Google AI for Developers19h ago

Bringing Visual Graph Debugging to Custom Edge Compilers with Model Explorer

Google AI Edge Model Explorer now supports custom compiler intermediate representations and open-source adapters like TOSA, VGF, and PTE for on-device machine learning. Developers can leverage hierarchical graph visualization, split-pane views, and per-node trace overlays to catch export regressions and verify hardware delegation. These tools enable engineering teams to transparently debug execution graphs and pinpoint cycle-level latency bottlenecks locally.

Google AI for Developers19h ago

Announcing New vLLM and SGLang Inference Engines on TPU

This post announces native PyTorch backends for vLLM and SGLang powered by TorchTPU, enabling developers to run and optimize serving workloads using familiar PyTorch tools. Built in collaboration with open-source project maintainers, these engines include optimized TPU kernel implementations, production-ready features like KV cache management with TPU Sync, and disaggregated serving. Public benchmarks demonstrate state-of-the-art performance and industry-leading cost efficiency on Ironwood TPU across long-context and agentic workloads.

Google AI for Developers19h ago

Integrating TorchTPU into TorchTitan and Optimizing Models for TPU

TorchTPU integrates a native torch.device("tpu") backend directly into PyTorch, allowing developers to train large-scale models on Google Cloud TPUs without rewriting code in JAX. The TorchTitan TPU fork enhances this with production-grade scaling primitives like SimpleFSDP, Graph Trainer, and custom Pallas kernels that achieve high Model Flops Utilization (MFU) across dense and MoE architectures. Developers can leverage these battle-tested optimization playbooks, recipes, and the Hugging Face modeling backend to efficiently scale their own workloads on TPU infrastructure.

Google AI for Developers19h ago

Unifying Edge AI: How Coral NPU’s open standard brings portable, energy-viable intelligence from model to silicon

Google Research has completed the 32-bit open-source Coral NPU RISC-V architecture with the introduction of its Matrix Execution Unit, which delivers up to 1 TOPS while targeting 10 mW average power for edge inference. Alongside this architecture, the release of the v1.0 open-source IREE/MLIR compiler allows developers to take models from JAX, PyTorch, and TensorFlow straight to Coral NPU hardware without writing custom assembly. Developers can now prototype and deploy these multimodal edge applications using new hardware options like the Synaptics Astra SR200 MCU series and globally available Coralboard devkits.12

GitHub1d ago

GitHub Copilot models deprecated on October 19, 2026

As of today, October 19, 2026, we have deprecated the following models across most GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions). These…

GitHub1d ago

Copilot model policy API for enterprise, orgs, and teams

You can now use the REST API to retrieve and update Copilot model policies for enterprises, enterprise teams, agent apps, and organizations. What’s new GET and PATCH endpoints are now…

Google AI for Developers1d ago

Native Model Authoring for Edge with LiteRT Tensor API

Meet the LiteRT Tensor API: giving developers native C++ control over the model graph to unify end-to-end ML computations on heterogeneous edge hardware.

Google AI for Developers1d ago

Step by Step guide: Build a Voice Agent That Never Goes Silent using ADK

The open-source Agent Development Kit (ADK) and gemini-3.8-live enable developers to build responsive voice agents by implementing non-blocking tools in Python. Developers can use streaming tools to yield progress updates or background execution patterns to keep conversations fluid during long-running backend queries. Additionally, configuring response scheduling behaviors such as WHEN_IDLE, INTERRUPT, or SILENT gives developers precise control over when and how tool results are delivered into the conversation.

Cursor4d ago

Cloud Agent Canvases and Environment Improvements

#Canvases from cloud agents Cloud agents can now build interactive canvases as part of their work. Share a finished canvas with your team by sending its link. Learn more about sharing canvases. #Environments API The Environments API is now available in beta. Use it to programmatically create and manage the cloud environments your agents run in. #Larger, faster environments Cloud agent environments now support up to 300 repositories. Large environments also load 5x faster.

GitHub5d ago

Upcoming deprecation of selected GitHub Copilot models in mid-November

We will deprecate the following models across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions) on November 16th, 2026: Model Deprecation date…

Google AI for Developers5d ago

Announcing DPoP Support for Google OAuth: Securing Refresh Tokens

Google OAuth Platform now supports DPoP (Demonstrating Proof-of-Possession) to sender-constrain refresh tokens, neutralizing Infostealer malware and adversary-in-the-middle attacks. By cryptographically binding long-lived refresh tokens while maintaining short-lived access tokens as standard Bearer tokens, developers achieve robust credential security without incurring high-QPS API performance overhead. Additionally, developers integrating multi-agent or Model Context Protocol (MCP) workloads can use Google Cloud Secure Token Service (STS) to handle secure token delegation across agent chains.

Google AI for Developers5d ago

Three layers, one repo: a tour of google/adk-recipes

The google/adk-recipes repository unifies Agent Development Kit (ADK) resources into three structured layers—core/, plugins/, and contrib/—serving as a single source of truth for building AI agents. Developers can leverage reference patterns, install modular vertical skills (such as retail product search and virtual try-on) directly into their coding assistants, and deploy production-ready services across multiple languages. This cohesive structure streamlines the entire workflow from initial scaffolding to full deployment on Google Cloud infrastructure.

GitHub5d ago

Agentic autofix for code scanning alerts general availability

Agentic autofix for code scanning alerts is now generally available. It remediates alerts by working across your codebase the way a developer would: it explores relevant files, proposes a fix,…

Google AI for Developers5d ago

Evaluating AI agents: moving past the vibe check

A practical engineering guide and reference architecture for establishing continuous evaluation pipelines for multi-turn AI agents using Gemini Enterprise Agent Platform, Google ADK, and OpenInference standards.

GitHub6d ago

HydraFusion updates and new Max option

HydraFusion has an updated model pool, improved orchestration workflows, and introduces HydraFusion Max. Both HydraFusion and HydraFusion Max are available across VS Code, the GitHub Copilot app, and GitHub Copilot…

Google AI for Developers6d ago

Announcing MCP support in Apigee hybrid: agentic tools that run in your own cluster

Apigee hybrid 1.17.0 introduces native Model Context Protocol (MCP) support, enabling the MCP data plane to run directly within your own Kubernetes cluster. This architecture ensures that AI agent request traffic and tool execution remain entirely inside your infrastructure while pulling configuration updates from the control plane. Developers can expose OpenAPI 3.0.x specifications as discoverable MCP tools, leverage existing security policies and API products, and trace end-to-end requests using W3C trace context headers.

Anthropic6d ago

Anthropic opens Singapore office and signs MOU with the Government of Singapore

Cursor7d ago

Origin App Marketplace

Origin now integrates with over 20 apps for deployments, CI, code review, security, monitoring, and project management, from partners including Cloudflare, Linear, Sentry, and Socket Security. Starting today, the marketplace is also open to public submissions, so any team building developer tools can publish an app for Origin. #Apps for your stack The marketplace now includes apps for: Deployments: Cloudflare, Netlify, Render, Spacelift, and Vercel CI: Buildkite, CircleCI, CloudBees, Depot, EngFlow, Namespace, and RWX Code review: CodeRabbit, Greptile, and Tenki Security: Artemis Security, Semgrep, Socket Security, and Upwind Monitoring: Sentry Project management: Linear #Publish to Marketplace To submit an app: Create an app in your namespace. It stays private to your namespace while you build. Build against the Origin API. Apps authenticate with an app JWT and installation access tokens, receive webhook events, and write back check runs, pull request comments, and reviews. Make the app public, then submit it from the app's page with a slug, suggested tags, and a demo video. The video should show install, uninstall, and your core product flows. We review the submission and list the app once it's approved. #Get started Try the apps in the Origin App Marketplace today. Want to build an Origin app? Start with the publishing guide and the Origin API reference. The Origin Apps plugin can also answer questions from the live Origin API docs and plan a port to Origin for an app you already run.

GitHub7d ago

Gemini 4 Argon in GitHub Copilot

Gemini 4 Argon, Google’s newest frontier model, is now generally available in GitHub Copilot. It is designed for complex coding, agentic, and reasoning tasks. In early testing, Gemini 4 Argon…

GitHub7d ago

Enterprise managed settings enforcement updates

Enterprise administrators can now require supported GitHub Copilot clients to retrieve current server-managed settings at startup instead of relying on a cached policy. We are also adding minimum client version…