A comprehensive guide to multimodal integration in 2024, the breakthrough that enabled AI systems to seamlessly process and understand text, images, audio, and video within unified model architectures. Learn how unified representations and cross-modal attention mechanisms transformed multimodal AI and enabled true multimodal fluency.
This article is part of the free-to-read History of Language AI book
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About the author: Michael Brenndoerfer
All opinions expressed here are my own and do not reflect the views of my employer.
Michael currently works as an Associate Director of Data Science at EQT Partners in Singapore, where he drives AI and data initiatives across private capital investments.
With over a decade of experience spanning private equity, management consulting, and software engineering, he specializes in building and scaling analytics capabilities from the ground up. He has published research in leading AI conferences and holds expertise in machine learning, natural language processing, and value creation through data.
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