AI Features in the Nobel Prize for Physics

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If you were confused by the title, we don’t really blame you. But get ready, because the entire article might baffle you even more!

The Royal Swedish Academy of Sciences announced the Nobel Prize for Physics a few days ago and they’ve been given to Geoffrey Hinton and John Hopfield.

Wondering who they are? They are leaders in the world of AI.

In fact, we spoke about Geoffrey Hinton in our very first article at AI For You (lucky beginnings, I guess!)

However, the real question we want to answer today is how does AI relate to physics? The work of these two laureates has been deeply rooted in the development of machine learning technologies, which depend on using neural networks. ( If you’d like a refresher on what these mean, head over to this article!)

According to the Royal Academy’s website, John Hopfield invented the Hopfield network which uses physics to comprehend and recreate patterns. Further, Geoffrey Hinton used this to develop the Boltzmann machine which learns to recognise elements in a given type of data, much like the human brain. These discoveries not only form the foundation of machine learning technologies but have also played an indispensable role in researching other topics in the field of Physics. This interdependent relationship is what might have fuelled this revolutionary decision.

While some physics traditionalists might not be too happy with the award being extended for highly unconventional discoveries, it is no doubt a huge win for everyone in the world of AI and those who continue to acknowledge the rising interconnectedness of all scientific fields.

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