Report shares the state of physical AI and robotics
While robotics developers have used artificial intelligence for years, the past few years have seen a fundamental shift in how the technologies work together. Rather than rely solely on deterministic programming for things like navigation and object recognition, robots are increasingly able to perceive, comprehend, decide, and act with AI. Physical AI is not just a buzzword; it’s also enabling the future of automation in factories, warehouses, and beyond. In this free download, readers wil
Physical AI represents a fundamental shift in how robots work, moving beyond pre-programmed instructions to perceive, comprehend, decide, and act using artificial intelligence for tasks like navigation and object recognition. This technology is enabling automation across factories, warehouses, and other domains, though its success depends on domain-specific data and different training approaches. Physical AI companies have raised over $23 billion in venture capital so far, with major investments focused on foundation models, industrial automation, autonomous vehicles, and humanoid form factors. The technology is being deployed to address labor shortages and precision needs across various markets, while also creating demand for hyperscale data centers that require simulation, fleet orchestration, and reasoning capabilities.
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Google 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
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Boston Dynamics adds wheels to Atlas humanoid to test whole-body control
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Practice Makes Precise: At CoRL, NVIDIA and Partners Reveal How Robots Rehearse Delicate Work in Simulation
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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