Kamilov et al. use machine-learning algorithms — computer programs that can learn from and make predictions based on input data — to give a boost to 3D phase imaging. By doing so, the authors ...

Generative AI and machine learning are closely related technologies, as the chart below illustrates. While generative AI excels at creating content, machine learning is geared for data analysis ...

Therefore, 3D printing is a powerful tool to create physical models which might provide a well-characterized training dataset as a purpose-built surrogate to clinical data for machine learning.

The framework models the complex mechanical behavior of spinodal microstructures by combining submicron 3D printing ... Most approaches to machine learning-based inverse design require large amounts ...

A 3D wiring diagram, the largest of its kind ... The research team at Princeton then used novel machine learning approaches to segment the images, defining each cell and its internal components ...

can be 3D printed. A team of researchers has found that the printer head toolpaths are easy to reproduce -- and therefore steal -- with machine learning (ML) tools applied to the microstructures ...

These building blocks, which in this case are composed of carbon, are arranged in complex 3D ... data; it learned from what changes to the shapes worked and what didn’t, enabling it to predict ...