According to @ylecun, citing @jayvanbavel and Nature, the US administration has proposed massive budget cuts across federal science agencies that would eliminate the National Science Foundation’s Social, Behavioral and Economic Sciences directorate and reduce funding for NASA and the National Institutes of Health, posing an “extinction-level event for science” with direct consequences for AI research pipelines and talent development. As reported by Nature, the proposed plan would slash multi-agency basic research funding that underpins machine learning, data resources, and compute-intensive projects, risking delays to foundational AI research and applied programs in healthcare and space data analytics. According to Nature, losing SBE support would also shrink AI-adjacent behavioral datasets, human-computer interaction studies, and algorithmic fairness research, weakening commercialization pathways for responsible AI and narrowing opportunities for startups relying on federal grants and open datasets.

According to Yann LeCun on X, citing Johns Hopkins provost Denis Wirtz, federal funding for US biomedical research has sharply contracted, with NIH allegedly down 80% in new grants and 70% in total awarded dollars since October 1, 2025, prompting lab closures and talent exits (source: X posts by @ylecun and @deniswirtz). As reported by these X posts, this funding shock jeopardizes AI-driven drug discovery, clinical ML pipelines, and translational bioinformatics that rely on NIH-backed datasets, compute, and multi-institution consortia. According to the same X sources, immediate business risks include stalled longitudinal datasets, shrinking grant-matched cloud credits, and reduced clinical trial AI validation. However, there are near-term opportunities: industry consortia can underwrite shared biobanks and real-world evidence pipelines; payers and providers can sponsor outcome-linked AI validation; foundation grants can bridge method development for multimodal models; and enterprises can accelerate private-public data partnerships to secure compliant training corpora. According to the X posts, if the trend persists, vendors building foundation models for omics, pathology, and radiology will need to pivot toward commercial co-development and revenue-backed pilots with health systems.