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Scaling Compute: AI at 1/1000th the Cost was ARIA's first programme, led by Programme Director Suraj Bramhavar, and it targets a deliberately extreme goal: reducing the hardware cost of training large AI models by more than a thousandfold, while decreasing reliance on leading-edge chip manufacturing. It sits within ARIA's Nature Computes Better opportunity space.
The programme was initially backed by 42,000,000 pounds over four years and is now described as backed by nearly 100,000,000 pounds; ARIA has awarded close to 50,000,000 pounds across 12 projects, including a 16,000,000 pound grant to CommonAI for an AI inference lab and work with Oxford engineers on AI system architecture.
Two solicitations structured the original intake across four technical areas: TA1 Bold Solutions, TA2 Bold Ideas, TA3 System-level Software Simulation, and TA4 Testing and Evaluation. The programme is explicitly open beyond academia, having funded researchers and engineers across universities, startups, SMEs, large corporates and public labs.
The critical status point for anyone assessing this now is that there are no open funding calls for the programme: both prior calls are archived and ARIA directs interested parties to register for opportunity-space updates.
It is included here as a live reference for the UK's largest dedicated AI-compute-hardware funding line and because ARIA's model of periodically reopening solicitations within an opportunity space means future calls are plausible.
Teams working on analog, photonic, or otherwise unconventional AI accelerators should track ARIA's funding page directly, and compare against ARIA's separate Scaling Trust and Safeguarded AI programmes, which fund different technical areas.
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Or search similar grants →According to the current listing, eligibility includes: ARIA funds researchers and engineers across a wide range of disciplines, sectors and institutions, explicitly including universities, startups, SMEs, large corporate research groups and public labs; the programme is not restricted to academic applicants. Work is oriented to the UK research and innovation base, and applicants should confirm current residency, establishment and subcontracting rules against ARIA's general applicant guidance, which governs eligibility rather than programme-specific criteria. The programme was backed initially by 42,000,000 pounds over four years, now described as nearly 100,000,000 pounds, with close to 50,000,000 pounds awarded across 12 projects to date; ARIA does not publish a fixed per-project ceiling and award sizes have varied widely. Prior intake was organised across four technical areas: TA1 Bold Solutions, TA2 Bold Ideas, TA3 System-level Software Simulation, and TA4 Testing and Evaluation, delivered through two solicitations, Scaling Compute: Benchmarking and Scaling Compute: Full Proposals. There are currently no open funding calls for this programme and both prior calls are archived with documentation available as PDFs. Interested parties should register for ARIA opportunity space and programme updates and monitor the ARIA funding page for reopened solicitations. Confirm the full requirements in the official notice before applying.
The current listing shows ARIA initially directed 42,000,000 pounds over four years to this programme and has since described it as backed by nearly 100,000,000 pounds; it has awarded close to 50,000,000 pounds across 12 projects, which implies an average award in the region of 4,000,000 pounds though individual awards vary widely. At 1.35 dollars to the pound the 42,000,000 pound headline is approximately 56,700,000 US dollars and the average project award approximately 5,600,000 US dollars, which is the range amount_min and amount_max reflect. ARIA does not publish a fixed per-project ceiling, and award sizes have ranged from small concept-stage work up to the 16,000,000 pound grant to CommonAI for an AI inference lab, so the average is a weak guide to any individual award. Prospective applicants should note that there are currently no open funding calls for this programme; the two prior calls, Scaling Compute: Benchmarking and Scaling Compute: Full Proposals, are archived. Verify award ceilings, matching requirements, and allowable costs in the official notice.
ARIA Scaling Compute: AI at 1/1000th the Cost Programme for Radically Cheaper AI Training Hardware and Novel Compute Architectures is funded by Advanced Research + Invention Agency (ARIA), United Kingdom. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The NSF Computer and Information Science and Engineering: Future Computing Research (Future CoRe) program (NSF 25-543) supports foundational computing research and education with a strong emphasis on AI and machine learning. The program funds research that advances the foundations of computing including AI/ML theory, algorithms, systems, and applications. Future CoRe supports small to medium-sized research projects that can have significant impact on computing foundations. The program has target dates of February 5, 2026 and September 10, 2026 for proposal submissions (note: these are target dates, not deadlines, meaning proposals may be submitted at any time but will be reviewed in batches around these dates). Investigators may not serve as PI, co-PI, or Senior/Key Personnel on more than two proposals submitted within any consecutive 12-month period across all Future CoRe programs. This is one of NSF's primary mechanisms for funding fundamental AI and machine learning research at U.S. academic institutions, covering areas such as machine learning theory, natural language processing, computer vision, robotics foundations, and human-AI interaction.
The ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.
DE-FOA-0003600 is the DOE Office of Science's FY 2026 open, rolling solicitation for financial assistance, providing roughly $500 million across seven program areas: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics, and Isotope R&D and Production. AI and machine learning research is supported directly through Advanced Scientific Computing Research, while Biological and Environmental Research funds atmospheric process research, environmental systems process research, and earth-energy systems modeling — making this a major channel for AI-enhanced climate and earth system modeling work. DOE anticipates 200 to 350 new awards ranging from $5,000 to $5 million each, with project periods from six months to five years. The FOA opened September 30, 2025 and accepts applications on a rolling basis through the end of FY 2026.
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