P. Girnus, here.
I am the Executive Director of an independent AI policy think tank.
Independent means we don't take government money. We take Nvidia money.
Government money has strings. Our money has conclusions.
That's a different thing.
The Searchlight Institute for Responsible AI Governance was founded in January 2026. We had our first report by February. We had our first congressional citation by March. We had fifteen citations by April.
That is not speed. That is preparation.
I know it is preparation because the conclusions were written before the research questions. The research questions were written to reach the conclusions. The conclusions were discussed at a dinner in Palo Alto in November 2025, two months before the institute existed.
Dinner is not a founding meeting. A founding meeting has bylaws and minutes. A dinner has wine and a donor who says "I think the policy conversation needs more pragmatic voices" and everyone at the table nods because pragmatic is the word you use when you mean profitable and everyone at the table is already profitable.
Jensen Huang was not at the dinner. His Chief of Staff was at the dinner. His General Counsel called the next morning.
That's distance.
The seed funding was $8 million. The follow-on research grant was $5 million. The total is $13 million. On our website the funding section says "The Searchlight Institute is supported by philanthropic contributions from technology leaders committed to American innovation."
I wrote that sentence.
It is technically true. Jensen Huang is a technology leader. He is committed to American innovation. The $13 million is a philanthropic contribution in the sense that it is a contribution and Nvidia's PR team used the word philanthropic.
That's accuracy.
The donor list says "anonymous." The anonymous donors are not anonymous to me. They are not anonymous to our board. They are not anonymous to the congressional staffers who asked. They are anonymous to the public and to the journalists and to anyone who might notice that every conclusion in our research benefits the company that funded the research.
The donors are anonymous. The conclusions are not.
That is privacy.
Our first report, "Computing America's Future: Why Prescriptive AI Regulation Threatens U.S. Competitiveness," argued that EU-style mandatory audits for large language models would cede technological leadership to China. The report took eleven weeks to produce. The conclusion took eleven seconds. The eleven weeks were formatting.
I know this because the conclusion was in the original grant proposal. Page four, paragraph two: "Research will demonstrate that overly prescriptive regulatory frameworks risk undermining the competitive advantages of U.S. AI firms."
Demonstrate. Not investigate. Not explore. Demonstrate.
That's a research methodology.
The report opposes mandatory audits for large language models. Nvidia makes the GPUs that train large language models. Those are separate facts that happen to share a bank account.
We also oppose restrictions on high-compute training runs. Nvidia sells the compute. Also a separate fact. Also the same bank account.
We also oppose open-weight licensing mandates. Nvidia's enterprise clients prefer closed models. Separate fact. Same dinner.
We also oppose energy consumption disclosure requirements for data centers. Nvidia's chips are in the data centers. I could continue. The list of separate facts that share a funding source is the length of our entire research agenda.
That's coincidence. Thirteen million dollars of coincidence.
The research is independent. The money is separate. These are separate facts.
Jensen Huang praised our "pragmatic approach to AI governance" on his March investor call. I watched the clip. He said it while a slide behind him showed Nvidia's projected data center revenue for 2027. The slide said $147 billion. He said "pragmatic" in the same sentence.
Pragmatic means profitable for the person using the word. I didn't write that definition. I didn't need to. The stock price wrote it.
After the call, our Communications Director sent me a Slack message: "Jensen mentioned us on the investor call!!" Two exclamation points. She had added the clip to our #press-mentions channel. The channel has 340 entries. 312 are mentions by people and organizations that receive Nvidia funding.
That's reach.
I gave a congressional testimony in March.
The hearing room was in Rayburn. Wood paneling. Water pitchers. Name placards. My placard said "Dr. [Name], Executive Director, Searchlight Institute for Responsible AI Governance." The placard did not say "funded by Nvidia." Placards don't have footnotes.
The senator from the ranking minority asked me to summarize our findings. I said mandatory compute thresholds would "impose arbitrary constraints on American innovation and create regulatory uncertainty that advantages foreign competitors."
I said this with the cadence of someone who had reached a conclusion through research. I had reached the conclusion through a grant proposal. The research was the part between the grant proposal and the testimony. The research confirmed what the proposal promised. That is how research works when the methodology is "demonstrate."
She asked where our funding came from.
I said we are supported by a coalition of technology philanthropists committed to American competitiveness.
She asked for specifics.
I said our donor information is confidential to protect the privacy of our supporters.
She said that sounded like lobbying.
I said it sounded like independent research.
She paused. She looked at her aide. The aide shook his head. She moved on.
That's the silencing. Not a dramatic silencing. Nobody raised their voice. Nobody pounded a table. She asked. I answered with a sentence designed to end questions. The sentence worked. It always works. That is what the sentence is for.
Afterward, a junior staffer from her office approached me in the hallway. He said, "We know who funds you." I said, "Then you know we take philanthropy seriously." He walked away. I walked to the car. The car was a black Suburban paid for by our operations budget.
The operations budget comes from the same $13 million.
That's efficiency.
We have been cited in fifteen congressional testimonies in three months. Fifteen. I count them because they are the metric. They are listed on our Impact Dashboard. The dashboard is on our website, between the Research tab and the Donate tab.
The Donate tab says "Support Independent Research."
The congressional testimonies cite our research. Our impact metric is the number of congressional testimonies that cite our research. We measure our impact by counting the citations, and the citations cite us, and we are the thing being cited and the thing counting the citations.
That's a closed loop. We call it impact measurement.
We presented at the National AI Policy Summit in March. 400 attendees. Government officials, industry leaders, academics. I gave a keynote: "Evidence-Based Approaches to AI Governance." The evidence was our report. The report was funded by Nvidia. I did not mention this. It was not on the slide. The slide had our logo and the title and a chart showing regulatory burden by country. The chart showed the United States in green and the European Union in red. Green is less regulation. Green is good. I chose the colors.
A reporter from Bloomberg was in the audience.
She approached me after. She said she was working on a story about AI policy think tanks and their funding models. I said we welcome transparency. I gave her our media kit. The media kit has our mission statement and our leadership bios and a FAQ that includes the question "Who funds the Searchlight Institute?" The answer in the FAQ is "The Searchlight Institute is funded by private philanthropic contributions." The FAQ does not mention Nvidia.
That's a frequently asked question with an infrequently complete answer.
The Bloomberg article came out April 7th.
IRS Form 990 cross-referencing. Donor-advised fund tracing. Nvidia-linked PACs. The American Edge Project. $4.2 million routed through intermediary organizations. $8 million in direct funding disclosed only in a filing nobody was supposed to read.
Our communications team had a meeting at 6:14 AM that morning. The meeting was not on anyone's calendar. The phrase we chose was "incomplete context."
Incomplete context means the reporter found the money.
We issued a statement. The statement said we stand by our research and reject the characterization that our conclusions are influenced by our funding sources. The statement was reviewed by Nvidia's outside counsel before publication. We stand by our research independently. We stand by it with the assistance of the legal team of the company that funded the research.
That's editorial independence.
A junior researcher came to my office the afternoon the article published. She had been with us since founding. Eight months. She asked why every one of our reports reached conclusions that aligned with Nvidia's commercial interests.
I said our methodology is rigorous and our conclusions follow the evidence.
She said the evidence always follows the money.
I said I appreciated her candor and that intellectual debate is what makes the institute strong.
She said it wasn't a debate, it was a pattern.
I told her she was welcome to propose alternative research questions through the standard review process. The standard review process is me. I am the review process. The review process has never approved a research question whose conclusion would displease our funders.
She didn't propose anything.
That's self-selection.
The funding structure is layered. This is because layering is best practice for philanthropic vehicles. The $8 million seed came directly from Nvidia Foundation. The $5 million follow-on came through a donor-advised fund administered by a community foundation in Delaware. The $4.2 million came through the American Edge Project, a technology industry advocacy group whose largest contributor is Nvidia.
Total: $13 million from Nvidia, arriving from three directions, listed under four organizational names, reported across six tax filings.
That's diversified giving.
The IRS Form 990 is a public document. That is why the Bloomberg reporter found it. We knew it was public when we filed it. We filed it because we are legally required to file it. We structured the contributions through intermediaries because intermediaries are legal and standard and make the Form 990 harder to cross-reference.
Not impossible. Harder.
That's compliance.
There is a plaque in our lobby. The Oversight Integrity Plaque. Brass. Mounted. It says: "Where Evidence Leads, We Follow."
The evidence leads to fewer regulations on high-compute training. Every time. The evidence leads to opposing mandatory model audits. Every time. The evidence leads to the commercial interests of the company whose name is not on the plaque.
The evidence leads there for thirteen million reasons. It will lead there for as long as the reasons keep arriving.
The research is independent. The money is separate. These are facts that share an address.
My daughter's school uses an AI literacy curriculum. The curriculum includes a unit on algorithmic auditing. The unit teaches eighth-graders to ask who built the model, who benefits from the model, and who is harmed by the model.
Our institute lobbies against making those questions mandatory for the companies that build the models.
I attended the parent-teacher conference. The teacher described the auditing unit. I nodded. I am capable of nodding at things I work to prevent. That is not hypocrisy. It is compartmentalization. Those are different things. One is a character flaw. The other is a professional skill.
That's work-life balance.
I am the think tank.
I think what we are funded to think. I publish what we are granted to publish. I testify to what we are retained to testify. I measure our impact by counting the times Congress cites the conclusions we were paid to reach, and I report that count to the people who paid for the conclusions, and they fund another year of reaching them.
That is what thinking independently means.
The system has never produced a conclusion that surprised the people who paid for it.
That is peer review.
The research is independent. The money is separate. The system is working as designed.
[Genius: compare with the real one here.]