This year, the Nobel Prizes were honored in physics and chemistry for discoveries in the field of artificial intelligence.
Nobel Prize in Physics: Automated Learning Bonus
The Nobel Prize in Physics this year is awarded to American John Hobfield and the British Canadian Jeffrey Henton for their work in artificial intelligence. What is the relationship between physics and artificial intelligence? The algorithms are highly dependent on the physical and sports principles, which were developed by these two pioneers.
In 1982, John Hubefield developed a model of the virtual nerve network inspired by real brain connections. Tangantly, this type of network shows the ability to interconnected memory, that is, it can recognize the shape, word or concept according to what it already learned. It is the basis of all the exploits of modern artificial intelligence. Jeffrey Hinton has used the principles of statistical physics to improve artificial nerve networks.
Then the researchers applied concepts of physics to develop artificial intelligence. Both are two worlds warning against the potential risks of artificial intelligence, because it develops very quickly and without guarantees.
Nobel Prize in Chemistry: Artificial Intelligence and Molecular Biology, Win
The works of the winners, American David Baker, British Dimis Hasabis, and American John M Jamper, have amazingly contributed to developing our understanding of proteins thanks to artificial intelligence.
Proteins, consisting of a series of amino acids, naturally takes a three -dimensional composition that determines their biological functions. The method of proteins has been studied about fifty years ago. Alphafold2, the computer tool developed by Hasabis and Jumper in Google DeepMind a few years ago, allowed the ability to predict the 3D structure of proteins from the amino acid sequence with unprecedented accuracy – about 90 %! Laboratory techniques used to determine the protein structure (X -ray and electronic microscopic microscopes) are complex and take a much longer time. For his part, David Baker used artificial intelligence to design amino acid sequences from the required protein structure. Thus, he opened the way for specially designed protein engineering.
These discoveries have important repercussions: scientists can now analyze and design proteins more quickly, which facilitates the development of new antibiotics and vaccines, and generally allows better understanding of the cell function.
Nobel Prize in Medicine or Physiology
Here, there is no artificial intelligence in the spotlight, but rather a small mechanism that has a tremendous effect on biology. Micrornas, which has been underestimated for a long time, which are small parts of the RNA (RNA) was considered useless in the past, has revealed its importance thanks to the work of the Nobel Prize winners in medicine, Americans Victor Ambros and Gary Rovkon. In 1993, these scientists have proven that the microbial Rana is actually plays a major role in organizing genes (and in the so -called Lagin genetics).
Micortnas, and it should not be confused with the Messenger RNA, is not encrypted, which means that it does not constitute a “recipe” for making proteins. Rather, it behaves like sticks that face cellular mechanics. It is associated with the target messing RNA, which prevents translation into proteins, which helps to regulate the amount of proteins produced in the cell.
