
Amazon’s Bhavana Chandrashekhar to speak at RoboBusiness’ Women in Robotics Lunch
From left to right: Bhavana Chandrashekhar and Joyce Sidopoulos. Currently, women make up just 35% of the global STEM workforce and 22% of the global AI workforce. This means many women in the robotics industry struggle to find community with other women. At RoboBusiness 2026, which will be on Oct. 20 and 21 in Santa Clara, Calif., spend an hour connecting with robotics professionals in an environment designed for thoughtful conversation and mentorship. The Women in Robotics Lunch is an opportun
A senior manager of applied science at Amazon Robotics will participate in a Women in Robotics Lunch at an industry conference in October 2026, where she will discuss AI and robotics with the co-founder of MassRobotics. Women represent only 35 percent of the global STEM workforce and 22 percent of the global AI workforce, making such networking events designed to build community and mentorship among women in robotics significant. The lunch is one of several programming at RoboBusiness 2026, a conference focused on commercial robotics development and applications across multiple industries.
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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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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