This article covers backpropagation in detail and why it is used to train neural networks. Later, we cover how it is implemented practically in machine learning frameworks using Automatic Differentiation.
Understand the mathematical foundations and practical applications of optimizing policies directly through gradients, exploring episodic and continuous environments. The piece offers theoretical insights and proofs, illuminating complex concepts like the policy gradient theorem and function approximation.
Find the paper here. Paper Gist:The paper introduces Integrated Understanding System(IUS) as an effort to make better language understanding models. They argue that up until now, models have only focused on the language part and have ignored how humans understand and communicate about the world around us. The authors say, to understand the language better…
In this post, I talk about Peter Voss’s paper. I first read about Peter’s theory of mind approach in Chapter 1 of the Artificial General Intelligence Textbook. I talk about much of what I learn in this paper in this video. In this paper, Peter discusses about essential properties of an AGI system and the…