these tools handle complex tasks like real-time inventory checks, wholesale commerce via UCP, and secure payment authorization through AP2. By leveraging the Agent Development Kit (ADK), developers can also implement A2UI and AG-UI to deliver interactive dashboards and seamless streaming interfaces to users.
MARCH 17, 2026 / Cloud
When you’re prototyping locally with AI agents like Gemini CLI, Claude Code, or your own agent, thei...
MARCH 11, 2026 / AI
Gemini CLI now features Plan Mode, a read-only environment that allows the AI to analyze complex codebases and map out architectural changes without the risk of accidental execution. By leveraging the new ask_user tool and expanded Model Context Protocol (MCP) support, developers can collaboratively refine strategies and pull in external data before committing to implementation.
MARCH 10, 2026 / AI
The Gemini Code Assist team has introduced a suite of updates focused on streamlining the core coding workflow through high-velocity tools like Agent Mode with Auto Approve and Inline Diff Views. These enhancements, along with new features for precise context management and custom commands, aim to transform the AI from a general assistant into a highly tailored, seamless collaborator that adapts to your specific development style.
