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HyperAI Super Neural
HyperAI Super Neural
Apr 20, 2026 · Artificial Intelligence

dnaHNet Boosts Inference Speed 3× and Cuts Genomic Learning Cost by Nearly 4×

The dnaHNet model, introduced by researchers from the University of Toronto, Vector AI Institute, and Arc Institute, achieves over three‑fold faster inference and nearly four‑fold lower computational cost than prior genomic foundation models, while delivering state‑of‑the‑art zero‑shot performance on variant effect prediction, gene essentiality classification, and unsupervised reconstruction of functional genome architecture.

Computational EfficiencydnaHNetdynamic tokenization
0 likes · 11 min read
dnaHNet Boosts Inference Speed 3× and Cuts Genomic Learning Cost by Nearly 4×
HyperAI Super Neural
HyperAI Super Neural
Jan 29, 2026 · Artificial Intelligence

AlphaGenome on Nature Cover: Predicts Variant Effects Across All Modalities in <1 s

DeepMind’s AlphaGenome, showcased on Nature’s cover, processes 1 Mb DNA sequences at single‑base resolution to predict thousands of regulatory attributes across cell types, using a U‑Net‑style architecture and two‑stage pre‑training plus distillation, achieving state‑of‑the‑art performance on 24 benchmarks and delivering variant‑effect scores in under one second on an H100 GPU.

AlphaGenomeDeepMindU-Net
0 likes · 11 min read
AlphaGenome on Nature Cover: Predicts Variant Effects Across All Modalities in <1 s