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Defense Technology

Lunar infrastructure starts with interoperability

The Defense Advanced Research Projects Agency (DARPA) has announced the 10-Year Lunar Architecture (LunA-10) capability study. The effort will examine how a future lunar economy might move from isolated, self-sufficient projects toward shareable and scalable infrastructure for power, communications, logistics, and other services.

The timing of that architectural work matters. Interoperability is easiest to praise before systems exist and hardest to achieve after every provider has optimized a private solution.

AI cyber defense needs a transition path

The Defense Advanced Research Projects Agency (DARPA) has launched the Artificial Intelligence Cyber Challenge (AIxCC), a two-year competition aimed at using artificial intelligence to find and fix vulnerabilities in widely used software. Anthropic, Google, Microsoft, OpenAI, and the Open Source Security Foundation are participating in the effort, with competitions planned around DEF CON.

The challenge is ambitious for good reason. Software underpins critical infrastructure, and human defenders cannot manually inspect every dependency at the speed new vulnerabilities appear. The difficult work will begin when a winning technique meets a real maintainer's backlog.

Trustworthy AI needs a research agenda, not a slogan

Researchers from academia, industry, and government are gathering this week for the Defense Advanced Research Projects Agency's Artificial Intelligence (AI) Forward workshop. The agenda centers on a question that is easy to state and difficult to engineer: how can AI systems operate reliably, interact appropriately with people, and support national-security needs under demanding conditions?

Calling a system trustworthy does not make it so. Trustworthiness has to be decomposed into research questions, engineering evidence, and operational learning.

Trustworthy decision support must be tested in the moment

The Defense Advanced Research Projects Agency (DARPA) has selected teams for its In the Moment program, which is exploring how machines might support difficult decisions when established rules are incomplete. Initial research focuses include mass-casualty triage and other settings where time, uncertainty, and competing values make judgment unusually demanding.

This is a serious test of human-centered artificial intelligence: not whether a model can produce an answer, but whether a human–machine team can make a better decision under pressure without obscuring who remains responsible.

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