Browsed by
Tag: Ackley Sejnowski and Hinton

Book Chapter: Draft Chapter 7 – The Boltzmann Machine

Book Chapter: Draft Chapter 7 – The Boltzmann Machine

Chapter 7: Energy-Based Neural Networks This is the full chapter draft from the book-in-progress, Statistical Mechanics, Neural Networks, and Artificial Intelligence. This chapter draft covers not only the Hopfield neural network (released as an excerpt last week), but also the Boltzmann machine, in both general and restricted forms. It deals with that form-equals-function connection, based on the energy equation. (However, we postpone the full-fledged learning method to a later chapter.) Get the pdf using the pdf link in the citation…

Read More Read More

A “Hidden Layer” Guiding Principle – What We Minimally Need

A “Hidden Layer” Guiding Principle – What We Minimally Need

Putting It Into Practice: If we’re going to move our neural network-type architectures into a new, more powerful realm of AI capability, we need to bust out of the “sausage-making” mentality that has governed them thus far, as we discussed last week. To do this, we need to give our hidden layer(s) something to do besides respond to input stimulus. It’s very realistic that this “something” should be free energy minimization, because that’s one of the strongest principles in the…

Read More Read More