Payman Benham, Sixu Li, Irene Wang, and William Won were chosen from over 150 applicants based on their machine learning (ML) ...

Despite the AI hype, ML tools really are proving valuable for leading-edge chip manufacturing. More aggressive feature ...

Reinforcement learning is widely applied in both FPGA and ASIC physical design flow, a topic of discussion in this paper. We also discuss various ML models like classical regression and classification ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

More information: Peizhen Bai et al, Mask-prior-guided denoising diffusion improves inverse protein folding, Nature Machine Intelligence (2025). DOI: 10.1038/s42256-025-01042-6 ...

Artificial intelligence (AI) refers to machine-based systems that analyze input data to generate predictions, recommendations, or decisions, 1 AI-based and machine learning (ML)-based technologies ...

Conclusions: PulmoSeek Plus V2.0, as a novel machine learning-based multidimensional model, improves the accuracy of pulmonary nodules classification, and potentially reduces the unnecessary invasive ...

BigHat’s antibody design platform, Milliner™, integrates a synthetic biology-based high-speed wet lab with state-of-the-art machine learning technologies into a full-stack antibody discovery ...