October 27
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Machine Learning has been in practical physics for about 30 years now, and it was used, for example, for discovering Higgs boson, Sergei Gleyzer, a researcher from the University of Alabama, told Armenian

Speaking about the use of Machine learning in physics, he recalled a discovery of Higgs boson in 2012, which was a really big event and led to Nobel Prizes for people who predicted it exists.

“When we found it, we used Machine learning actually to do that and it helped get to that discovery quicker. So, in a way I look at Machine Learning as at a tool, which may be similar to something like a telescope or microscope, depends which way you look at it, which allows us to see further, get to become more sensitive and be able to do more with a data,” the scientists said during the Global Innovation Forum in Yerevan.

He explained that the other side of the coin is that actually physics can help us understand why Machine Learning works the way it works.

Asked about what discoveries we should expect in the future, Sergei Gleyzer went on to say that he personally is interested whether they can discover Dark matter at Large Hadron Collider.

“The reason it’s interesting is that we know the Dark matter exists, we know it’s there, we don’t really know what it is, we have only theories and ideas and best guesses. So, it would be really interesting if it happens to be a particle that we could find it. It’s quite illusive and all the searches so far have come up empty, but I think we only now starting to get to the point, where we are going to have a lot of more data and new algorithms that may help us actually hopefully find it,” he said.

The second Global Innovation Forum (GIF) on “Transforming Intelligence” is being held in Armenia from October 16 to 18 with the participation of leading scientists and thought leaders.

The forum organized by Foundation for Armenian Science and Technology (FAST)․

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