Multimodal large language models are beginning to transform science education by combining text, visuals, audio, and other data to enrich teaching and learning. From analyzing classroom interactions ...

Multimodal AI tools like Google’s NotebookLM are transforming how people research, organize, and present ideas by combining text, visuals, audio, and video in one workflow. They help users absorb ...

When students in the Ephrata, Pa., district complete a project, their goal is not just to explain what content they know, but ...

Weiyao Wang spent eight years at Meta — his first job out of college — helping build multimodal perception systems and ...

The researchers argue that traditional centralized learning platforms are no longer equipped to handle the scale, speed, and ...

This study investigated how Chinese learners of English perceive the effectiveness of different multimodal input for vocabulary learning. Forty participants perceived 14 combinations of visual, ...

Abstract: This study explores the application and effectiveness of Eye Movement Modeling Examples (EMME) in learning Standard Operating Procedures (SOP) in the manufacturing industry, where improving ...

In this post, we share the motivations, design choices, experiments, and learnings that informed its development, as well as an evaluation of the model’s performance and guidance on how to use it. Our ...

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors provide convincing evidence that ...

A common ineffective way teachers check for understanding in the classroom is by asking a variation of the question, “Does everybody get this?” If not that, then what? Today’s post will offer a number ...

In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, ...