Discovering and characterizing new materials is important for unlocking advances in fields like clean energy, advanced ...

Researchers from Google DeepMind in Berlin, BIFOLD, and the Technical University of Berlin have introduced a new machine ...

The promise of AI revolutionizing the modern workplace is a rather seductive one. You feed it your data, find patterns that might have been missed, and optimize your decisions based on said findings.

Laser-based processes for metals are considered to be particularly versatile in industry. Lasers can be used, for example, to precision-weld components together or produce more complex parts using 3D ...

Recent advances in froth flotation optimisation have increasingly leaned on machine learning methodologies to improve process control and enhance mineral recovery. By integrating data‐driven ...

Validating drug production processes need not be a headache, according to AI researchers who say machine learning (ML) could be a single answer to biopharma’s multivariate problem. The FDA defines ...

Transfer learning can help biopharmaceutical developers to leverage historical data to guide the development of new manufacturing processes.

Back in the ancient days of machine learning, before you could use large language models (LLMs) as foundations for tuned models, you essentially had to train every possible machine learning model on ...

Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable ...