A team led by Tak, Garomsa and Zapaishchykova published a foundation AI model in Nature Neuroscience that claims broad generalizability for human brain MRI analysis across cohorts and scanners. The model reportedly reduces the need for task‑specific retraining and promises to streamline multi-site imaging studies and automated biomarker extraction. Foundation models in imaging are large, pre-trained networks intended to transfer to many downstream tasks; here the authors argue their framework achieves that transfer for structural MRI. Peer review and broad external benchmarking will determine practical uptake in clinical research pipelines and regulatory acceptance for diagnostic use.