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DateDate: 11-04-2019, 05:56

The academic publishing house Springer Nature presented the first research book created using machine learning. Reported by The Verge.
The book "Lithium-Ion Batteries: A Machine-Generated Summary of Current Research" contains a summary of peer-reviewed articles published on this topic, including citations, hyperlinks and automatically generated links to the content. The tutorial is available for free download.
In his opening remarks, Henning Schoenenberger of Springer Nature said that such books are capable of starting "a new era in scientific publications, automating routine work."
Schoenberger notes that in the last three years alone more than 53,000 scientific papers on lithium-ion batteries have been published. This is a huge problem for scientists who are trying to keep abreast of developments. But using AI to automatically scan and summarize these results, scientists can save time and continue important research.
"This method allows readers to speed up the process of mastering the literature in this field of research. At the same time, if necessary, readers can always identify the source and go to it for further study of the subject," said Schönenberger.
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Although the recent boom in machine learning has greatly improved the ability of computers to generate the written word, the performance of these bots is still very limited. They cannot struggle with the long-term consistency and structure that human writers create, and therefore such efforts as fiction or poetry generated by AI are more likely to be formatted.
What an AI can do is compose formula texts when loading a library. For example, in journalism, machine learning is used by organizations such as The Associated Press to create reports of football matches, earthquakes, and financial news. These are topics where creativity is an obstacle.
According to associate professor at the Institute of Human Computer Interaction Jeff Bigham, the book was not the most impressive feat of AI. “It’s enough just to take a high-quality introductory text, briefly summarize the main conclusions and make the material look connected. In fact, the very nature of the extract means that it will be consistent in parts if the input texts are coherent. would call it valuable, "commented Bigham.
Earlier, InternetUA has already reported on AI journalism: the world's largest media uses robot authors to create articles. Moreover, AI journalists are already writing fake news - computers that have already been used to create short news reports from press releases can be taught to read and write long false texts.

DateDate: 10-04-2019, 05:55

Scientists have conducted experiments to test how much artificial intelligence is smarter than man.
As an experimental, the researchers took the DeepMind neural network and decided to offer it to independently examine the school curriculum in mathematics, and also to perform tasks from the tenth grade level. Reports the edition about it "Today".
As a result, DeepMind failed the school test with disgrace, gaining 14 points out of 40. Most British students receive marks much higher.
Artificial intelligence was unable to adequately evaluate test assignments. If an ordinary schoolchild can easily recognize a huge number of numbers, letters and formulas, then this is given to a neural network with difficulty. Most of the time, DeepMind spent on character recognition, as well as translating information into a readable form for its own analysis spent a lot of energy.
Meizu got into a big scandal: what happened
Meizu got into a big scandal: what happened
But still, artificial intelligence is able to solve a complex mathematical problem. For this, it must be presented in a special form so that the neural network does not spend its resources on recognition. In the meantime, the "visual" information is processed by neural networks with difficulty, which promises such distressing results.
Earlier it was reported that artificial intelligence has learned to predict death to the nearest second.
Thus, the case histories of half a million Britons aged 40 to 69 years were chosen as the material for the study.
Artificial Intelligence
Researchers from the University of Nottingham began testing a self-learning algorithm that they had independently developed. This algorithm is able to assess the risks of premature death of a person suffering from chronic diseases. And also knows how to name almost the exact date of departure from a person’s life.
Half a million Britons aged 40 to 69 years of age were chosen for the study.
After comparing the data, it turned out that the neural network predicted human deaths more accurately than the system used by humans.

DateDate: 9-04-2019, 05:57

Machine learning was used to create very tasty basil bushes - you probably know this plant with an unusual taste, the main ingredient of pesto sauce. Although, unfortunately, we cannot convey the taste of this herb, it only remains for scientists to take the word. However, these results reflect a broader trend that includes the use of a scientific approach in data and machine learning to improve agriculture. What makes basil so tasty? In some cases - artificial intelligence.
Machine learning makes products better
Scientists who have grown optimized basil used machine learning to determine growing conditions that would maximize the concentration of volatile compounds responsible for the taste of basil. A study published in the journal PLOS One.
Basil was grown on hydroponic farms in modified transport containers in Middleton, Massachusetts. Temperature, light, humidity and other environmental factors inside the containers can be controlled automatically. Scientists tested the taste of plants by searching for certain compounds using gas chromatography and mass spectrometry. And they used the data in machine learning algorithms developed by the Massachusetts Institute of Technology and Cognizant.
Strangely, the study showed that the effect of light on plants for 24 hours a day gives the best taste. Now scientists are planning to explore how technology can improve the ability of plants to fight diseases, as well as how different flora reacts to the effects of climate change.
“We are really interested in creating networking tools that can take into account the experience of the plant, its phenotype, a set of environmental stresses and its genetics, and digitizing it all so that you can understand the interaction of the plant and the environment,” says Caleb Harper, head of the OpenAg group at Media Lab MIT. His lab worked with colleagues at the University of Texas at Austin.
The idea of using machine learning to optimize yields and plant properties is rapidly gaining momentum in agriculture. Last year, the Wageningen University in the Netherlands organized the “Autonomous Greenhouse” competition in which various teams competed to develop algorithms that increase the yield of cucumber while minimizing the necessary resources. They worked with greenhouses in which computer systems control various factors.
A similar technology is already being used in some commercial farms, says Nawin Single, who heads a group of data scientists who deal with yield at Bayer, a German multinational company that acquired Monsanto last year. “Taste is one of the areas where we intensively use machine learning,” he says. And he adds that machine learning is a powerful tool for growing in greenhouses, but less useful for open fields. In “field conditions,” scientists are still looking for ways to narrow the gap.
Harper added that in the future his group will consider the genetic structure of plants (just what Bayer introduces into their algorithms) and will try to spread the technology. Their goal is to develop open source technology at the interface of data collection, sensing and machine learning, and so on.

DateDate: 8-04-2019, 05:17

The electronics manufacturer Bosch, together with the German energy company Wien Energie, presented a refrigerator that runs on blockchain technology.
This is reported in the press release Wien Energie.
The refrigerator uses blockchain - the technology on which cryptocurrencies operate - in order to determine from which source electricity comes and to inform the user about it. The user, in turn, will be able to choose a supplier.
“This means that everyone decides for himself where the electricity comes from: from the solar photovoltaic system, from the neighboring building or from the wind power plant,” explains Wien Energie.

DateDate: 7-04-2019, 06:05

If you have an old smartphone that is gathering dust on the shelf and you want to use it with benefit, you may be interested in the new robot on the smartphone created by the Besmani company team.
Besmo is a smart robot that uses the capabilities of your smartphone, including artificial intelligence functions, which allows it to receive voice commands, as well as provide communication via Bluetooth, GPS, Wi-Fi and high-speed mobile Internet.
“Besmani develops robots that are similar to other family members, friends or pets. Computer science teacher and founder of Besmani Mehdi Besharat designed and created a smart home robot called Besmo. Besmo is a new type of robot that has several functions borrowed from smartphones ... Besmo is also part of a new type of robot that has many functions similar to those you can expect from a computer. The high-intelligence robot of the future surpasses the average robot on the market. Thanks to the integration of smartphone functions, Besmo becomes an ideal companion for everyday use. Besmo is compatible with Apple's iPhone, Windows Phone, Android and Google Pixel smartphones. ”
Check out the demo below to learn more about the robot-driven smartphone, which is currently available for pre-order on Kickstarter for as low as $ 199. After starting mass production, the suggested retail price is $ 499.
It should be recalled that crowdfunding campaigns are designed to raise funds for the launch of mass production of the product, but such campaigns do not always end with the delivery of this product to the doors of pre-customers.