This work aims to explore the quality of cold-start recommendations derived from collective matrix factorization models [11] in collaborative filtering with explicit-feedback data in the form of ratings. Recommender systems based on collaborative filtering are typically constructed solely based on data about useritem interactions [6], such as movies rated by different users, which result in domain-independent and easily-implementable models, but have the disadvantage of only being able to make recommendations about users and items for which there is interactions data available (known as warm-start recommendations in the literature). In many settings however, there is oftentimes additional side information available about users and/or items, which is not used in the most common models such as low-rank matrix factorization [6] or kNN-based formulas [10], but which can be used both to improve recommendation models that take interactions data, and to make recommendations in the absence of interactions data (so-called cold-start recommendations). This work focuses on the second case: studying recommendations from matrix factorization models that are based on attributes data without interactions data.

The machine learning models were able to identify a patient's cancer type using only the microbial data from his or her blood.

Are you ready for Skynet? What about synths destroying the colonies of Mars as seen in Picard? With so much fiction bleeding apocalyptic images of artificial intelligence (AI) gone wrong, we'll take a look at some possible scenarios of what could actually happen in the rise of artificial intelligence. While many researchers and computer experts aren't worried, new technologies need risk-assessment. But, some high profile scientists like Elon Musk and the late Stephen Hawking sounded the alarm years ago, and there is some reason for concern.

Do you love creating innovative solutions for customers? We are currently seeking a passionate Software Engineer interested at building data-driven capabilities that drive transformation as a member of Thomson Reuters Labs in Zug. In this role, you will have significant and direct impact on our company in helping to create new information products which customers will use. We experiment, build and deliver. We work with big data sets to discover what new products, services, or analysis we can create for our customers.

Artificial intelligence has been around for many decades.

Gamified Scavenger Hunts with Artificial Intelligence … Based on internal testing, Let's Roam estimates that their machine learning is 99% accurate …

Fighting fake news has become a growing problem in the past few years, and one that begs for a solution involving artificial intelligence. Verifying the near-infinite amount of content being generated on news websites, video streaming services, blogs, social media, etc. is virtually impossible There has been a push to use machine learning in the moderation of online content, but those efforts have only had modest success in finding spam and removing adult content, and to a much lesser extent detecting hate speech. Fighting fake news is a much more complicated challenge. But they have limited reach. It would be unreasonable to expect current artificial intelligence technologies to fully automate the fight against fake news.

Science gets a lot of respect these days. Seven in 10 Americans think the benefits from science outweigh the harms, and nine in 10 think science and technology will create more opportunities for future generations. Scientists have made dramatic progress in understanding the universe and the mechanisms of biology, and advances in computation benefit all fields of science. On the other hand, Americans are surrounded by a rising tide of misinformation and fake science. Scientists are in almost complete agreement that people are the primary cause of global warming.

Welcome to a new series of short articles I am presenting about Artificial Intelligence specifically in the Azure AI stack. The objective is that you will learn about an Azure based AI service in no more than one minute and thus quickly get familiar with the entire stack over a short period of time. These are going short, easily digestible articles so let's get started!

Every day, a large portion of the population is at the mercy of a rising technology, yet few actually understand what it is artificial intelligence. You know, HAL 9000 and Marvin the Paranoid Android? Thanks to books and movies, each generation has formed its own fantasy of a world ruled (or at least served) by robots. We've been conditioned to expect flying cars that steer clear of traffic and robotic maids whipping up our weekday dinner. But if the age of AI is here, why don't our lives look more like the Jetson's?