Yann LeCun and Christopher Manning discuss Deep Learning and Innate Priors

Read a summary of the discussion here: http://www.abigailsee.com/2018/02/21/deep-learning-structure-and-innate-priors.html

A discussion between Yann LeCun and Christopher Manning on February 2 2018, at Stanford University. Discussion topic: "What innate priors should we build into the architecture of deep learning systems?" Moderated by Abigail See.

ABOUT THE EVENT:

Deep Learning has achieved huge success largely on the basis of end-to-end learning: the idea that a single neural network with many layers can learn to perform a complex task, from the raw input to the final output, with minimal human guidance on the intermediate stages. This approach has many advantages: it reduces the need for human-designed features, and allows us to design systems that are less pipelined and less task-specific. However, it may sometimes be advantageous to include certain innate priors – such as linguistic information for text-based tasks, for example – in our deep learning systems.

At this event, Professors LeCun and Manning discuss what role these innate priors should play in modern Deep Learning – an active debate in the AI community.

ABOUT THE SPEAKERS:

Yann LeCun is the Chief AI Scientist at Facebook AI Research, a Silver Professor at New York University, and one of the leading voices in AI. He pioneered the early use of convolutional neural networks, which have been central to the modern success of Deep Learning. LeCun has been a leading proponent for the ability of simple but powerful neural architectures to perform sophisticated tasks without extensive task-specific feature engineering.

Christopher Manning is the Thomas M. Siebel Professor in Machine Learning at Stanford University, and the world's leading NLP researcher. His work on applying deep learning to NLP includes influential research on Tree Recursive Neural Networks, GLoVe word vectors, and neural dependency parsing. Manning is a proponent for the importance of incorporating linguistic structure into deep learning systems.

Видео Yann LeCun and Christopher Manning discuss Deep Learning and Innate Priors канала Stanford AI Salon