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In this video, Richard Feynman discusses how renormalization can be used to eliminate divergences in a theory. He explains how this technique can be used to extract meaningful results from otherwise unsolvable problems.

**00:00:00**In this video, Richard Feynman describes how perturbation theory and Feynman diagrams are used to calculate approximate solutions to problems that otherwise couldn't be solved. In the process, divergences can arise that can be problematic. Renormalization, a mathematical technique, can be used to navigate these divergences and extract meaningful results.**00:05:00**In this video, the author discusses how to renormalize a theory in particle physics by redefining and scaling parameters, and by adding in a counterterm. This is all done in an artificial way, to make the theory look slightly different.**00:10:00**Renormalization is a technique used to eliminate divergent behavior in a theory. In this video, we see how renormalization can be used to recover a finite result for expressions which include counter terms. In the end, we are left with a set of differential equations which guarantee that physical observables are completely independent of the energy scale used in renormalization.**00:15:00**This video discusses the concept of renormalization, which is the process of reducing the size of certain parameters in a model in order to improve its accuracy. Renormalization can be done using either a minimal subtraction method (ms) or an on-shell scheme. In either case, once the renormalization is complete, the calculations should be completely independent of the chosen scheme. The reason renormalization works is that it allows for the inclusion of new interactions that cancel divergences.**00:20:00**Renormalization is a technique used in particle physics to remove infinities from equations. It allows scientists to make predictions about the universe, and even prove more general results in quantum field theories. Although it can be inconvenient to have these infinities present at first, renormalization ultimately gives scientists powerful tools to work with.

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