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Technology Orchestration for National Optimization:
Executive Summary:Ā
Executive Summary:Ā
Objective: Accelerate AI adoption within the government through strategic private-public sector knowledge transfer. It relates to "Enable AI Adoption" and "Accelerate AI Adoption in Government", sections of the AI Action Plan.
Key Provisions:
Establish mechanisms for the diffusion of private-sector AI expertise to US startups and the government.
Create incentive frameworks for targeted AI projects through voluntary and rotational personnel.
Meet Bimhox, an AI technical expert who spent the last five years pouring his energy and passion into serving a large tech corporation in Silicon Valley. Today is his first day of sabbatical, and he deserves a break.
Back at the drawing board, Bimhox began thinking about how he could better serve his community. As he pondered new ways to give back, he had an idea: revisit one of his long-forgotten passion projects. After grabbing a mint mojito coffee, he mentally scrolled through his catalog of half-started ideas. Ah-ha. Idea #41 š”š. Perfect another great one.
But as the caffeine ā kicked in and his neurons began to fire in familiar patterns, a new thought surfacedāidea #42. A flash of inspiration. With his sabbatical, he finally had three uninterrupted months for deep work. Bimhox was off to work.Ā
While refining his idea, Bimhox had a call with his friend Brannon, who lives in Washington, D.C. Brannon mentioned a brand-new initiative that had just launched: Technology Orchestration for Nation Optimization. š§āš»
Bimhox's ears perked up. Intrigued, he asked for more information. The next day, an elegantly designed brochure landed in his inbox. š© After reading it, Bimhox was captivated. It outlined a new government-backed program tied to national AI priorities, perfectly aligned with the recently released āAI Action Planā. The program was now accepting applications for a unique role they called an "AInaut."Ā
AInauts. The word made Bimhox pause. He lived in Palo Alto, the epicenter of innovation. Couldnāt his idea just as easily become the next big startup? Maybe. But then he read something that changed his perspective.
He learned that the program allowed participants to contribute existing stock, without triggering capital gains, if the stock was reinvested into this public-aligned innovation program.
Bimhox stared at the number: š²4 million in vested stock. With the AI race accelerating and a paradigm shift looming, he felt the pressure to act fast. He could either leverage his skills now, or risk being left behind.
It was risky, but then again, so was space travel š§āšš.
He thought of Armstrong again. Of the risks astronauts took for a greater mission. The term "AInaut" was beginning to feel serious. Not life-or-death serious, but real and meaningful. Bimhox submitted his proposal. His alignment score came back at 100%.
That guaranteed him an interview. The application's parametersāand even the LLMs used to process themāwere open-source. Transparency, they said, was part of the process.
Weeks later, the NIST Foundation [1,3] committee met, together with the Center for AI Standards and Innovation (CAISI) [2]. Eleven members, Ā including venture capitalists, government officials from the Department of Labor, Commerce, and Energy, and startup founders, reviewed Bimhox's proposal.Ā
It aligned perfectly with a top-priority, internally drafted mission. The full details are classified, but we can say this: It involved increasing data quality through a participatory framework.Ā
In this framework, AI models could trace causation, attribute outputs to original data contributors, and ensure that those contributorsāthe peopleācould share in the benefits. All of this was done while protecting privacy and offering full opt-out rights. The committee saw its potential and forwarded it to CAISI for orchestration. CAISI's job was threefold:
Identify which government entities would benefit most (such as the NSF, IRS, or NIH).
Find if other funding from grants, challenges, or agencies could be allocated.
Identify or define standards and baselines for the project.
The Proposal: Market-Driven Participatory Framework
The Proposal: Market-Driven Participatory Framework
This section covers Bimhox's proposal.Ā
High Quality Data
High Quality Data
Scientific Discovery
Scientific Discovery
Support Next-Generation Manufacturing
Support Next-Generation Manufacturing
Soon after, Bimhox received the acceptance letter. š
He coordinated with all the committee members, plus other startup CEOs who were identified as potential collaborators in this project in exchange for providing some equity to Bimhox. Under the new model, the foundation could co-invest alongside Bimhox, who could use his non-taxed RSUs for this project along with other government funding if it was previously allocated to similar projects. It was a high-risk, high-reward play. His stake could increase a hundredfold or drop to zero. But the mission wasn't just financial.
If Bimhox succeeded, he would receive a Medal of Honor š . CAISI would define the key metrics and standards. These KPIs were supposed to be achievable within a year. Bimhox accepted. He built. He launched. And yes, he contributed toward secure and efficient AI systems to serve the best interests of US, THE PEOPLE.
Cite:
@article{CDI_TONO20250730,
Ā Ā Ā Ā Ā Ā Ā Ā title = {Technology Orchestration for National Optimization: AInauts},
Ā Ā Ā Ā Ā Ā Ā Ā author = {Computational Design Institute board of directors},
Ā Ā Ā Ā Ā Ā Ā Ā keywords = {AInauts, Technology Orchestration, National Optimization}
}
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