Google DeepMind unveiled AlphaGenome, a deep learning model that predicts functional effects of mutations across long stretches of noncoding DNA, and published the work in Nature. AlphaGenome ingests sequences up to one million base pairs to forecast expression and regulatory consequences, aiming to illuminate the genome’s 'dark matter' and prioritize variants for follow‑up. DeepMind released a version for public research use. Early users and peer reviewers have already called for comparisons against other prediction models to validate performance; community scrutiny is accelerating. If robust, AlphaGenome could materially compress the time to identify causal noncoding variants, improving target discovery and variant interpretation in genetic disease research and therapeutic development.