Google DeepMind published research introducing SynthIDBio, a system that watermarks AI-designed proteins without compromising their function. Built on Google's SynthID technology (used for text/image watermarking), the system works with ProteinMPNN, a popular protein design tool, to embed detectable signals during the amino acid placement process. The watermark is randomly distributed across the protein sequence and can be detected using a cryptographic-like key, even though proteins only use 20 amino acids and have far less 'room' to hide signals than images.
Google is rolling out Guided Vision in Gemini Live on compatible Android devices, allowing users to share their phone camera and get real-time audio descriptions of surroundings, objects, and text like fine print. The feature is aimed at people who are blind or have low vision, similar to Apple's VoiceOver Live Recognition. Users can ask follow-up questions, such as reading an expiration date on an identified item, and the feature is also available via Google TalkBack or an accessibility shortcut on Android 9+.
OpenAI launched two new shopping features in ChatGPT globally: a virtual try-on tool that lets users upload a photo to see how clothing or accessories would look on them, and a Favorites feature to save products to a Library for later. Both features use the newly launched ChatGPT Images 2.5 model, which OpenAI says improves lighting, textures, instruction-following and reduces image generation latency. This follows OpenAI's earlier pivot away from an instant checkout feature that underperformed.
Google's TPU engineering team reproduced the Allen Institute for AI's fully open Olmo 3 7B model from scratch using MaxText, a JAX/XLA training framework, matching Ai2's PyTorch/GPU reference run on held-out metrics rather than just the training loss curve. The reproduction covered stage-1 pre-training (~5.93T tokens, 1.41M steps) and stage-2 mid-training annealing, including porting Olmo 3's non-standard architecture (reordered-norm block, QK-norm, 3:1 sliding/global attention) to JAX. The team also caught and fixed a subtle data-loader bug that caused training loss to falsely appear better due to memorization, verified by held-out evaluation.
Google engineers describe how they implemented sparse spatio-temporal attention for video diffusion models on TPU v6e chips, converting the theoretical sparsity of the Sparse VideoGen (SVG) approach into real hardware speedups. Through a progression of kernel optimizations (full/boundary tile specialization, tile-size tuning, and mask-tile alignment), they reduced attention kernel latency from 96.37ms (naive sparse) to 32.76ms, a 2.40x speedup over dense Splash Attention on a single TPU v6e chip, using 75.6K tokens, 10 heads, and head dimension 128.
Google DeepMind unveiled SynthID Bio, a watermarking technology that embeds an imperceptible, verifiable signature into AI-designed proteins and 3D structures without compromising their biological function. The system was tested on protein binders (VEGF-A, SARS-CoV-2 spike RBD, PD-L1) using AlphaProteo and a modified ProteinMPNN, and also fine-tuned into AlphaFold 3's diffusion network for watermarking predicted 3D structures. DeepMind is also collaborating with Stanford's Hie lab and Arc Institute to apply the approach to Evo 2, a genomic model, to watermark designed bacteriophage genomes. The goal is to strengthen biosecurity by helping DNA synthesis screening providers and public databases verify the provenance of AI-generated biological designs.
Google Cloud introduced, in public preview, a remote MCP server that exposes the gcloud and bq command-line tools to AI agents via two tools: run_gcloud_command and run_bq_command. The server runs in an isolated, network-restricted sandbox on Google Cloud infrastructure, removing the need for agents to install or maintain local CLI binaries. It uses Agent Identity, OAuth 2.0, and IAM for authentication, integrates with Model Armor to screen for prompt injection, and supports Cloud Audit Logging for full visibility into tool calls.
Google announced that its Antigravity SDK now supports running agentic workflows locally and offline, with initial support for Gemma 4 26B A4B running via Google AI Edge's LiteRT. Developers can build agents that run entirely on-device, without cloud API costs or internet dependency. Google also demonstrated a hybrid 'Architect-Builder' pattern where a cloud model (Gemini 3.8 Flash) plans tasks and a local swarm of Gemma 4 26B instances does the heavy execution, keeping source code off the cloud.
Google Cloud API Gateway now supports acting as a remote MCP server in Public Preview. By annotating an existing OpenAPI spec (x-google-api-management.mcp and x-google-mcp-tool), teams can expose their current REST operations as agent-ready MCP tools without building or hosting a separate MCP server. Existing authentication (JWT/API key), quotas, and logging continue to apply unchanged since MCP and REST traffic share one policy path.
