How do Multimodal AI models work? Simple explanation

Multimodality is the ability of an AI model to work with different types (or "modalities") of data, like text, audio, and images. Multimodality is what allows for a model like GPT-4 to write code given a diagram, and models like DALL-E 3 to generate an image given a description.

In this video, we'll learn about how multimodality works in AI, and the distinction between multimodal models and multimodal interfaces.

Links:

Intro repository: https://github.com/AssemblyAI-Example...
Introduction to Diffusion Models: https://www.assemblyai.com/blog/diffu...
How DALL-E works: https://www.assemblyai.com/blog/how-d...
Build your own text-to-image model: https://www.assemblyai.com/blog/minim...
How RLHF works: https://www.assemblyai.com/blog/how-r...

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#MachineLearning #deeplearning

0:00 Writing code with GPT-4
0:31 Generating music with MusicLM
0:48 What is multimodality?
1:15 Fundamental concepts of multimodality
2:30 Representations and meaning
4:00 A problem with multimodality
4:50 Multimodal models vs. multimodal interfaces
6:21 Outro