Google Research proposed PhotoScan, a deep learning framework that estimates body fat percentage, A/G ratio and V/S ratio from ordinary 2D phone photos to predict insulin resistance.
Berkeley AI Research and IBM Research extended the K-Search evolutionary kernel search framework to MLX, transferring existing CUDA kernel knowledge to Apple Silicon through a structured CUDA-to-MLX translation layer.
Google Research published a study in Nature introducing PHRM, which records video with a phone’s front camera in the seconds after face unlock and uses deep learning to estimate heart rate and resting heart rate in the background.
Google combined a new single-message encrypted aggregation protocol with TEEs, letting devices submit without multiple online rounds. Google receives only anonymised group insights; raw data is neither exposed nor reconstructed even within hardware protection. TEE attestation proves execution follows public code.