Technology News, Deep Tech

NSF puts $20 million toward turning lab research into real businesses

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September 15, 2026 by Ivy Delaney

The National Science Foundation is investing $20 million in a two-year pilot program designed to bridge the gap between federally funded research and viable businesses, addressing what the agency calls the need for deep-technology ventures. Led by the University of Central Florida’s National Commercialization and Translation Institute, the program will test funding, mentorship, and investor connections to help small businesses bring innovations to market.

“By helping these companies go further in bridging the so-called ‘valley of death,’ we can build on NSF’s R&D investments and help more breakthrough innovations reach the market,” said Erwin Gianchandani, NSF Assistant Director for Technology, Innovation and Partnerships. The pilot aims to establish best practices for translating research into nationally impactful technologies.

UCF’s NCTI Leads $20M Deep-Tech Commercialization Pilot

This initiative, authorized under the NSF Small Business Innovation Research/Small Business Technology Transfer (NSF SBIR/STTR) Commercialization Readiness Pilot Program, will administer commercialization funding alongside expert mentorship and connections to potential investors for participating small businesses. The pilot’s design incorporates a research study intended to rigorously assess which approaches most effectively propel deep-tech ventures toward market viability, generating evidence for best practices in technology translation. NSF’s investment extends beyond simply providing capital; it aims to maximize the impact of prior research and development spending.

This focus on using existing investments signals a strategic shift toward realizing a return on the agency’s substantial portfolio of early-stage research. The program’s structure will allow for detailed analysis of commercialization pathways, identifying critical bottlenecks and successful strategies.

UCF’s selection to lead this pilot reflects its established strength in fostering innovation and translating research into economic opportunity. “We are grateful to NSF for its continued confidence in UCF and for the opportunity to help shape the future of research translation and commercialization,” said University of Central Florida President Alexander N. “Discovery reaches its greatest potential when it moves beyond the laboratory and improves lives, strengthens industries and creates opportunities.” Central Florida’s concentration of industry and talent positions the university to potentially establish a national model for accelerating deep-tech commercialization, building on a track record of helping technologies become viable products and companies. NSF data demonstrates the potential for increased return; $1.6 billion in NSF SBIR/STTR investments over five years supported startups in attracting over $36 billion in subsequent funding.

NSF invests in small businesses that bring the most innovative, cutting-edge technologies to the market.

Erwin Gianchandani, NSF Assistant Director for Technology, Innovation and Partnerships
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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