Artificial Intelligence VS Machine Learning

https://youtu.be/oIXF8XZyPUM

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task.

Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.

The Extreme Physics Pushing Moore’s Law to the Next Level

ASML makes big machines that make chips smaller, faster and greener.

This video provides an overview of the semiconductor evolution and advances in miniaturization.

The video highlights ASML’s lithography machines that use extreme ultraviolet light. EUV lithography uses light with a wavelength of just 13.5 nanometers (nearly x-ray level), a reduction of almost 14 times that of the other enabling lithography solution in advanced chipmaking, DUV (deep ultraviolet) lithography, which uses 193-nanometer light.

Robotics: Crash Course AI #11

Robots aren’t like humans who can do a lot of different things. They’re designed for very specific tasks like vacuuming our homes, assembling cars in a factory, or exploring the surface of other planets. So even though it may be a while before we have a general household robot that can do it all, robots are still really important because they can do some things incredibly well even better than humans. So today, we’re going to take a look at the role of AI in overcoming three key challenges in the field of robotics: localization, planning, and manipulation.