The application of deep neural networks to speech recognition in 2012, led by Geoffrey Hinton and his colleagues, marked a revolutionary breakthrough that transformed automatic speech recognition. This work demonstrated that deep neural networks could dramatically outperform Hidden Markov Model approaches, achieving error rates that were previously thought impossible and validating deep learning as a transformative approach for AI.
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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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