Mistral AI released its first embodied navigation model, Robostral Navigate. The 8B model uses one ordinary RGB camera without LiDAR or depth sensors, achieving 76.6% success in unseen R2R-CE validation environments, 9.7 percentage points above the best single-camera approach and 4.5 points above the best depth- or multi-camera system.
Hugging Face and Cerebras jointly demonstrated a real-time speech-to-speech pipeline, accelerating Gemma 4 31B inference with Cerebras and combining Nvidia Parakeet speech recognition with Alibaba Qwen3TTS synthesis.
Google DeepMind released Nano Banana 2 Lite (gemini-3.1-flash-lite-image) and Gemini Omni Flash (gemini-omni-flash-preview).
Mistral released OCR 4, returning bounding boxes, block-type classifications and per-page and per-word confidence alongside text extraction. It supports 170 languages and single-container self-hosting. Independent annotators preferred OCR 4 on average 72% of the time in blind evaluations of over 600 documents. It scored 85.20 on OlmOCRBench and 93.07 on OmniDocBench, though Mistral warns both benchmarks have known scoring limitations.
Google Research released vector data converting Farmscapes 2020 high-resolution raster maps into usable inventories of hedgerows, stone walls and coppices across over 130,000 square kilometres of the UK. The framework fine-tunes an RSF Vision-Transformer pretrained on over 300 million global satellite images with around 247 square kilometres of labelled data. Polsby–Popper compactness distinguishes woodland, clusters of trees and hedgerows, with a threshold below 0.5 for linear features.
The UK AISI alignment team and Timaeus co-founded nonprofit Sequent, arguing alignment research is unprepared for superintelligence. It plans 40–80 full-time staff within two to three years and initial fundraising of $100–150 million.
Google published two studies on AI-assisted understanding of skin problems. In a survey of 2,345 participants, over 62% using AI tried to name a skin condition versus 41% in the control group, with 23% accuracy, nearly triple the control group's 8%. A mixed-methods study examined how people use these tools for their own skin concerns, their understanding and differences in doctor communication. AI offered limited help in deciding the next steps for seeking care.
Google DeepMind released Gemini 3.5 Live Translate, a near-real-time speech-to-speech translation model supporting more than 70 languages, with automatic language detection and preservation of speakers' intonation, rhythm and pitch.
Google DeepMind released Gemma 4 12B, a multimodal model for local laptop use between the edge-focused E4B and 26B MoE. Its unified encoder-free architecture feeds visual and audio inputs directly into the LLM backbone.
Google Research published a study in Nature introducing PHRM, which records video with a phone’s front camera in the seconds after face unlock and uses deep learning to estimate heart rate and resting heart rate in the background.
Google Research unveiled the experimental Gemini for Science toolkit at I/O 2026, including Computational Discovery based on ERA and AlphaEvolve, Hypothesis Generation based on Co-Scientist and Literature Insights based on NotebookLM.
Google DeepMind added Street View grounding to experimental prototype Project Genie. Users select a real US location with a Maps pin, choose a style and describe a character, then Genie creates an interactive world whose starting location is grounded in real imagery.
Google DeepMind released Gemini Omni Flash, the first model in the Gemini Omni family, generating high-quality video from combined image, audio, video and text inputs and supporting iterative video editing through natural-language conversations.
Google announced the expansion of content transparency and verification tools to Search, Gemini, Chrome, Pixel and Cloud. SynthID has watermarked over 100 billion images and videos and 60,000 years of audio. SynthID verification in the Gemini app has been used 50 million times and will reach Search and Chrome in the coming weeks.
Google DeepMind and Singapore's government formed a national AI partnership with new projects in healthcare, research, education and climate. It explores an AI-assisted triadic-care model, uses AlphaFold and Google Earth for Southeast Asian infectious-disease research and develops a Gemma-based running assistant to help visually impaired athletes train independently.
Google DeepMind launched the Gemini 3.5 family with 3.5 Flash, focusing on agents and coding. It is available from today in the Gemini app, Google Search AI Mode, Google Antigravity, Gemini API and Gemini Enterprise.
Google DeepMind announced AI co-clinician research to explore AI agents assisting patient care under clinical supervision. In blinded assessments of 98 real primary-care queries, 97 responses had no critical errors, and doctors preferred them to existing evidence-synthesis tools. Across 140 consultation skills, AI matched or exceeded primary-care doctors on 68, but expert doctors were better overall at recognising red flags and guiding key physical examinations.
Google DeepMind launched Gemini 3.1 Flash TTS, a new text-to-speech model emphasising stronger controllability, expressiveness and audio quality. From today, developers can preview it through Gemini API and Google AI Studio, enterprises through Vertex AI, and Workspace users can use it in Google Vids.
Google DeepMind released Gemini Robotics-ER 1.6, an upgraded reasoning-first robotics model with stronger spatial reasoning and multi-view understanding. New instrument reading capabilities cover circular pressure gauges, level indicators and digital readouts.
Google released PaperVizAgent for paper illustrations and ScholarPeer for automated peer review. PaperVizAgent combines retrieval, planning, style, visualisation and review agents, scoring 60.2 on a 0–100 evaluation, ahead of GPT-Image-1.5, Nano-Banana-Pro and Paper2Any. It was the only framework above the 50.0 human baseline.
Google DeepMind released the open-source Gemma 4 family in four sizes—E2B, E4B, 26B MoE and 31B Dense—under Apache 2.0.
Google released Vibe Coding XR, combining Gemini with the XR Blocks framework based on WebXR, three.js and LiteRT.js to turn natural language prompts directly into physically aware Android XR apps, reportedly in under 60 seconds.
Google Research announced healthcare AI advances at The Check Up, including its Personal Health Agent (PHA) research with Fitbit, which found it supported long-term health better than single-task apps.
The AIMS collaboration between Google Research and several NHS organisations published two companion studies in Nature Cancer evaluating an AI breast cancer detection system within NHS screening workflows.
Mistral AI released Mistral Small 4, the next major version in the series and its first model to combine Magistral reasoning, Pixtral multimodal capabilities and Devstral agentic coding in one model, under Apache 2.0.
Mistral AI released Mistral OCR 3 with an overall 74% win rate against Mistral OCR 2 on forms, scans, complex tables and handwriting. The company says its accuracy exceeds enterprise document-processing and AI-native OCR solutions.
Mistral released the Mistral 3 family, comprising 14B, 8B and 3B small dense models and its strongest yet Mistral Large 3, a sparse MoE with 41B active and 675B total parameters. All are open-source under Apache 2.0.
Mistral fine-tuned Pixtral-12B with LoRA, substantially outperforming the untuned baseline on Aerial Image Dataset (AID) satellite classification and reducing hallucinated invalid class names. Fine-tuning uses Mistral's API or LaPlateforme UI without extensive hyperparameter tuning, with 8,000 training and 2,000 test samples.
Mistral added features to Le Chat including preview Deep Research, Voxtral-powered voice mode, multilingual reasoning with Magistral, Projects for organising conversations and image editing with Black Forest Labs.
Mistral AI released Mistral Medium 3, claiming at least 90% of Claude Sonnet 3.7’s performance on several benchmarks. Pricing is $0.40 per million input tokens and $2 per million output tokens.
Mistral AI released Mistral Small 3.1, improving text performance and multimodal understanding over Small 3, expanding context to 128k tokens and reaching 150 tokens per second, under Apache 2.0.
Mistral AI introduced Mistral OCR, an optical character recognition API that reads images and PDFs and outputs text and images interleaved in order. It is already the default document understanding model for millions of Le Chat users.