Prior work has shown that coupling sequential latent variable models with semantic ontological knowledge can improve the representational capabilities of event modeling approaches. In this work, we present a novel, doubly hierarchical, semi-supervised event modeling framework that provides structural hierarchy while also accounting for ontological hierarchy. Our approach consists of multiple layers of structured latent variables, where each successive layer compresses and abstracts the previous layers. We guide this compression through the injection of structured ontological knowledge that is defined at the type level of events: importantly, our model allows for partial injection of semantic knowledge and it does not depend on observing instances at any particular level of the semantic ontology. Across two different datasets and four different evaluation metrics, we demonstrate that our approach is able to out-perform the previous state-of-the-art approaches by up to 8.5%, demonstrating the benefits of structured and semantic hierarchical knowledge for event modeling.

He's a certified drug and alcohol counselor who opened a sober living house at the peak of last winter's deadly COVID-19 surge and is on-site at least six days a week. She works for a production company, colonized their kitchen table for her two outsize computer monitors and has stayed largely locked up in their 600-square-foot Mar Vista apartment, where they now dine on TV trays. "When L.A. was, like, the worst place on Earth for COVID, I was going out and looking at three houses a day," scouting locations for Hyperion Sober Living, said co-owner Jack Shain. Shain's job means he's out in the world nearly every day, where it's impossible to tell the vaccinated from the sick. Cara Ferraro's allows her to stay home with the cats, her anxiety and the ever-present pile of dishes in the sink.

A new partnership between computing giant IBM and The Fashion Institute of Technology (FIT) in New York is aiming to embed AI into the full spectrum of the fashion industry. The partnership will see a suite of artificial intelligence (AI) tools covering deep learning, natural language processing and computer vision applied to the fashion industry, across design and development, merchandising, supply chain and retail. It will see the FIT/Infor Design and Technology Lab (DTech Lab) build on a previous partnership with the technology heavyweight, which saw the DTech Lab work with IBM and leading fashion brand Tommy Hilfiger. The project, Reimagine Retail, focused on using AI to increase the brand's competitive position through optimisations in product design, supply chain and market insights. "Reimagine Retail was a powerful example of what happens when fashion partners with a global tech leader to advance challenging innovations," said Michael Ferraro, director of the FIT/Infor DTech Lab.

They tell a story, which gives the photos context and additional emotional meaning. A paper published by Microsoft Research describes an image captioning system that mimics humans' unique style of visual storytelling. Companies like Microsoft, Google, and Facebook have spent years teaching computers to label the contents of images, but this new research takes it a step further by teaching a neural-network-based system to infer a story from several images. Someday it could be used to automatically generate descriptions for sets of images, or to bring humanlike language to other applications for artificial intelligence. "Rather than giving bland or vanilla descriptions of what's happening in the images, we put those into a larger narrative context," says Frank Ferraro, a Johns Hopkins University PhD student who coauthored the paper.