Digests » 158

this week's favorite

An introduction to knowledge graphs

Knowledge Graphs (KGs) have emerged as a compelling abstraction for organizing the world’s structured knowledge, and as a way to integrate information extracted from multiple data sources. Knowledge graphs have started to play a central role in representing the information extracted using natural language processing and computer vision. Domain knowledge expressed in KGs is being input into machine learning models to produce better predictions.

Accelerating large-scale model inference and training via system optimizations and compression

Last month, the DeepSpeed Team announced ZeRO-Infinity, a step forward in training models with tens of trillions of parameters. In addition to creating optimizations for scale, our team strives to introduce features that also improve speed, cost, and usability. As the DeepSpeed optimization library evolves, we are listening to the growing DeepSpeed community to learn how users are engaging with the library and to take on new frontiers to expand the capabilities of DeepSpeed.

The ultimate beginner’s guide to data types in R

R is a system for statistical computation and graphics. It provides, among other things, a programming language, high level graphics, interfaces to other languages and debugging facilities. If you peruse through the job descriptions of various Data Scientist jobs, you’ll notice that R is becoming an increasingly demanded skill. R provides extensive statistical and graphical techniques such as times series analysis, classification, clustering and modelling to name a few.

NNCP: Lossless Data Compression with Neural Networks

NNCP is an experiment to build a practical lossless data compressor with neural networks. The latest version uses a Transformer model.

wav2vec Unsupervised: Speech recognition without supervision

Wav2vec-U is the result of years of Facebook AI’s work in speech recognition, self-supervised learning, and unsupervised machine translation. It is an important step toward building machines that can solve a wide range of tasks just by learning from their observations. We think this work will bring us closer to a world where speech technology is available for many more people.