Research in the field of artificial intelligence has been evolving considerably in the recent years. Nevertheless, even the smartest machine is far from the level of understanding and autonomy of the human being. Learn, understand, adapt: these are fundamental intelligence principles that Pascal Vincent, full professor at Université de Montréal, is trying to implement in the next generation of intelligent machines.
Professor Vincent is interested in the human beings’s capability to interpret raw sensory data (sounds, images) and to transform it into high-level representations of our surroundings. Through his work, Pascal Vincent focuses on exploiting complex statistical regularities in order to render reality, in the same way that a neural network would. With the expansion of big data and new artificial intelligence technologies, it is now feasible to generate complex learning algorithms that could, in the long term, grant machines the capability to capture and interpret the world that surrounds us, by adopting consequential outcomes to a given event.
Researcher at the Montréal Institute for Learning Algorithms (MILA) along with professeur Yoshua Bengio, Pascal Vincent holds a PhD in Computer Sciences from Université de Montréal since 2003. He is a full professor at the Department of Computer Sciences and Operations Research (DIRO) of Université de Montréal.
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