Practitioners from diverse occupations and backgrounds are increasingly using machine learning (ML) methods. Nonetheless, studies on ML Practitioners typically draw populations from Big Tech and academia, as researchers have easier access to these communi…

We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys’ Data Release 9. Targeting the identification of new strong gravitational le…

This intelligent arm learns how to move naturally, based on what the wearer is doing, as Phil King discovers in the latest issue of The MagPi…

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Machine learning (ML) systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. As with other powerful technologies, safety for ML should be a leading research priority. In response to e…

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The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new region…

In this piece, the Friendly Overfitting Argument is laid out, as well as when it doesn’t hold. Is overfitting in Machine Learning and Artificial Intelligence really as bad as people make it out to be?

The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new region…