Explore Yoshua Bengio's groundbreaking 2003 Neural Probabilistic Language Model that revolutionized NLP by learning dense, continuous word embeddings. Discover how distributed representations captured semantic relationships, enabled transfer learning, and established the foundation for modern word embeddings, word2vec, GloVe, and transformer models.
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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