jay.kim@experientialdesigngroup.com

Creators claim their videos were used without their knowledge.

Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled data. They can be applied to a variety of tasks, like generating images or answering customer questions. But these models, which serve as the backbone for powerful artificial intelligence tools like ChatGPT and DALL-E, can offer up incorrect

This post is co-written with MagellanTV and Mission Cloud.  Video dubbing, or content localization, is the process of replacing the original spoken language in a video with another language while synchronizing audio and video. Video dubbing has emerged as a key tool in breaking down linguistic barriers, enhancing viewer engagement, and expanding market reach. However,

This post is co-written with Vlad Lebedev and DJ Charles from Mixbook. Mixbook is an award-winning design platform that gives users unrivaled creative freedom to design and share one-of-a-kind stories, transforming the lives of more than six million people. Today, Mixbook is the #1 rated photo book service in the US with 26 thousand five-star

Computer scientist Lance Fortnow writes that by embracing the computations that surround us, we can begin to understand and tame our seemingly random world.

The MIT Stephen A. Schwarzman College of Computing recently marked a significant milestone as it celebrated the completion and inauguration of its new building on Vassar Street with a dedication ceremony. Attended by members of the MIT community, distinguished guests, and supporters, the ceremony provided an opportunity to reflect on the transformative gift that initiated the

Robotics researchers are exploring how large language models can give physical machines more smarts.

When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers recently peered into the proverbial magnifying glass to examine how LLMs fare