Our Responses to the NSF Tech Labs RFI
Metascience, AI, biotech, and more
We recently wrote about why we’re excited about the NSF Tech Labs initiative and how it could become a landmark moment for Focused Research Organizations. Today we’re sharing our full response to the NSF’s Request for Information.
We submitted a Program Design response, drawing from our experience launching ten FROs to offer concrete recommendations on team selection, governance structure, milestone design, IP management, and transition planning. We also suggested ways in which we could serve as an implementation partner — providing the operational infrastructure, governance oversight, and nonprofit scaffolding we’ve built over four years to help Tech Labs teams deploy funds and start building from day one rather than spending their first year on administrative setup.
Separately, we submitted responses on translational bottlenecks in focus areas the NSF might select. Based on our work exploring high-leverage opportunities for science and technology, we recommend the following areas as especially impactful for US competitiveness. Within each area, we also highlight 10+ teams with promising Tech Labs concepts.
Artificial intelligence: As AI capabilities accelerate, we have a narrow window to build the defense-dominant technologies that will help determine whether the transition goes well. Provably secure cyber-physical systems will be essential if AI supercharges offensive capabilities — yet AI can also accelerate provable security. Meanwhile, the infrastructure we build may determine the extent to which AI can accelerate beneficial science, and the brain still holds important secrets that may inspire the next generations of more energy efficient and prosocial AI. We highlight teams working on formal verification for trustworthy human-AI agreements, brain-inspired architectures grounded in large-scale neural recordings and connectivity maps, and federated infrastructure for scientific synthesis that moves knowledge out of PDFs and into structured, queryable networks of claims and evidence. Read our full response*.
Biotechnology: Even superhuman AI reasoning cannot substitute for measuring contingent physical facts about biology — mapping “biological dark matter”, developing more powerful and cost effective observational tools, and generating high-quality empirical datasets become more valuable as AI advances and meaningful, predictive data becomes the bottleneck. We highlight teams working on turning connectomics and neural recording data into predictive brain models across species, unlocking Earth’s vast unculturable microbial diversity for the bioeconomy, building fully defined and reproducible organoid platforms, scaling tissue biomanufacturing from artisanal lab practice to automated production, and generating large-scale immunogenicity datasets to predict how engineered therapeutics will behave in the human body. Read our full response*.
Quantum, materials, and semiconductors: Quantum computing is increasingly constrained less by fundamental physics than by engineering challenges in hardware and software infrastructure. Materials discovery is bottlenecked by the gap between computational prediction and experimental validation, including physical materials synthesis and testing. And semiconductor based innovation in new domains is gated by the prohibitive cost and timeline of custom chip development. Meanwhile, fundamental experiments and technology development to underpin atomically precise manufacturing remain underexplored. We highlight teams working on an open-source quantum operating system and unified quantum-classical compute fabric, an AI-native materials data foundry that captures the “dark data” of failed experiments, molecular-scale nanomanufacturing using engineered proteins and DNA origami, and open-source ASIC design tools that let scientists and small startups build custom chips without a need for massive investments. Read our full response*.
(*Please note that some of the “potential tech lab” descriptions have been modified or redacted slightly, at the request of the proposing teams.)
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