Robotics

Ondas acquires DZYNE for $875.8M, expanding its defense capabilities

Grasshopper delivers autonomous aerial resupply in contested environments. | Source: DZYNE Technologies Ondas Inc. last week acquired DZYNE Technologies LLC, an Irvine, Calif.-based defense technology company. The acquisition is valued at $875.8 million and was financed through a cash-and-stock structure. Ondas said the acquisition will give it complementary capabilities across multi-domain intelligence, surveillance, and reconnaissance (ISR); counter-uncrewed aerial systems (UAS); precision str

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Ondas Inc. acquired DZYNE Technologies, a defense technology company, for $875.8 million in a cash-and-stock deal. The acquisition combines DZYNE's capabilities in autonomous aircraft, counter-unmanned aerial systems, and other defense technologies with Ondas' existing robotics and networking portfolio to create an integrated defense platform. DZYNE, founded in 2012, brings proven autonomous systems including long-endurance aircraft for surveillance, kinetic interceptors for countering drones, and autonomous cargo delivery systems. Ondas established a new operating division called Ondas Sentinel to unify these defense technologies under a single organization with shared technology roadmaps and software platforms.

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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

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Gemini Robotics 2.5 accelerates real-world general dexterity

Our most capable vision-language-action model enhances robot dexterity, reliability, and safety

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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

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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

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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

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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