An automated way to assemble thousands of objects

The manufacturing industry (largely) welcomed artificial intelligence with open arms. Less of the dull, dirty, and dangerous? Say no more. However, planning for mechanical assemblies still requires more than scratching out some sketches, of course—it’s a complex conundrum that means dealing with arbitrary 3D shapes and highly constrained motion required for real-world assemblies.

Modeling Heart Rate Response to Exercise with Wearable Data

This paper was accepted at the workshop “Learning from Time Series for Health” at NeurIPS 2022. Heart rate (HR) dynamics in response to workout intensity and duration measure key aspects of an individual’s fitness and cardiorespiratory health. Models of exercise physiology have been used to characterize cardiorespiratory fitness in well-controlled laboratory settings, but face additional …

Stable Diffusion with Core ML on Apple Silicon

Today, we are excited to release optimizations to Core ML for Stable Diffusion in macOS 13.1 and iOS 16.2, along with code to get started with deploying to Apple Silicon devices. Figure 1: Images generated with the prompts, “a high quality photo of an astronaut riding a (horse/dragon) in space” using Stable Diffusion and Core …