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The Department of Defense is backing up its AI ambitions with serious money. This month saw multiple significant contracts that outline the military's priorities in autonomous systems, cybersecurity, and intelligence applications.

Big AI deals

Palantir secured a $99.2 million Army contract focused on user-centered machine learning research through 2029. In parallel, Jericho Security won the first-ever generative AI defense contract, landing $1.8 million to develop cybersecurity solutions for the Air Force. The company will focus on simulating complex phishing attacks and creating personalized security training.

Anthropic formed key partnerships with Palantir and AWS to provide AI services to intelligence agencies. This arrangement will give Claude, Anthropic's AI assistant, access to classified information to support government data analysis.

Hardware innovations

On the hardware front, Allen Control Systems unveiled Bullfrog, an AI-enabled counter-drone platform. The system combines computer vision with a conventional machine gun on a rotating turret, offering improved mobility at under 400 pounds. This aligns with the Pentagon's "Replicator" initiative for autonomous defense systems and addresses growing concerns about weaponized drones in modern conflicts.

Clear priorities

These contracts reveal three focus areas for military AI:

The variety and scale of these contracts suggest the military is moving decisively beyond experimentation into operational deployment of AI systems across multiple domains.

The coming months will likely reveal more major defense contracts as the Pentagon continues implementing its AI strategy. With clear priorities now established through these initial deals, we can expect to see accelerated development in autonomous systems, cybersecurity, and intelligence applications.

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Our partners at Bagel (the AI & cryptography research lab) just released some new research on two complementary methods for advancing AI reasoning: training-time and inference-time techniques.

The findings suggest combining both approaches: training-time builds foundational reasoning, while inference-time optimizes its application. Bagel Network supports this advancement through open-source infrastructure, empowering a community-driven AI evolution through monetizable open source AI.

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Alexander Reben, OpenAI's first artist in residence, used AI technology to transform digital creations into physical sculptures, including a striking four-foot marble piece carved from white Italian marble with black and gray veins. Utilizing Nvidia’s neural radiance field technology and Sora's AI text-to-video tool, he generated 3-D models that Monumental Labs then etched into marble.