Polymers, such as plastics, are essential in many aspects of life and industry, from packaging and cars to medical devices and optic fibers.

Machine learning algorithms need data, so the researchers designed a polymerization process that would quickly and efficiently generate experimental data to feed into the mathematical model.

Setting this mindless process in motion lets a mathematical approximation of the task emerge automatically, without human beings having to specify which details matter. With efficient algorithms, well ...

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

The FDA defines process validation as consisting of three parts: process design (PD), process qualification (PQ), and continued process verification (CPV). The first two stages are discrete—once ...

Further, if they made use of a tool such as H2O.ai’s Driverless AI, which automates a significant portion of the machine learning process, they could make these teams dramatically more efficient.

Like everything else associated with machine learning, deep learning, and large language models, the generative AI development process is subject to change, often with little or no notice.