We engage with automation and machine learning every day in ways we may not realize. Consider the most common online habits: browsing social media, shopping on Amazon or binge-watching on Netflix.

University libraries hold vast collections of scholarly work, yet most academic books are borrowed only a handful of times ...

Algorithmic recommendation systems on social media sites like YouTube, Facebook and Twitter have shouldered much of the blame for the spread of misinformation, propaganda, hate speech, conspiracy ...

Social media company X has taken an uncommon step in an industry known for secrecy by publicly releasing the source code ...

Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...

Elon Musk isn't a fan of X's algorithm, so he's documenting the company's efforts to improve the tech that decides what you ...

Recommender systems form an integral component of modern digital platforms, providing personalised suggestions by filtering through vast amounts of data. These systems largely rely on collaborative ...

Fashion image retrieval and recommendation systems represent a rapidly evolving intersection of computer vision, machine learning and artificial intelligence, tailored to the unique demands of the ...

Like their US-based counterparts, Google and Amazon, the Chinese Internet giants Baidu and Alibaba rely on GPU acceleration to drive critical parts of their AI-based services. At Nvidia’s GPU ...

Artificial intelligence performance startup ArthurAI Inc., said today it’s adding a powerful new tool to its suite of AI monitoring services. The new Recommender System Support tool is designed to ...

A music store like Apple iTunes contains more than 5 million songs today. And there are plenty of similar music stores online. With people posting online their own creations or excerpts of the ...