In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, ...
Abstract: This study proposes an unsupervised deep learning-based (DL-based) approach to precoding design for integrated sensing and communication (ISAC) systems. Designing a dynamic precoder that can ...
For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...
Abstract: There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this paper we ...
Computer engineers and programmers have long relied on reverse engineering as a way to copy the functionality of a computer ...
An AI agent reads its own source code, forms a hypothesis for improvement (such as changing a learning rate or an architecture depth), modifies the code, runs the experiment, and evaluates the results ...