AI in engineering: Engineering teams are adopting AI tools to speed up design iteration, detect system issues earlier, and scale internal expertise without replacing core CAD and simulation systems.

From AI literacy & cybersecurity awareness to leadership & sustainability, here's what engineers must master to thrive amid ...

School hosted the KAIROS 2026 Mega Pool Drive on the theme Where Action Meets Opportunity. Over 500 candidates were connected ...

The round is led by Headline, with new investors Bullhound Capital, Felix Capital, and Daphni. Valuation is undisclosed. Sereact’s vision language action models already run in BMW, Daimler Truck, and ...

Nvidia Corp. and Google LLC used the search giant’s annual Cloud Next event to deepen their long-running partnership, creating a full-stack “artificial intelligence factory” that integrates Google’s ...

Siemens tests a Humanoid robot with Nvidia technology in a live factory trial in Germany, putting autonomous logistics work on the shop floor.

As robotics evolves beyond fixed automation, manufacturers are adopting a new generation of systems designed for flexibility, intelligence and real-world adaptability. In some cases, that shift is ...

Foxconn's US AI factories could reshape global electronics supply chains by accelerating US-based AI server production and offering a replicable smart factory model for overseas sites. The company's ...

The promise of physical AI is that engineers will be able to program physical agents the same way they do digital ones. We’re not there yet. Robotics is still held back by a paucity of data from ...

The two companies announced an expanded partnership at a Cadence conference in Santa Clara on Wednesday. The goal: make robot training data more accurate so physical AI systems reach real-world ...

SANTA CLARA, California, April 15 (Reuters) - Cadence Design Systems (CDNS.O), opens new tab and Nvidia (NVDA.O), opens new tab are partnering to further the development of artificial intelligence for ...

Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity ...