Unum and Nebius announced a GPU‑optimized release of StringZilla, accelerating sequence alignment and fingerprinting tasks critical to large‑scale omics and drug discovery workflows. The port targets pairwise alignment scoring and retrieval phases, yielding faster performance for high‑throughput genomics pipelines. Parallel advances adapt transformer architectures to genome language models, merging NLP techniques with genomic sequences to improve representation learning for biological data. Together, hardware‑level acceleration and model innovations are shortening analytic cycles and enabling more ambitious AI‑driven biology projects.