Robotics & Automation News

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Decart’s Oasis 3 world model streams realism into robotic training environments

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Frontier AI research lab Decart is aiming to bridge the gap between synthetic simulation and physical AI with the launch of its latest world model, Oasis 3.

Announced recently, the new video output model was designed to accelerate the training of operating system models for robots and autonomous vehicles. The goal is to create intelligent hardware that won’t be fazed by the unpredictable nature of the world it operates in.

Makers of robotics face significant challenges due to the dearth of useful data that can be harnessed to train their machines to operate in complex physical environments. [Read more…] about Decart’s Oasis 3 world model streams realism into robotic training environments

Nebius and Nvidia launch Physical AI Living Lab for European robotics startups

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Nebius, the AI cloud company, has announced the Physical AI Living Lab, a six-month program that equips British and European robotics startups with Nvidia’s physical AI development tools and Nebius’s AI cloud infrastructure. 

Physical AI depends on large-scale simulation, synthetic data, and accelerated compute that most early-stage robotics companies cannot assemble on their own.

The Physical AI Living Lab removes that barrier, putting the same class of tooling and compute used to build physical AI at scale into the hands of founders, so they can move from simulation to real-world deployment faster. [Read more…] about Nebius and Nvidia launch Physical AI Living Lab for European robotics startups

Interview with Columbia professor and co-founder of SceniX Yunzhu Li: ‘Simulation is central’

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The robotics industry is enjoying a surge of investment, media attention, and ambitious promises about the future of humanoid machines.

Companies are announcing plans to manufacture thousands of robots, while advances in artificial intelligence have fueled expectations that general-purpose robots may soon become commonplace in factories, warehouses, workplaces, and even homes.

Yet beneath the excitement lies a fundamental technical challenge that many researchers believe remains far from solved. [Read more…] about Interview with Columbia professor and co-founder of SceniX Yunzhu Li: ‘Simulation is central’

Why robotics can’t advance without physical AI

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The next leap in robotics won’t come from faster processors or more sophisticated mechanical design. It will come from better data, specifically, from training environments that replicate how the physical world actually behaves.  [Read more…] about Why robotics can’t advance without physical AI

Lightwheel reports $100 million in Q1 orders for physical AI robotics infrastructure

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Lightwheel says it secured approximately $100 million in orders during the first quarter of 2026, reflecting what the company describes as a broader industry shift from robotics experimentation toward real-world deployment infrastructure.

Lightwheel is a robotics infrastructure company that develops simulation, synthetic data, evaluation, and deployment systems for training and scaling physical AI robots in real-world environments.

The company says the orders span simulation, synthetic data generation, evaluation systems, and deployment-oriented robotics infrastructure designed to support physical AI applications at industrial scale.

According to Lightwheel, the demand is being driven not simply by interest in robotics hardware or AI models, but by the growing need for systems capable of training, validating, and deploying robots reliably in real operating environments. [Read more…] about Lightwheel reports $100 million in Q1 orders for physical AI robotics infrastructure

Achieving Dataset Parity to Close the Robotics Training Gap

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It was in 1954 when the world witnessed its first real industrial robot, Unimate, a machine built to perform repetitive factory operations.

Fast forward to 2026: today robots like Unitree GD01 are being trained to learn adaptive mobility, AI decision-making, and terrain navigation.

In just half a century, robotics have evolved from immobile programmable arms into intelligent mobile systems capable of seeing and interacting with the physical environments around them. [Read more…] about Achieving Dataset Parity to Close the Robotics Training Gap

Nebius teams with Nvidia to build cloud for robotics and physical AI

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Nebius, the AI cloud company, has announced it is collaborating with Nvidia to accelerate physical AI development with an end-to-end platform purpose-built for the full robotics lifecycle, from simulation and training to real-world deployment at scale.

Combining Nebius’s global AI cloud infrastructure with the Nvidia Physical AI Data Factory Blueprint, an open reference architecture for massive data generation and evaluation, Nebius will provide robotics developers and enterprises an agent-driven environment that addresses the two fundamental barriers to physical AI at scale: infrastructure and tooling fragmentation, and the lack of high-quality training data for rare, unpredictable scenarios that determine real-world success.

“Physical AI is going to be one of the defining technology shifts of this decade, and the teams building it today are being held back by infrastructure and tooling that was never designed for those workloads, ” said Evan Helda, head of physical AI at Nebius. [Read more…] about Nebius teams with Nvidia to build cloud for robotics and physical AI

From Design to Deployment: Synthetic Data Management in Action

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Synthetic data generation has become a practical requirement in modern software delivery. Teams need realistic, compliant datasets on demand – not as a “nice to have”, but as a way to ship faster while reducing privacy risk and improving test coverage.

But most organizations learn quickly that synthetic data generation doesn’t solve the problem by itself. The real challenge is operational: how synthetic data is prepared, governed, maintained, and delivered across environments and pipelines. In practice, synthetic data has to work in two places at once – design and deployment.

That’s the role of enterprise synthetic data management. It turns synthetic data into an operational asset that behaves like real data, preserves cross-system relationships, stays compliant, and is available when teams need it. Here’s what synthetic data management looks like in action – and how organizations move from isolated generation to scalable delivery with K2view. [Read more…] about From Design to Deployment: Synthetic Data Management in Action

Amazon takes ‘major step’ toward zero-touch manufacturing facilities with Nvidia AI

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Amazon, arguably the world’s largest user of robotics technologies, is said to be “powering big leaps” in zero-touch manufacturing with a new physical AI software solutions and digital twin technologies from Nvidia.

Deployed this month at an unnamed Amazon Devices & Services facility, the company’s innovative, simulation-first approach for zero-touch manufacturing trains robotic arms to inspect diverse devices for product-quality auditing and integrate new goods into the production line – all based on synthetic data, without requiring hardware changes.

This new technology brings together Amazon Devices-created software that simulates processes on the assembly line with products in Nvidia-powered digital twins. Using a modular, AI-powered workflow, the technology offers faster, more efficient inspections compared with the previously used audit machinery. [Read more…] about Amazon takes ‘major step’ toward zero-touch manufacturing facilities with Nvidia AI