Protein folding, one of the biggest mysteries in biology, has been solved by artificial intelligence company DeepMind.
Category: robotics/AI – Page 1,767
A 50-year-old science problem has been solved and could allow for dramatic changes in the fight against diseases, researchers say.
For years, scientists have been struggling with the problem of “protein folding” – mapping the three-dimensional shapes of the proteins that are responsible for diseases from cancer to Covid-19.
Google’s Deepmind claims to have created an artificially intelligent program called “AlphaFold” that is able to solve those problems in a matter of days.
LONDON — Alphabet-owned DeepMind has developed a piece of artificial intelligence software that can accurately predict the structure that proteins will fold into in a matter of days, solving a 50-year-old “grand challenge” that could pave the way for better understanding of diseases and drug discovery.
Every living cell has thousands of different proteins inside that keep it alive and well. Predicting the shape that a protein will fold into is important because it determines their function and nearly all diseases, including cancer and dementia, are related to how proteins function.
“Proteins are the most beautiful, gorgeous structures and the ability to predict exactly how they fold up is really very, very challenging and has occupied many people over many years,” Professor Dame Janet Thornton from the European Bioinformatics Institute told journalists on a call.
Researchers at DeepMind say they have solved “the protein folding problem,” a task that has bedeviled scientists for more than 50 years.
Since Xi put out the call to build up the new area, China’s tech giants have piled in. Alibaba Group Holding, Tencent Holdings, Baidu, Zhongguancun Science Park and Tsinghua University have all established projects in Xiongan. The projects include the use of sensors, 5G networks and facilities for supercomputing and big data in the pursuit of building up the smart city. Alibaba is the parent company of the Post.
JD Digits, the e-commerce giant’s big data arm, is building a smart city operating system that uses artificial intelligence for urban management.
Scientists at Osaka University develop a label-free method for identifying respiratory viruses based on changes in electrical current when they pass through silicon nanopores, which may lead to new rapid COVID-19 tests.
The ongoing global pandemic has created an urgent need for rapid tests that can diagnose the presence of the SARS-CoV-2 virus, the pathogen that causes COVID-19, and distinguish it from other respiratory viruses. Now, researchers from Japan have demonstrated a new system for single-virion identification of common respiratory pathogens using a machine learning algorithm trained on changes in current across silicon nanopores. This work may lead to fast and accurate screening tests for diseases like COVID-19 and influenza.
In a study published this month in ACS Sensors scientists at Osaka University have introduced a new system using silicon nanopores sensitive enough to detect even a single virus particle when coupled with a machine learning algorithm.
A new MIT report proposes how humans should prepare for the age of automation and artificial intelligence.
Summary: A new AI system helps researchers better understand the brain computations that underlie thought.
Source: Baylor University.
A team led by researchers at Baylor College of Medicine and Rice University has developed artificial intelligence (AI) models that help them better understand the brain computations that underlie thoughts. This is new, because until now there has been no method to measure thoughts. The researchers first developed a new model that can estimate thoughts by evaluating behavior, and then tested their model on a trained artificial brain where they found neural activity associated with those estimates of thoughts. The theoretical study appears in the Proceedings of the National Academy of Sciences.
A small group of economists from Italy, the U.K., and the U.S. has published a Policy Forum piece in the journal Science suggesting that consumers need to be protected from collusive price setting by AI systems. They also outline some possible ways to solve the problem.
For most countries, price collusion is illegal. It is where two or more makers or sellers of goods get together and agree to charge higher than market prices for the goods or services they are selling. Such practices are illegal because consumers wind up paying higher prices than they would if prices were market based. In their paper the economists reveal that many large corporations have taken to using computer systems with an AI component to set their prices. Using computers to set prices is not new, of course, some companies sell hundreds of thousands of products. Using computers to help set prices saves a lot of time and money. But until now, such systems have been constrained by the laws in which the companies operate—such laws can be baked in. But now, the authors contend, things have begun to change. AI systems have found, through learned experience, that uncommunicated collusion can lead to higher profits.