University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > The Languages(s) in the Machine -- Multi-Modal Grounding for Explainable AI

The Languages(s) in the Machine -- Multi-Modal Grounding for Explainable AI

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If you have a question about this talk, please contact Hector Basevi.

Host: Prof Ales Leonardis

Speaker’s homepage: https://www.robots.ox.ac.uk/~nsid/

Abstract: Perceiving and interacting with the world around us involves a myriad of challenges. As humans, we are able to seek (plan), acquire (represent), and verify (reason) beliefs about the world, utilising a variety of sources (sights, sounds, etc.) Moreover, we can share these beliefs with one another using natural language. Across such tasks, we employ a very language-like ability, making use of compositional hierarchies to build abstractions that encapsulate meaning.

In this talk, I will demonstrate some of the benefits of such a grounded language-model-based approach, using generalisable and interpretable abstractions across vision, language, and robotics to perform reasoning (and meta-reasoning) about the world. Furthermore, I will discuss some of the difficulties with such an approach—the extent of presumed knowledge, availability of supervision, learning multi-modal interpretable representations—and provide some potential solutions that leverage current advances in deep generative models, a combination of neural-networks and probabilistic models.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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