Sep 30, 2026 | Gemini 4 Argon delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense. Today, we’re announcing our new frontier model, Gemini 4 Argon, which is rolling out to a set of trusted cyber defenders through our Fairwind Program.
Condé Nast partnered with the AWS Generative AI Innovation Center (GenAIIC) to build multimodal video retrieval on Amazon Bedrock and Amazon OpenSearch Service, using the TwelveLabs Marengo embedding model to jointly encode visuals, audio and transcripts.
Microsoft Research released Quine, an AI research system for biological complexity, comprising a biological world model trained on multimodal data spanning sequences, structures, functions, cell states and imaging, and an interactive harness connecting the model, scientific tools, literature and experimental researchers.
MSRA – Singapore, Microsoft's first research lab in Southeast Asia, spent its first year focusing on next-generation AI models and agent systems, domain AI, AI-native research practices and talent ecosystems. It works with Singapore's healthcare ecosystem on multimodal medical AI and self-evolving diagnostic agents, and jointly held a logistics and transport AI executive roundtable with EDB in February 2026.
Using the open-source SkyRL framework on Amazon SageMaker HyperPod, multimodal reinforcement learning post-training with GRPO increased the Qwen3-VL-8B vision-language model’s maze-solving success rate from 43.75% to over 95% on a fixed evaluation set of 64 mazes.
Google Research published research on long-form video generation, proposing an AI video co-director multi-agent orchestration framework built on Gemini and Veo to plan visual continuity across multi-shot narratives.
Google DeepMind released Gemini 3.8 Live with Live Avatar, adding near-real-time video generation to a native live conversation model to create a dynamic visual avatar that can hear, see and speak. It is available on Gemini Enterprise from today.
Liquid AI released experimental draft model LFM2.5-VL-DSpark for vision-language model LFM2.5-VL-3B. Speculative decoding speeds it up without changing output quality: decoding improves by up to 3.13x on devices and 2.66x on H100, with end-to-end gains of up to 2.62x and 2.27x respectively.
Google DeepMind released Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS. The former targets character design and line-by-line performance direction, while the latter targets high-concurrency voiceovers and voice agents.
NVIDIA and partners showcased AI deployment progress in Southeast Asia at Singapore AI Day. Singapore's HTX is researching public-safety AI based on Nemotron 3 Super and Nemotron 3 Nano Omni.
Google DeepMind and Google Research released WeatherNext 3, calling it the most advanced and accurate global weather model available. It learns directly from real-time geostationary Earth-observation satellite data and generates hourly forecasts, with five-kilometre resolution for key surface variables and roughly five times the overall detail of WeatherNext 2.
Hugging Face launched NeoMME in 260M and 800M sizes. A single bidirectional Transformer handles text tokens and 32×32 image patches, trained from scratch with a masked discrete diffusion objective rather than pretrained vision towers or causal language models.
Google DeepMind introduced agentic video understanding for Gemini 3.7 Flash, 3.6 Flash and 3.5 Flash-Lite, reducing video analysis token use by up to 88% and costs by up to 66%, while improving accuracy by up to 7%.
Google DeepMind released Gemini Omni 1.1 Flash, offering developers more controllable video generation through the Gemini API in Google AI Studio.
Google released research prototype AgentHands, published at CHI 2026, mapping LLM reasoning to speech-synchronised hand animations in XR headsets so agents can point and demonstrate object operations in 3D. It combines environment perception, a gesture event library, gesture-embedding reasoning and local synchronised execution, supporting deictic, iconic and expressive gestures. In an N=12 user study, it significantly improved spatial reference over voice-only interaction.
Google Research proposed PhotoScan, a deep learning framework that estimates body fat percentage, A/G ratio and V/S ratio from ordinary 2D phone photos to predict insulin resistance.
Hugging Face's OlmoEarth Studio now computes and exports embeddings. Users choose an area, period, encoder variant and resolution through UI or API and receive Cloud-Optimized GeoTIFF (COG) results.
Microsoft Research introduced MindTopo to evaluate multimodal models' reasoning and planning over connectivity, enclosure, order, separation and knotting. Current models perform much better at static-image recognition than interactive planning, with failures mainly in planning rather than perception and overall performance far below humans. Image and video generation helps only when preserving structural relations in a single frame; multi-step operations often change topology or violate constraints.
Google DeepMind released SL2T, a multilingual sign-language-to-text model, bringing the capability to consumer products for the first time. Gboard and Live Transcribe on Pixel 11 support ASL-to-English dictation, with more devices and languages to follow.
Google Research released AMIE (Video), built on Gemini and Project Astra, for real-time video clinical consultations. It can perceive non-verbal cues and guide virtual physical examinations.
Microsoft Research released CARE-X, a unified chest X-ray vision-language research model for report generation and structured prediction. It rewards clinical correctness using multitask reinforcement learning (DAPO). Generation and dual-inference modes cover lesion presence and negation, localisation, multilabel classification, catheter and tube malposition detection, and localisation of 29 anatomical regions.
NVIDIA released Magpie TTS Multilingual, a 364M-parameter open-weight speech synthesis model supporting English, Spanish, French, German, Italian, Vietnamese, Chinese, Hindi and Japanese, plus newly added Modern Standard Arabic, Korean and Brazilian Portuguese, for 12 languages in total.
Meta released Muse Glimmer, a multimodal model distilled from Muse to 30B parameters under Apache 2.0, targeting local agent use cases such as coding, document analysis and personal assistants.
Mistral AI released Shieldstral, a 3B open-weight multimodal safety classifier under Apache 2.0 that runs on one 16 GB NVIDIA GPU. It frames moderation as policy-adaptive question answering: policies written in natural language at inference time produce calibrated safety scores without retraining, handling text and images uniformly. Official claims say it matches models up to seven times larger on text safety and sets new best results on multimodal moderation benchmarks.
Google DeepMind released Gemini Robotics ER 2 as a high-level brain for robots, supporting video understanding, multi-step task orchestration and multi-robot collaboration, while delegating action execution to lower-level VLA models.
Google DeepMind released Gemini Robotics 2, a next-generation robot intelligence layer achieving whole-body control of a complete humanoid robot for the first time, with fine manipulation using both hands and grippers.
NVIDIA introduced Cosmos-H-Dreams, a real-time action-conditioned generative simulator for surgical robots. It runs through FlashDreams on one RTX PRO 6000 GPU and supports closed-loop interaction by humans and policies.
Google Research published SymptomAI research, using five Gemini Flash 2.0 agents with different questioning strategies for symptom interviews and differential diagnosis, involving 13,917 participants.
Google DeepMind released three models: Gemini 3.6 Flash, 3.5 Flash-Lite and cybersecurity-focused 3.5 Flash Cyber.
DharmaOCR scored 0.925 on a Portuguese OCR benchmark, ahead of Mistral OCR4's 0.798 and Unlimited-OCR's 0.7587. It specialised through two-stage training: supervised fine-tuning on Portuguese corpora, then DPO to stabilise inference. The author argues that concentrating parameters on one language remains a structural advantage despite emerging architectures.
Thinking Machines released Inkling on Hugging Face, a multimodal MoE model with around one trillion parameters, a one-million-token context and native image, text and audio inputs, alongside Inkling-Small with 276 billion total and 12 billion active parameters.
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.
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.