The course of two thousand years, have been able to pass from words to the true and real Terms, at least, should have been agreed upon among the disputants and our enquiries, in Great eagerness, since the first origin of science and philosophy, that the meaning of all It might reasonably be expected, in questions, which have been canvassed and disputed with I am just collating and reproducing the discussion that happened in twitter for everyone’s benefit. Lack of explainability, trustworthiness.

My posts often made a rendition of my discomfort by portraying through various aspects like I am not a scholarly being and often lack the articulation to convey my thoughts mainly the discomfort when it comes to the underlying learning process of deep learning models. Introductionĭeep Learning often caused me an uncomfortable feeling because of its foundational principle of Gradients(descent/ascent or the backprop algorithm).

Also, I have added quotes from Laura Ruis' explanation and implementation of the paper Learning in High Dimension Always Amounts to Extrapolation by Randall Balestriero, J´erome Pesenti, and Yann LeCun. The objective of this post is to consummate the views of Yann LeCun, Gary Marcus and François Chollet on the fundamentals of Deep Learning Systems. Have to extrapolate, regardless of the dimension of the underlying data manifold. Talking about generalization, because for high dimensional data deep learning models always We shouldn’t use interpolation/extrapolation in the way the terms are defined below when The whole discussion was started because of an interesting reply from Dr.Yann LeCun to Steven Pinker who made an appreciation note to Andre Ye's post titled - You Don’t Understand Neural Networks Until You Understand the Universal Approximation Theorem. This post is a mere reproduction(with few opinions of mine) of one of the interesting discussions of Deep Learning focusing on interpolation/extrapolation in Twitter. Deep Learning is Not As Impressive As you Think, It's Mere Interpolation

Chollet deep learning