I have long been an advocate of respecting virtuosity. Too often applications and other systems fail when they are over-automated and try to replace, rather than supplement, human intelligence. I ...

Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Known for its flexibility, ease of use, and GPU acceleration, PyTorch is widely adopted in both ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated ...

In an X-note, Awni Hannun, of Apple’s ML team, calls the software: “…an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)” The idea is that it ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...

Streamlit, a new machine learning startup from industry veterans who worked at GoogleX and Zoox, launched today with a $6 million seed investment and a flexible new open-source tool to make it easier ...