Key Takeaways from Multimodal AI Lecture
pliang279 · x · 2026-07-17
This retweet summarizes a lecture on **Multimodal AI** at the Oxford Machine Learning School. The lecture covered three parts: - **What is Multimodal AI**: handling heterogeneous, interconnected, interactive data beyond single text. - **Why it's hard**: core challenges in representation, alignment, reasoning, generation, transfer, and quantification. - **What's next**: focusing on multimodal foundation models, extending LLMs to multimodal generation. The speaker also mentioned their team's research on new modalities: - **Touch**: OpenTouch, tactile sensing gloves - **Smell**: SmellNet, AromaGen - And future directions towards 'self-evolving multimodal'
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