The White House’s Office of Management and Budget (OMB) has made a public call for suggestions on how federal agency privacy impact assessments could address the escalating risks with the increasing complexity of technologies such as artificial intelligence (AI).
In the increasingly important world of artificial intelligence (AI), Steve Sousa, Senior Vice President at CGI’s federal arm, advocates that its integration offer federal health care agencies ample opportunities to improve patient outcomes.
The FTC’s inquiry into partnerships between AI developers and major cloud providers was a competition investigation. It also surfaced a practical enterprise-architecture problem.
Organizations often select a model as though it were a separable service. In reality, the decision can commit them to a chain of cloud infrastructure, identity, data platforms, safety controls, networking, application tooling, commercial terms, and strategic relationships. The model endpoint is the visible interface to a larger dependency system.
For public-sector and regulated buyers, architecture diligence should begin by mapping the cloud behind the model.
The Department of Justice (DOJ) has unveiled that the FBI is exploring the use of Amazon’s Rekognition, an image and video analysis software.
In a recently unveiled “white paper,” Chief of Space Operations Gen. Chance Saltzman emphasizes the critical importance of timely and active space domain awareness (SDA) in American defense strategy.
Revised and substantially expanded July 17, 2026.
The National Artificial Intelligence Research Resource (NAIRR) pilot began in January 2024 with an unusual coalition: the National Science Foundation, other federal agencies, and dozens of private-sector and nonprofit contributors offering compute, datasets, models, platforms, training, and expertise. The coalition was correctly celebrated as evidence that the United States could mobilize resources across institutional boundaries.
Collaboration, however, is not self-governance.
When public research infrastructure depends on contributed commercial resources, the central design question is not whether industry should participate. It should. Industry operates much of the world's advanced AI infrastructure and holds expertise that a public program cannot recreate quickly. The hard question is whether the resulting system advances an independent public mission—or quietly becomes a distribution channel for the technical architectures, pricing models, and research priorities of its largest contributors.
The distinction turns on institutional design. A durable NAIRR must be able to accept private contributions without becoming dependent on any particular donor; offer researchers useful proprietary capabilities without making their work nonportable; and learn from vendors without delegating public allocation and assurance decisions to them.
In short, a national resource should be grateful for donations but architected to survive their withdrawal.
The Defense Information Systems Agency (DISA) is currently grappling with several security challenges as it progresses in developing a pioneering AI ‘concierge.’ Steve Wallace, the Project Lead, shared the ambitions to roll out the prototype in the first half of the current year.
Northrop Grumman is making strides in enhancing global missile tracking capabilities with an innovative system named ‘False Track Reduction Using Machine Learning.’