Tickets, geofences, and 1M miles: The new reality of California AV compliance
Guident is operating an AuveTech shuttle in South Florida, managing a four-mile route in West Palm Beach and a one-mile route in Boca Raton with its remote monitoring technology. | Credit: Guident California is rewriting the rules of the road for driverless cars, replacing the tech industry’s “move fast and break things” era with strict accountability measures and rigid mileage hurdles. Harold Braun, executive chairman and CEO of Guident, spoke with The Robot Report about the s
California has established new regulatory requirements for autonomous vehicles operating on public roads, replacing flexible testing approaches with strict accountability measures. The new rules require manufacturers to respond to traffic violations within 72 hours (or 24 hours if marked as a public safety priority), equip vehicles with emergency communication systems that must be answered within 30 seconds, and comply with emergency geofencing commands within two minutes. Light-duty autonomous vehicles must complete 50,000 miles of testing with a safety driver and another 50,000 miles without one before commercial deployment, while heavy trucks face a 1 million-mile threshold including at least 200,000 miles on California public roads. These regulations represent a shift from the technology industry's traditional approach toward government-mandated safety oversight and accountability for autonomous vehicles operating alongside the general public.
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Google DeepMind releases new advanced robotics AI model and next-generation gene prediction model
Alphabet Inc.’s artificial intelligence research lab, Google DeepMind, Tuesday debuted the next generation of Gemini Robotics, the company’s most capable vision-language-action model to date for creating an “AI brain” for robotics. Separately, DeepMind announced AlphaGenome 2 today, a next-generation AI model that can predict how DNA sequences and their variations affect human cell types, creating […] The post Google DeepMind releases new advanced robotics AI model and next-generation gene
Also reported by MarkTechPost
Gemini Robotics 2.5 accelerates real-world general dexterity
Our most capable vision-language-action model enhances robot dexterity, reliability, and safety
Also reported by Ars Technica
Can AI agents program industrial robots without training data? Berkeley says yes
The new RoboSimStudio is an open-source project that enables agentic AI coding of robotic simulation environments. | Credit: UC Berkeley UC Berkeley and NVIDIA have released open-source tools for a new approach: enabling teams of AI coding agents to write, simulate, and refine readable robot programs. Since the early days of industrial robots, programming, tuning, and troubleshooting robotic workcells has taken weeks to months. New research coming out of UC Berkeley has demonstrated that new age
Boston Dynamics adds wheels to Atlas humanoid to test whole-body control
Bridging the divide between deterministic physics-based control and policy-driven adaptation, Boston Dynamics has deployed a hybrid locomotion architecture on a wheeled variant of its Atlas humanoid. The “experiment” combined classical model-based motor control with whole-body reinforcement learning to maintain dynamic stability across unstructured, real-world terrain. In the video, Andy Wu, controls engineer for Atlas at Boston Dynamics, highlights some recent experiments that he
Practice Makes Precise: At CoRL, NVIDIA and Partners Reveal How Robots Rehearse Delicate Work in Simulation
Simulation, which has long been the proving ground for robots learning to walk, roll and hop, is now helping researchers teach robots tasks that require a finer touch: aligning gears, connecting cables and assembling small components. The shift from locomotion to manipulation is taking center stage at this week’s Conference on Robot Learning (CoRL) in Austin, Texas, alongside the rise of agentic robotics — a new paradigm that integrates frontier agents to create interpretable code for physical
Memories.ai builds standardized egocentric video pipeline
Memories.ai models label every clip: Memories-H0 for hand pose, EgoAction for action segments. | Credit: Memories.ai Memories.ai is building a data pipeline for robotics companies that combines standardized video collection with AI-powered annotation to turn everyday egocentric footage into training data for robots. The San Francisco-based company is developing software and AI to help robots understand the physical world. It builds video-understanding models and data infrastructure, and it colle