News

October 10, 2019

Facebook’s Captum Brings Explainability to Machine Learning

Captum is a tool for visualizing and comparing machine learning model explainability with deep learning library PyTorch.

October 10, 2019

Facebook Launches PyTorch Mobile for Edge ML

Facebook's PyTorch Mobile will support machine learning for embedded devices beginning with Android and iOS devices.

October 10, 2019

PyTorch 1.3 Comes with Speed Gains from Quantization and Google Cloud TPU Support

The latest version of Facebook's open-source deep learning library PyTorch also comes with support for named tensors.

October 8, 2019

Expanding Scene and Language Understanding with Large-scale Pre-training and a Unified Architecture

Making sense of the world around us is a skill we as human beings begin to learn from an early age.

October 1, 2019

Announcing updates to AutoML Vision Edge, AutoML Video, and Video Intelligence API

Google is constantly inspired by all the ways its customers use Google Cloud AI for image and video understanding.

October 1, 2019

Upcoming Boston Imaging and Vision Meetup Presentations Discuss Computer Vision and Microscopy

If you live in (or near) Cambridge, Massachusetts, the Boston Imaging and Vision Meetup Group would like to invite you to a series of talks taking place on the evening of Wednesday, October 16. Presentations include:
September 30, 2019

Computer Vision Developer Survey from the Embedded Vision Alliance — Tell Us What You Think!

The Embedded Vision Alliance is conducting our annual survey to understand what types of technologies are needed by product developers who are incorporating computer vision in new systems and applications.
September 27, 2019

Building ML Models for Everyone: Understanding Fairness in Machine Learning

Fairness in data, and machine learning algorithms is critical to building safe and responsible AI systems from the ground up by design.

September 24, 2019

Contributing Data to Deepfake Detection Research

Deep learning has given rise to technologies that would have been thought impossible only a handful of years ago.

September 23, 2019

Efficient Inference for Dynamical Models Using Variational Autoencoders

Dynamical systems theory provides a mathematical framework for studying how complex systems evolve over time.