Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.

From immersive data art to machine-composed music, A.I. is challenging how we define creativity and who—or what—gets the credit.

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings.

Machine learning (ML) has demonstrated huge potential to accelerate design and discovery of membrane materials. In this review, we cover strengths and weaknesses of the traditional methods, followed ...

Sentiment Analysis (SA) is one of the prominent and emerging research area in the domain of natural language processing. This paper explores the field of sentiment analysis using machine learning (ML) ...

Explore how machine learning interprets art styles, offering insights into authenticity, evolution, and personal curation.

In 2019, Kyle O’Connell had a vision of leveraging technology to boost in-person relationships with students at the School of the Art Institute of Chicago. He set out to create a machine ...

Delving into the controversial role of AI in art creation, SlashGear spoke to AI Ethics Researcher Wes Rahman about the debate over AI-generated images.

Other approaches include the use of pre-trained deep learning networks to fuse both methods. In this paper, we will introduce a combination of pre-trained convolutional neural networks (CNN) to ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know.