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On 12-01-20, NEW YORK TIMES Published DUBIOUS Update on AI, DEEPMIND,FOLDING PROTEINS and COVID-19

On December 1, 2020, the NEW YORK TIMES published a dubious update on DEEPMIND, Artificial Intelligence, Folding of proteins, and Coronavirus. 

Dubious as in Untrustworthy. 

The following is excerpted from that article: Artificial Intelligence Cracks a Mystery About Proteins| 

“Some scientists spend their lives trying to pinpoint the shape of tiny proteins in the human body. 

Proteins are the microscopic mechanisms that drive the behavior of viruses, bacteria, the human body and all living things. They begin as strings of chemical compounds, before twisting and folding into three-dimensional shapes that define what they can do — and what they cannot. 

For biologists, identifying the precise shape of a protein often requires months, years or even decades of experimentation. It requires skill, intelligence and more than a little elbow grease. Sometimes they never succeed. 

Now, an artificial intelligence lab in London has built a computer system that can do the job in a few hours — perhaps even a few minutes. 

DeepMind, a lab owned by the same parent company as Google, said on Monday that its system, called AlphaFold, had solved what is known as “the protein folding problem.” Given the string of amino acids that make up a protein, the system can rapidly and reliably predict its three-dimensional shape. 

This long-sought breakthrough could accelerate the ability to understand diseases, develop new medicines and unlock mysteries of the human body. 

Computer scientists have struggled to build such a system for more than 50 years. For the last 25, they have measured and compared their efforts through a global competition called the Critical Assessment of Structure Prediction, or C.A.S.P. Until now, no contestant had even come close to solving the problem. 

DeepMind solved the problem with a wide range of proteins, reaching an accuracy level that rivaled physical experiments. Many scientists had assumed that moment was still years, if not decades, away. 

“I always hoped I would live to see this day,” said John Moult, a professor at the University of Maryland who helped create C.A.S.P. in 1994 and continues to oversee the biennial contest. “But it wasn’t always obvious I was going to make it.” 

As part of this year’s C.A.S.P., DeepMind’s technology was reviewed by Dr. Moult and other researchers who oversee the contest. 

If DeepMind’s methods can be refined, he and other researchers said, they could speed the development of new drugs as well as efforts to apply existing medications to new viruses and diseases. 

The breakthrough arrives too late to make a significant impact on the coronavirus.But researchers believe DeepMind’s methods could accelerate the response to future pandemics. Some believe it could also help scientists gain a better understanding of genetic diseases along the lines of Alzheimer’s or cystic fibrosis. 

Still, experts cautioned that this technology would affect only a small part of the long process by which scientists identify new medicines and analyze disease. It was also unclear when or how DeepMind would share its technology with other researchers….NEW YORK TIMES.” 

On February 6, 2019, this Blogger addressed  DEEPMIND, A.I., and folding proteins. 

If A.I. Did That and It Did; It Can Do This-Create DISEASE X 


The following is excerpted from that Blog:  


“SAN FRANCISCO — You can think of it as a World Cup of biochemical research.Every two years, hundreds of scientists enter a global competition. Tackling a biological puzzle they call “the protein folding problem,” they try to predict the three-dimensional shape of proteins in the human body. No one knows how to solve the problem. Even the winners only chip away at it. But a solution could streamline the way scientists create new medicines and fight disease. 

 

…..The contest, the Critical Assessment of Structure Prediction, was not won by academics.  

 

It was won by DeepMind, the artificial intelligence lab owned by Google’s parent company.“I was surprised and deflated,” said Dr. AlQuraishi, a researcher at Harvard Medical School. “They were way out in front of everyone else.” 

 

DeepMind specializes in “deep learning,” a type of artificial intelligence that is rapidly changing drug discovery science. A growing number of companies are applying similar methods to other parts of the long, enormously complex process that produces new medicines. These A.I. techniques can speed up many aspects of drug discovery and, in some cases, perform tasks typically handled by scientists. 

 

“We have to connect so many other dots,” said Juan Alvarez, associate vice president of computational and structural chemistry at Merck. 

 

In the spring of 2016, after making headlines with A.I. systems that played complex games like the ancient board game Go, DeepMind researchers were looking for new challenges. So they held a “hackathon” at company headquarters in London. Working with two other computer scientists, the DeepMind researcher Rich Evans homed in on protein folding. They found a game that simulated this scientific task. They built a system that learned to play the game on its own, and the results were promising enough for DeepMind to greenlight a full-time research project. The protein folding problem asks a straightforward question: Can you predict the physical structure of a protein — its shape in three dimensions? 

 

If scientists can predict a protein’s shape, they can better determine how other molecules will “bind” to it — attach to it, physically — and that is one way drugs are developed. A drug binds to particular proteins in your body and changes their behavior. 

 

In the latest contest, DeepMind made these predictions using “neural networks,” complex mathematical systems that can learn tasks by analyzing vast amounts of data. By analyzing thousands of proteins, a neural network can learn to predict the shape of others.….DeepMind’s victory showed how the future of biochemical research will increasingly be driven by machines and the people who oversee those machines. 

 

…“This is a first step,” said David Baker, the director of the Institute for Protein Design at the University of Washington. “There are so many other steps still to go.”As they work to better understand the proteins in the body, for instance, scientists must also create new proteins…….NEW YORK TIMES.” 

 

If A.I. can discover the solution to  the protein folding problem, it can create DISEASE  X…..,”THE MAXEY CHRONCILES.


 On April 22, 2020, this Blogger published the following:

This Blogger’s theory of the Coronavirus case is this: that the Chinese Communists created this pathogen by folding proteins. To solve the Coronavirus will take more than trained scientists; it will take code breakers to crack the deadly algorithm. It will take  A.I.(Artificial Intelligence), the efforts of a super computer. 

 

If the Chinese Communists used a DEEP MIND variant to fold proteins into Coronavirus, America will need a super computer to discover its road map. .MAXEY CHRONICLES.” 

 This Blogger’s theory of the Coronavirus case is this: that the Chinese Communists created this pathogen by folding proteins. To solve the Coronavirus will take more than trained scientists; it will take code breakers to crack the deadly algorithm. It will take  A.I.(Artificial Intelligence), the efforts of a super computer. 

 

If the Chinese Communists used a DEEP MIND variant to fold proteins into Coronavirus, America will need a super computer to discover its road map. 

 

America had a super computer, achieved by linking up personal computers. That super computer was SETI; it was used  to search for extraterrestrial life. SETI could have been adapted for use against Coronavirus; it was dismantled. 

 

But in response to Coronavirus, Mankind, Western Civilization, America  is at it again, developing a super computer to ascertain the folding proteins of coronavirus. 

 

“The world’s fastest supercomputer has been created from volunteers loaning spare time on their home PCs to fold proteins, a scientific task that could prove instrumental in the fight against the coronavirus. 

 

According to Folding@Home, the organisation that runs the distributed computing effort, the combined power of the network broke 1,000,000,000,000,000,000 operations per second – or one “exaflop” – on 25 March. 

 

That made it six times more powerful than the current world’s fastest traditional supercomputer, the IBM Summit, which is used for scientific research at the US’s Oak Ridge National Laboratory. By Monday, it had more than doubled that, hitting a new record of 2.4 exaflops, faster than the top 500 traditional supercomputers combined, thanks to almost 1 million new members of the network. 

 

The breakthrough reflects a huge spike in support for the Folding@Home project. Backers run a simple piece of software on their home computer, which then downloads and performs small tasks to help determine the physical structure of proteins. 

 

All complex proteins are made of one or more strings of amino acids, folded in on themselves in complex – but predictable – ways to make 3D shapes. By applying those predictable rules, even a home computer can carry out folding calculations, and when millions of home computers are running the software at the same time, the total network can far outpace traditional supercomputers. 

 

In March, Folding@Home announced a new set of tasks related to Covid-19 that would put contributors to work simulating the dynamics of the proteins that make up Sars-CoV-2 (the virus that causes Covid-19) to hunt for new prospects for drugs to tackle the disease. 

 

It is already paying off. One effort has been focusing on the “spike” protein that Sars-CoV-2 uses to invade human cells, says Greg Bowman, one of the researchers coordinating the effort. “It is well established that the spike must undergo a dramatic opening motion to reveal the interface that ultimately binds a human cell. Understanding how the spike opens up … could be extremely useful. Every step along the way could potentially be targeted with therapeutics. 

 

“Unfortunately, there is no way to watch a spike undergo this transition, at least with existing experimental techniques. Data on what the open state even looks like is also limited.” But after just a few weeks of project time, the team was able…. to create a simulation that showed the first stage of the “mouth” opening up…..THE MAXEY CHRONICLES.” 

 

DEEPMIND solved the folding protein problem almost two years ago; there has been plenty of time to marshal its AI power against COVID-19. Obviously, the Global Elite did not want those powers marshaled against the virus which has decimated Western Civilization. 

 

Does it make one a bizarre paranoid to wonder why not? 



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