Artificial intelligence shows that we may not even know half of the structures in our body cells

Many of the diseases that affect us are related to cell malfunction. It might be possible to treat them more effectively, but first scientists need to understand exactly how cells are built and function. By combining artificial intelligence Using microscopic and biochemical techniques, scientists at the University of California, San Diego Medical School (UCSD) have made an important step in understanding the cells of the human body.

With Microscopes we can see cell structures as small as a single micrometer. In contrast, biochemical techniques that use individual proteins make it possible to study structures the size of nanometers, i.e. 1 / 1000th of a micrometer. However, a major problem in the life sciences is completing the knowledge of what is inside the cell between the micro and nanoscale. It has been found to help with this artificial intelligence is possible.

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Power Fx - Programming for Non-Programmers

Microsoft has the publication of Power Fx announced a new low-code programming language based on popular Excel formulas. The company puts the language under one Open source license available and hopes to help develop his Power platforms such as Power Automate or Power Virtual Agents and eventually become a standard for this type of application.

Artificial intelligence improves viruses for gene therapy

Dependoviruses or parvoviruses "associated" with adenoviruses (AAVs) are very useful tools in the US Gene therapy. This is because they can transfer DNA into the cell and are harmless to humans. Therefore, they are used as carriers of the genetic information needed to fight diseases.

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Vulnerabilities in Apple devices. Criminals are already taking advantage of them

Apple has patches for three Zero-day vulnerabilities Released in the iPhone, iPad and Apple TV operating systems. Cyber criminals actively exploited vulnerabilities in iOS, iPadOS and tvOS. They have been patched with version 14.4 of all the systems mentioned.

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Facebook AI accelerates MRI exams

Image reconstruction by artificial intelligence (AI) shortens the time of Magnetic resonance imaging examinations (MRI) significant.

https://healthcare-in-europe.com/

The first clinical study to compare AI-accelerated knee MRI scans with conventional scans shows that the AI scans are not only diagnostically interchangeable with the conventional ones, but also provide higher quality images. The results of this interchangeability study are a key milestone in a joint initiative launched in 2018 by NYU Langone Health of New York City and the Facebook Artificial Intelligence Research (FAIR) group to accelerate the MRI scanning process.
The research was published in the American Journal of Roentgenology.

Successful storage of digital information in the DNA of a living organism

Hard drives and other data storage systems store huge amounts of information today. However, like magnetic tapes or floppy disks in the past, these devices can become out of date over time and we will lose access to the data we collect on them. That is why scientists have developed a method to convert data into the DNA to record a living organism. This kind of "mass storage"will probably not become obsolete in the foreseeable future.

Seth Shipman of the University of California at San Francisco, who was not involved in the work, praised the performance of his colleagues from Columbia University, but points out that it will be a long time before such systems find practical application.

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Further details can be found in Nature. (https://www.nature.com/articles/s41589-020-00711-4)

AI helps solve one of physics' biggest unsolved problems

Researchers at ETH Zurich have succeeded for the first time in automating the modeling of turbulence in liquids by combining fluid mechanics and artificial intelligence. Their approach is based on the combination of Reinforcement machine learning algorithms with turbulent Flow simulationscarried out on the Piz Daint supercomputer of the Swiss National Supercomputing Center.

According to a description of the research recently published in the journal Nature Machine Intelligence published, the researchers developed new reinforcement machine learning (RL) algorithms and combined them with a physical approach to modeling Turbulence.

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They attacked a robotic vacuum cleaner and overheard what was going on in the room where it was working

Scientists from the United States and Singapore used a robotic vacuum cleaner to eavesdrop on the sound in the rooms and identify TV programs playing in the room where the vacuum cleaner was located. The performance is even more impressive as the Standalone vacuum cleaner are not equipped with a microphone. This work shows that any device with lidar technology can likely be used for eavesdropping.

We use these types of devices at home without thinking about it much. We have shown that although such devices do not have a microphone, we can rewrite their navigation system to eavesdrop on conversations and reveal confidential information, says Professor Nirupam Roy of the University of Maryland.

This in autonomous robots used Lidar system examines the environment with the help of lasers. Their light is reflected from the surroundings of the vacuum cleaner and fed into the sensors of the vacuum cleaner to create a room map. Experts have been speculating for some time that the maps created by autonomous vacuum cleaners, which are often stored in the cloud, can be used for advertising.

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How to outsmart artificial intelligence - human versus machine.

AI computer systems are finding their way into many areas of our lives and offer great potential, from self-driving vehicles to assisting doctors with diagnoses to autonomous search and rescue robots.

However, one of the major unsolved problems, especially with the branch of AI known as "neural networks", is that scientists often cannot explain why things go wrong. This is due to a lack of understanding of the decision-making process within AI systems. This problem is known as the "black box" problem.

Who is smarter?

A new 15-month research project from the University of Lancaster, in which the University of Liverpool is also involved, aims to unlock the secrets of the black box problem and find a new way to "Deep Learning"of AI computer models that make decisions transparent and explainable.

The project "Towards responsible and explainable autonomous robotic learning systems"will develop a series of security verification and test procedures for the development of artificial intelligence algorithms. These will help ensure that the decisions made by the systems are robust and explainable.

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