Introducing Petastorm: Uber ATG’s Data Access Library for Deep Learning

In recent years, deep learning has taken a central role in solving a wide range of problems in pattern recognition. At Uber Advanced Technologies Group (ATG), we use deep learning to solve various problems in the autonomous driving space, since many of these are pattern recognition problems. Many of our models require tens of terabytes […]

Carnegie Mellon Researchers Develop New Deepfake Method

Deepfakes, ultrarealistic fake videos manipulated using machine learning, are getting pretty convincing. And researchers continue to develop new methods to create these types of videos, for better or, more likely, for worse. The most recent method comes from researchers at Carnegie Mellon University, who have figured out a way to automatically transfer the “style” of […]

Facebook’s Field Guide to Machine Learning video series

The Facebook Field Guide to Machine Learning is a six-part video series developed by the Facebook ads machine learning team. The series shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems. Machine learning and artificial intelligence are in the headlines everywhere today, and there are many resources […]

Predicting e-sports winners with Machine Learning

Video game/E-sports streaming is a huge and ever rising market. In the world championship of League of Legends (LoL) last year, one semifinal attracted 106 million viewers, even more than the 2018 Super Bowl. Another successful example is Twitch, where thousands of players broadcast their gameplay to millions of viewers. Visor, a company that provides […]

Why humans learn faster than AI for now

In 2013, DeepMind Technologies, then a little-known company, published a groundbreaking paper showing how a neural network could learn to play 1980s video games the way humans do by looking at the screen. These networks then went on to thrash the best human players. Source: technologyreview

Google Just Indexed Millions of ‘Life Magazine’ Photos Using Artificial Intelligence

The search giant, which debuted a website for the photo project on Wednesday, said it was able to categorize over 4 million iconic Life Magazine photographs without human help. After clicking on a particular label like “skateboarding,” for example, users are shown photos of people performing skateboard tricks along with Wikipedia’s definition of the sport. […]

Open Sourcing the Hunt for Exoplanets

Recently, we discovered two exoplanets by training a neural network to analyze data from NASA’s Kepler space telescope and accurately identify the most promising planet signals. And while this was only an initial analysis of ~700 stars, we consider this a successful proof-of-concept for using machine learning to discover exoplanets, and more generally another example […]

Reptile: A Scalable Meta-Learning Algorithm

We’ve developed a simple meta-learning algorithm called Reptile which works by repeatedly sampling a task, performing stochastic gradient descent on it, and updating the initial parameters towards the final parameters learned on that task. This method performs as well as MAML, a broadly applicable meta-learning algorithm, while being simpler to implement and more computationally efficient. […]

Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It?

The idea has been around for a bit. Jaron Lanier, the tech philosopher and virtual-reality pioneer who now works for Microsoft Research, proposed it in his 2013 book, “Who Owns the Future?,” as a needed corrective to an online economy mostly financed by advertisers’ covert manipulation of users’ consumer choices. Source: nytimes