artificial intelligence

A memo sent out last week by the Office of Management and Budget and the Office of Science and Technology Policy outlines this year’s R&D priorities. Federal science agencies will use this memo to design their budget requests for the fiscal year 2025.

Representatives from leading AI companies (Amazon, Anthropic, Google, Inflection, Meta, Microsoft and OpenAI) gathered at the White House on July 21 for the announcement of their voluntary commitment to “help move toward safe, secure, and transparent development of AI technology.” According to a White House statement, the companies have made commitments to ensuring products are safe before introducing them to the public, building systems that put security first, and earn the public’s trust.

Last month, NIH came out with a policy statement that prohibits using generative AI to analyze or critique NIH grant applications and contract proposals. Specifically, as written in NIH Notice NOT-OD-23-149, “NIH prohibits NIH scientific peer reviewers from using natural language processors, large language models, or other generative Artificial Intelligence (AI) technologies for analyzing and formulating peer review critiques for grant applications and R&D contract proposals.” The problem with using generative AI in peer review is that it compromises confidentiality. As expressed in the notice, once information is loaded onto a generative AI platform, “AI tools have no guarantee of where data are being sent, saved, viewed, or used in the future, and thus NIH is revising its Confidentiality Agreements for Peer Reviewers to clarify that reviewers are prohibited from using AI tools in analyzing and critiquing NIH grant applications and R&D contract proposals. Such actions violate NIH’s peer review confidentiality requirements.”

The National Science Foundation (NSF) is expanding a network of research centers across the country to translate university-based R&D into new, and hopefully, better advanced materials. In late June, NSF announced the distribution of $162 million to support the creation of nine more Materials Research Science & Engineering Centers (MRSECs), bringing the total number of centers to twenty. Each of the new centers will receive $18 million over six years.

If a recent forecast from McKinsey & Company is correct, climate change isn’t the only rough ride ahead over the next decade for regional and national economies.

More than 50% of the patents granted in 2020 were related to AI, according to a USPTO report. Considering this large volume of AI-related patents, the office recently sought feedback regarding AI inventorship. Key points made by AUTM, BIO, Google, IBM, and Microsoft are summarized here.

A new fact sheet released today from the White House outlines three recent activities related to artificial intelligence. First, the National Science Foundation is announcing today its latest investments in National AI Research Institutes; the new $140 million across seven awardees brings the total number of institutes funded since 2020 to 25. Second, the administration is supporting an AI “red team” event at DEF CON 31 that intends to have thousands of hackers explore large language models from Google, Open AI, NVIDIA and others. Third, the Office of Management and Budget will release draft policy guidance on the use of AI systems by the federal government this summer.

States with top-ranking university AI research programs garner a greater number of Phase II AI-related SBIR awards, according to a working paper from the Department of Economics at the University of North Carolina at Greensboro. Researchers there investigated state variations in the distribution of Phase II SBIR research projects focused on artificial intelligence (AI). The authors of the paper hypothesized that the state-by-state variations are related to the presence of a research university with a “Top 10” AI program in each state. Analysis showed that three out of the five states receiving the most funding for AI-related Phase II SBIR projects had a top-ranked AI research university. Although proximity to a top research university may be beneficial to Phase II SBIR applicants with AI-focused projects, it is not the only path to success in capturing SBIR funds.

The National Science Foundation has announced the establishment of 11 new NSF National Artificial Intelligence Research Institutes, reaching a combined investment of $220 million and including a total of 40 states when adding the original seven institutes announced last year. The institutes are expected to act as connections in a broader nationwide network and will be led by NSF in partnership with the U.S. Department of Agriculture National Institute of Food and Agriculture, U.S. Department of Homeland Security, Google, Amazon, Intel and Accenture. All but one of the 11 new institutes will be led by universities. The exception is the NSF AI Institute for Adult Learning and Online Education (ALOE), which will be led by SSTI member, the Georgia Research Alliance (GRA).

Over $1 billion has been awarded for the creation of 12 new quantum information services (QIS) and artificial intelligence (AI) research institutes across the country over the course of the next five years, according to an announcement from the White House Office of Science and Technology Policy, the Department of Energy (DOE) and the National Science Foundation. With this investment, the White House hopes the newly created institutes will “spur cutting edge innovation, support regional economic growth, and advance American leadership in these critical industries of the future.”