This podcast episode explores how asking good questions is essential in machine learning and how it is crucial to consider the philosophy behind it. The guest discusses the importance of studies and their implementation in ML and the need for an admissible set of functions.
The podcast discusses possible benchmarks to achieve AI intelligence, such as natural language conversation and self-supervised learning for robotics, and how resistance to change can hinder progress.
As machine learning advances, researchers are accumulating endless amounts of training data, allowing neural networks to learn to do functions; programming, as we currently know it, will become less about coding and more about gathering data.
The rise of machine learning in communal platforms, such as Google Maps, Waze, and social media, has enabled them to optimize services on behalf of users by predicting traffic, personalized products, and user preferences through data analysis.
Can you learn everything you need to know if you refine your filter in 40 minutes? This podcast explores that question and delves into the fascinating story of a chef at Beyond Sushi.
The idea of exporting ideas into a structure for people to benefit from is seen as a cosmic achievement for scientists, and there are only a few individuals who can hold dangerous conversations that need to be heard.