Gemini Robotics 2 brings whole body intelligence to robots
From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks.
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Gemini 4 Argon: our next era of frontier intelligence
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
MIT Transit Lab to develop an AI platform for public transit agencies
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Introducing Gemini 3.8 Live with Live Avatar
Introducing Gemini 3.8 Live with Live Avatar, which brings near real-time visual presence to Gemini’s conversational AI.
Related papers
Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey
This survey reviews representative Transformer-based autonomous driving models and organizes them by task role, sensing configuration, and architectural design and analyzes how efficiency constraints reshaping model design choices in practice affects deployability, robustness, and safety.
SurgRAW: Multi-Agent Workflow With Chain of Thought Reasoning for Robotic Surgical Video Analysis
This work introduces SurgCoTBench, the first reasoning-focused benchmark in RAS, and proposes SurgRAW, a clinically aligned Chain-of-Thought (CoT) driven agentic workflow for zero-shot multi-task reasoning in surgery, which surpasses mainstream VLMs and agentic systems and outperforms a supervised model.
AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots
This work proposes AtomicVLA, a unified planning-and-execution framework that jointly generates task-level plans, atomic skill abstractions, and fine-grained actions, and introduces a flexible routing encoder that automatically assigns dedicated atomic experts to new skills, enabling continual learning.
Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
This paper introduces POEF (POlicy EFfective Jailbreak), an automated red-teaming framework that takes into account the robot-specific constraints during both the optimization and evaluation processes and proposes two defense strategies that mitigate the behavior jailbreak risks.