As our chart based on data provided by the OECD.AI project shows, China is well on its way to surpassing traditional artificial intelligence research …

Artificial intelligence is at the forefront of our future, and these two stocks in the space are set to soar.

Vulnerability allows attackers to run arbitrary commands, including the ability to delete, modify, and exfiltrate private source code.

To help examine artificial intelligence (AI) systems and evaluate their … "Artificial intelligence informed by machine learning is increasingly …

Using Artificial Intelligence to transform the learning experience can remove … it is pretty ironic that machine learning and AI are designed to …

Experiments to understand the sensorimotor neural interactions in the human cortical speech system support the existence of a bidirectional flow of interactions between the auditory and motor regions. Their key function is to enable the brain to `learn' how to control the vocal tract for speech production. This idea is the impetus for the recently proposed "MirrorNet", a constrained autoencoder architecture. In this paper, the MirrorNet is applied to learn, in an unsupervised manner, the controls of a specific audio synthesizer (DIVA) to produce melodies only from their auditory spectrograms. The results demonstrate how the MirrorNet discovers the synthesizer parameters to generate the melodies that closely resemble the original and those of unseen melodies, and even determine the best set parameters to approximate renditions of complex piano melodies generated by a different synthesizer. This generalizability of the MirrorNet illustrates its potential to discover from sensory data the controls of arbitrary motor-plants.

Predicting the political leaning of social media users is an increasingly popular task, given its usefulness for electoral forecasts, opinion dynamics models and for studying the political dimension of polarization and disinformation. Here, we propose a novel unsupervised technique for learning fine-grained political leaning from the textual content of social media posts. Our technique leverages a deep neural network for learning latent political ideologies in a representation learning task. Then, users are projected in a low-dimensional ideology space where they are subsequently clustered. The political leaning of a user is automatically derived from the cluster to which the user is assigned. We evaluated our technique in two challenging classification tasks and we compared it to baselines and other state-of-the-art approaches. Our technique obtains the best results among all unsupervised techniques, with micro F1 = 0.426 in the 8-class task and micro F1 = 0.772 in the 3-class task. Other than being interesting on their own, our results also pave the way for the development of new and better unsupervised approaches for the detection of fine-grained political leaning.

Peloton today launched Lanebreak, a new series of workouts that mimic a racing game for its connected stationary bike. Riders get behind a virtual wheel, race down a multi-lane highway and gain points for higher levels of output and resistance. The fitness company briefly beta tested Lanebreak last July, and is now launching the new mode as a software update to all Peloton bikes in the US, UK, Canada, Germany and Australia. Instead, riders can choose from a selection of different pop-centric playlists to listen to in the background, featuring the likes of David Guetta, David Bowie, Bruno Mars and Ed Sheeran. For Peloton riders who are bored with the usual slate of instructor-led classes, Lanebreak adds a change of pace.

Ask any Peloton user what they like about their bike, and most answers would probably include some reference to a Peloton instructor rather than the bike itself. It's been written many times before, but it's worth noting again: Peloton's big draw is a combination of the instructor personalities, pick-me-up mantras, and music playlists. As the company wades through the hardware muck and a massive corporate restructure, its special sauce--and source of recurring revenue--is still its software platform. So it makes sense that Peloton's first big new feature in a long while is a software feature. What's more interesting is that it involves no instructors at all.

The military branches need to coordinate on goals and means of cultivating people who can advance the use of artificial intelligence.