In a new paper Composable Function-preserving Expansions for Transformer Architectures, a research team from Google DeepMind and University of Toulouse introduces parameter expansion transformations for transformer-based neural networks while preserving functionality, enabling the expansion of the capability of the model as needed.
A Microsoft Research India team presents Varuna, a system for training massive deep learning models on commodity networking that eliminates the need for specialized hyperclusters and alleviates the cost, scale, and resource utilization challenges of deep learning model training.
OneClick.ai, a startup founded by two former Microsoft engineers in Seattle, is on a mission to make AI more accessible to businesses. “We design, build and deploy custom AI models as a scalable API that can be accessed from anywhere. Just prepare your data, and we’ll take care of the rest,” says co-founder and CTO Ning Jiang.