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Overland AI Showcases Fully Autonomous Tactical Vehicle at Army Applications Lab Demo

In a recent experimentation event, Overland AI showcased the capabilities of its fully autonomous tactical vehicle at a demonstration hosted by the Army Applications Lab. Attended by combat engineers from across multiple U.

Anduril Teams with Microsoft to Advance IVAS Program for U.S. Army

Anduril and Microsoft partner to advance the IVAS program, delivering next-gen AR/VR and AI capabilities to the US Army, enhancing battlefield awareness and mission command.

He sold Deliverr to Shopify for $2.1 billion. Now his new startup is betting big on an AI assistant named Augie.

Deliverr cofounder Harish Abbott has raised $25 million for his startup building an AI assistant for logistics companies.

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Apollo Go: AI-Powered Autonomous Ride-Hailing Services Advancing Toward Mass Deployment

As artificial intelligence reshapes global industries, the transportation sector is undergoing a profound transformation. Autonomous driving technology is accelerating towards large-scale deployment,

AI is Taking Over Aviation--And These Two Companies Just Hit the Accelerator

Archer and Palantir are teaming up to revolutionize flight with AI-powered manufacturing and next-gen air traffic control.

2025: The Defining Year for Autonomous Vehicle Adoption

The Defining Year for Autonomous Vehicle Adoption" was previously published in February 2025 with the title, "Autonomous Vehicles: Why 2025 Will Usher in the Self-Driving Car." It has since been updated to include the most relevant information available.

Cyngn Inc. (CYN) Expands Autonomous Vehicle Solutions with DriveMod Deployments Across Key Industries

We recently compiled a list of the Top 8 Must-See AI News Updates Investors Probably Missed. In this article, we are going to take a look at where Cyngn Inc.

Autonomous vehicles on trial: Who's liable when AI breaks the rules?

One of the key challenges in AV integration is ensuring that these vehicles comply with traffic laws in a way that is predictable and transparent to human drivers. Traditional machine-learning-based approaches to AV decision-making often rely on large datasets and black-box AI models,