What Is Multimodal AI? | Multimodal Weekly 21

In the 21st session of Multimodal Weekly, James Le - the Head of Developer Experience at Twelve Labs - dissected Multimodal AI. This is a rapidly evolving field that focuses on understanding and leveraging multiple modalities to build more comprehensive and accurate AI models.
✅ He delved into the historical and modern applications of Multimodal AI.
✅ He provided a comprehensive overview of the foundational principles of Multimodal AI, including modality heterogeneity, connections, and interactions.
✅ He also discussed the core challenges researchers face when applying Multimodal AI to different applications, such as representation, reasoning, and generation.
👯‍♀️ Connect with James: jameskle.com/
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Timestamps:
00:20 Introduction
00:38 Historical Applications of Multimodal AI
02:57 Modern Applications of Multimodal AI
05:20 Foundational Principles of Multimodal AI
06:00 Principle 1 - Modality Heterogeneity
07:00 Principle 2 - Modality Connections
09:00 Principle 3 - Modality Interactions
10:20 Core Research Challenges in Multimodal AI
12:00 Multimodal Representation
12:30 Multimodal Pretraining
15:44 Limitations in Multimodal Pretraining
20:41 Cross-Modal Interactions in Multimodality
23:51 Future Directions of Multimodal Representation
26:38 Multimodal Reasoning
26:55 How to Understand Reasoning?
28:13 How Do Pretrained Models Reason?
31:14 Challenges in Multimodal Reasoning
33:35 How Are Reasoning Models Useful to Us?
36:15 Multimodal Generation
36:45 Multimodal Summarization
38:20 Multimodal Translation
39:27 Multimodal Creation
41:46 Challenges in Multimodal Generation
44:55 Ethical Issues in Multimodal Generation
46:40 Conclusion
46:55 The Future of Multimodal Foundation Models
48:08 Twelve Labs Video AI Demo
53:02 James answers audience questions