Headline, March 30 2025/ ''' DREAMS A.I. DRAGON '''

''' DREAMS A.I. 

DRAGON '''

WHAT DO STUDENTS DREAM? ............. A.I. can also be used to predict. The shapes into which proteins twist themselves after they are made in a cell are vital to making them work. Scientists do not yet know how proteins fold.

BUT in 2021, Google DeepMind developed AlphaFold, a model that had taught itself to predict the structure of a protein from its amino-acid sequence alone.

Since it was released, AlphaFold has produced a database of more than 200 million predicted protein structures, which has already been used by over 1.2 million researchers.

For example, Matthew Higgins, a biochemist at the University of Oxford, used AlphaFold to figure out the shape of protein is mosquitoes that is important for the malaria parasite that the insects often carry.

He was then able to combine the predictions from AlphaFold to work out which parts of the protein would be the easiest to target with a drug.

Another team used AlphaFold to find - in just 30 days - the structure of protein that influences how a type of liver cancer proliferates, thereby opening the door to designing a new targeted treatment.

AlphaFold has also contributed to the understanding of other bits of biology. The nucleus of a cell, for example, has gates to bring in material to produce proteins.

A few years ago, scientists knew the gates existed, but knew little about their structure. Using AlphaFold, scientists predicted the structure and contributed to understanding about the internal mechanisms of the cell.

'' We don't really completely understand how [ the A.I.] came up with that structure,'' says Pushmeet Kohli, one of the AlphaFold's inventors who now heads Google's DeepMind's. ''A.I. for Science '' team.

'' But once it has made the structure, it is actually a foundation that now, the whole scientific community can build on top of.''

AI is also proving useful speeding up complex computer simulations. Weather models, for example, are based on mathematical equations that describe the state of Earth's atmosphere at any given time.

The supercomputers that forecast weather, however, are expensive, consume a lot of power and take a lot of time to carry out their calculations.

And models must be run again and again to keep up with the constant inflow of data from the weather stations around the world.

Climate scientists, and private companies, are therefore beginning to deploy machine learning to speed things up.

Pangu-Weather, an AI built by Huawei, a Chinese company, can make predictions about a weather in advance thousands of times faster and cheaper than the current standard, without any meaningful dip in accuracy.

This Master Research and Knowledge Publishing, continues. The World Students Society thanks The Economist.

With respectful dedication to the Global Founder Framers of The World Students Society - the exclusive and eternal ownership of every student in the world - and then Students, Professors and Teachers.

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