The Department of Defense (DoD) has granted Northrop Grumman clearance to initiate low-rate production of the B-21 Raider stealth bomber, as announced by William LaPlante, Under Secretary for Acquisition and Sustainment at the DoD and a two-time Wash100 awardee. The original article can be found here .
The Defense Advanced Research Projects Agency (DARPA) has initiated a second round of its Tools Competition aimed at discovering innovative artificial intelligence (AI) solutions for enhancing adult learning, particularly in data science and STEM fields.
In an event supported by the Office of Naval Research (ONR), various technologies aimed at bolstering the capability of the U.S. Marine Corps were exhibited. These tech platforms are designed to enhance mine countermeasures, intelligence, surveillance, reconnaissance, and other amphibious undertakings. The original article can be found here .
The Office of the Under Secretary of Defense for Research and Engineering’s 2024 “Unleashing Data at Speed and Scale” outreach asked industry for technologies spanning collection, storage, processing, monitoring, analysis, and communication. The breadth reflected a real challenge: modern military decisions depend on data moving across sensors, networks, computing environments, organizations, classifications, and national boundaries.
It also exposed a recurring acquisition risk. When a problem is described as a list of technical functions, industry responds with products optimized for individual layers. The Department can acquire faster links, larger stores, stronger processors, and more sophisticated models while the mission thread remains fragmented.
The organizing object should be neither the technology nor “the data.” It should be a decision-ready data product with an accountable owner, defined consumers, observable quality, and a mission outcome.
Rep. Don Beyer, Vice Chair of the Congressional AI Caucus and the New Democrat Coalition’s working group on AI, expressed optimism about the prospect of legislation on AI in 2024.
Revision note, July 17, 2026: The original version of this essay overstated the public record. I have not found an official January 2024 announcement of an OpenAI–Department of Defense cybersecurity partnership. What was publicly visible at the time was a change to OpenAI's usage-policy language and secondhand reporting about exploratory national-security work. OpenAI's first official announcement identified in this review of a Department of Defense pilot involving proactive cyber defense was published in June 2025. The analysis below corrects that distinction and develops the more important lesson it exposes.
In January 2024, changes to OpenAI's usage policies generated headlines suggesting that the company had opened the door to military work. The original version of this post converted that signal into a much stronger claim: that OpenAI and the Department of Defense had announced a cybersecurity collaboration at the World Economic Forum in Davos. That conclusion was not adequately supported.
The historical reporting that prompted the post described OpenAI's removal of a categorical reference to “military and warfare” from its prohibited-use language and discussed comments about possible cybersecurity applications. OpenAI's own policy changelog records a January 10, 2024 update, but a policy revision is not a contract announcement, an authority to operate, a fielded capability, or evidence of an operational partnership. The original GovCon Wire article remains useful as a record of how the change was interpreted at the time; it is not sufficient evidence for the claim this essay originally made.
That correction is more than editorial housekeeping. It reveals a recurring error in public-sector technology analysis: collapsing a chain of materially different institutional events into a single word—adoption.
Calls for defense technologies that can collect, store, process, monitor, analyze, and transmit data at scale naturally attract products that maximize one dimension: sensor volume, link capacity, database throughput, analytic speed, or model performance.
Mission systems do not win by maximizing any of those quantities independently. They win by preserving a useful relationship between a changing environment and an accountable decision.
That makes data at speed and scale a control problem. The system must sense, estimate, decide, act, observe the result, and adapt—while delays, uncertainty, adversaries, and limited resources affect every stage.
When the Department of Defense asks industry for technologies covering collection, transport, storage, processing, monitoring, and analysis, it encounters a predictable commercial response: every vendor explains why its platform should become the center of the architecture.
The Department’s problem is not a lack of platforms. It is the cost of composing capabilities across programs, vendors, clouds, classifications, and missions. Selecting another comprehensive product may solve a local integration problem while creating a larger dependency.
The alternative is not to build everything internally. It is to create a data capability market: a governed environment in which products can compete at stable architectural seams and must demonstrate evidence against shared mission threads.