Current Affair 1:

News:

On October 8, John Hopfield and Geoffrey Hinton won the 2024 Nobel Prize for physics “for foundational discoveries and inventions that enable machine learning with artificial neural networks”.

We won’t go deep inside topic. Read first this:

Artificial Neural Network (ANN)

An artificial neural network processes information using the entire network structure. The inspiration initially came from the desire to understand how the brain works.

What John Hopfield did?

Suppose you used a particular perfume regularly in a certain stage of your life. Years later, you smell that perfume somewhere, and memories of that time come flooding back. This process is called associative memory, and this is what was central in Hopfield’s work, who built an artificial network of nodes to store information, mimicking the human brain. Each node could store an individual value, of either 0 or 1.

As the Nobel website says, “The Hopfield network can store patterns and has a method for recreating them. When the network is given an incomplete or slightly distorted pattern, the method can find the stored pattern that is most similar.”

What Geoffrey Hinton did

Hinton started with the Hopfield network and “expanded it to build something new, using ideas from statistical physics,” the Nobel website says. Along with other researchers, he built the Boltzmann machine.

The Boltzmann machine can learn – not from instructions, but from being given examples…. A trained Boltzmann machine can recognize familiar traits in information it has not previously seen. Imagine meeting a friend’s sibling, and you can immediately see they must be related. Similarly, the Boltzmann machine can recognize an entirely new example if it belongs to a category found in the training material, and differentiate it from dissimilar material.

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