Large, well-capitalized AI research ventures have recently demonstrated that investors and top technical talent believe AI-accelerated discovery is investable at industrial scale — in physical engineering specifically. Project Agora proposes testing a structurally different version of the same underlying bet: that the same mechanism — high-weight AI models performing the investigative work, with a small human team providing direction and validation — generalizes across the full range of human inquiry, at a small fraction of the capital, and with its findings published rather than held proprietary. EM Foundation has already built and proven the core architecture. This page describes what exists, what scaling it would take, and how to help fund that next stage.
Large physical-AI research ventures in 2025–2026 have raised tens of billions of dollars to pair frontier AI models with sizable human research teams, aimed at compressing the cycle from idea to validated physical result — for example, in engineering design and manufacturing. This is a legitimate and closely watched bet: that AI can meaningfully compress the distance between a hypothesis and a validated outcome, given enough capital and enough specialized human talent.
There is a second, less capital-intensive version of the same bet, and it does not require billions of dollars or a large research staff to test. It requires treating high-weight AI models not as tools that assist a human research team, but as the primary investigative workforce — generating hypotheses, retrieving and grounding evidence, running adversarial verification against each other, and escalating to specialized compute when a finding warrants it — with a small human team providing direction, ethical oversight, and final validation.
This is not a hypothetical. It is already built, already running, and already has 65 published outputs to show for it.
Everything below is live, checkable infrastructure, not a roadmap. It was built by a small technical team working with frontier AI models as engineering partners, at infrastructure cost.
Full source: emfoundation.net/publications.html — every claim above is independently checkable.
Project Agora — a working name — proposes scaling the CIRE/MMDE architecture into a standing, multi-domain research institution: many parallel, adversarially-verified, evidence-grounded research programs running simultaneously, in mathematics, physical and quantum-adjacent science, AI safety and governance, and economic and regulatory policy, using frontier models as the primary investigative workforce.
| Typical large-capital physical-AI venture | Project Agora | |
|---|---|---|
| Primary workforce | A sizable human research staff, AI-assisted | High-weight AI models, human-directed and human-validated |
| Domain scope | Physical engineering | Domain-agnostic: mathematics, physics, AI safety, economics, policy |
| Typical capital scale | Billions of dollars | Illustrative order-of-magnitude: $1.5–2.75M/year operating (see Section 4) |
| Output posture | Proprietary | Public by design — every finding, including negative results, published |
| Validation model | Internal research staff | Explicit funded external-expert validation layer above a confidence threshold |
| Track record so far | Varies by venture | 65 published, independently checkable outputs already live |
The figures below are an order-of-magnitude framework for discussion, not a completed costing. A real budget requires real diligence — the same standard this Foundation applies to its own research findings before publication.
| Illustrative cost category | Range |
|---|---|
| Frontier model API costs at scale (20–50 parallel programs, heavy multi-model adversarial cycles, quantum-compute escalation) | $50K – $300K / yr |
| Small core human team (technical lead, 2–4 domain stewards, 1 infrastructure/ops) | $600K – $1.2M / yr |
| Funded external-expert validation panel (paid domain specialists, per-finding review) | $300K – $800K / yr |
| Infrastructure, hosting, quantum compute credits, data/API licensing | $100K – $250K / yr |
| Legal, governance, and publication infrastructure | $100K – $200K / yr |
Illustrative total: roughly $1.5M – $2.75M per year — several orders of magnitude below typical large-capital physical-AI ventures, for a broader domain scope.
The recent wave of large-capital physical-AI ventures demonstrates that AI-accelerated research is investable at scale, in one domain. It does not demonstrate whether the same mechanism generalizes to the full space of human inquiry — mathematics, safety, economics, policy — where discovery has historically depended on institutional access that EM Foundation's own published research argues is unevenly distributed (see "The Curiosity Dividend," September 2026).
Project Agora is a test of that broader claim: that a transparent, publicly-accountable research institution can run at the same technical frontier, across more domains, for a small fraction of the capital.
Project Agora is currently a proposal, not yet a running program. EM Foundation is seeking founding sponsors to move it from proposal to operation. Several paths are open, and the right structure depends on diligence and counsel on both sides:
Fund one research domain or program directly — for example, a specific Millennium Prize track, an AI-safety research line, or a post-automation economics program — with sponsor attribution on all resulting publications.
Provide compute, API access, or cloud credits in kind — the single largest recurring cost category as the program scales.
Grant support to EM Foundation for AI Research, Inc. (501(c)(3) public charity, EIN 42-3000086) to fund the public-research-infrastructure version of this program directly. Tax-deductible to the extent allowed by law.
Back one flagship program to a public, independently-judged milestone as a proof point before a larger commitment.
For sponsorship inquiries, contact research@emfoundation.net. Individual supporters can also contribute directly via the Foundation's general donation page.