
Medtronic invests $700M in surgical partner Cornerstone Robotics
Sentire combines clinical workflows with integrated engineering, software, and imaging technologies. | Source: Cornerstone Robotics Medtronic PLC today announced a new partnership with Cornerstone Robotics Ltd. that includes a $700 million investment. Medtronic has also gained the rights to distribute Cornerstone Robotics’ Sentire surgical system in select markets outside the U.S. where the system is approved. Medtronic will distribute Sentire alongside its own Hugo robotic-assisted surger
Medtronic, a Minneapolis-based medical device company, invested $700 million in Cornerstone Robotics and gained distribution rights to its Sentire surgical system in select markets outside the U.S. Medtronic will now offer two robotic-assisted surgery platforms: its own Hugo system and the newly partnered Sentire system, which has completed multi-specialty clinical trials and received market approval in China, the European Union, and Singapore. This dual-platform approach matters because it expands access to robotic surgery by giving surgeons and health systems more options suited to their varying clinical needs and preferences. The partnership reflects Medtronic's broader strategy to drive growth in minimally invasive surgery, an area where Hugo procedures are already growing at more than double the rate of the overall robotic surgery market.
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Browse AI courses on MavenGoogle DeepMind releases new advanced robotics AI model and next-generation gene prediction model
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Gemini Robotics 2.5 accelerates real-world general dexterity
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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

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