Food and agribusiness comprise a $5 trillion industry that accounts for 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse-gas emissions. This massive industry does not change easily, but change – transformative innovation – is precisely what's needed. We collected some examples of artificial intelligence techniques that can help farmers to save thousands of dollars. Three years ago Belarusian startup OneSoil was created. It's an online service to monitor the status of sown areas, which can increase productivity and save resources with the help of artificial intelligence.

Machine learning and data mining are research areas of computer science whose quick development is due to the advances in data analysis research, growth in the database industry and the resulting world construction market needs for methods that are capable of extracting valuable knowledge from large data stores. Here are some of the examples of machine learning being applied in the construction industry. It's important to note that machine learning techniques apply mostly on a business side, less so in the actual construction. At the same time, the construction industry is currently experiencing explosive growth in its capability to generate and collect data. Advances in data storage technology, such as faster, higher capacity, and less expensive storage devices, better database management systems, and data-warehousing technology, have allowed the transformation of an enormous amount of data into computerized database systems. These data, however, have no use until they are processed and interpreted.

We propose a method for recovering the structure of a sparse undirected graphical model when very few samples are available. The method decides about the presence or absence of bonds between pairs of variable by considering one pair at a time and using a closed form formula, analytically derived by calculating the posterior probability for every possible model explaining a two body system using Jeffreys prior. The approach does not rely on the optimisation of any cost functions and consequently is much faster than existing algorithms. Despite this time and computational advantage, numerical results show that for several sparse topologies the algorithm is comparable to the best existing algorithms, and is more accurate in the presence of hidden variables. We apply this approach to the analysis of US stock market data and to neural data, in order to show its efficiency in recovering robust statistical dependencies in real data with non stationary correlations in time and space.

Self-service hasn't transformed the analytics industry the way it did the gas industry. When data mining work benches first came on the market, I found that executives loved seeing the product demonstrations. They were drawn to the graphics and the speedy setup. That was exactly what data mining product developers had in mind. The object was to put analytics power into the hands of business people, enabling them to discover useful patterns in data and put the information into action independently, without the participation of an analytics specialist.

Along with an entire generation of comic book fans, Chao Wang grew up following the exploits of Wolverine, a.k.a Now an assistant professor of chemistry at University of Califormia, Riverside, Wang recently paid tribute to his childhood hero, in a chemical engineering sort of way. Wang and a group of collaborators have developed a transparent and stretchable material that could give future robots the ability to heal rapidly, similar to Wolverine's handy superpower. According to the research team, the space-age material could power artificial muscles that mend themselves after injury or normal wear-and-tear. Researchers say that the artificial skin represents the first time scientists have created an ionic conductor that's stretchable, transparent and able to heal itself.

Machine learning and artificial intelligence are all the rage today in venture capital circles. We've seen spectacular exits in the past few years, from Google absorbing Deepmind in 2014 for $500 million, to Twitter buying TellApart in 2015 for $533 million, and Intel swallowing Nervana in 2016 for $400 million. But these were all IT plays. Berkeley-based Lygos is engineering and designing microbes that convert low-cost sugar into high-value, specialty chemicals. Ultimately, the ability to design and optimize microbes, or program them, is becoming faster and cheaper than ever before.

This year, we kicked things off by telling you how deadly and difficult space is to explore. It can kill you with radiation, giant flying space rocks, and regular old time. And those are just a few of its weapons. But while space is a pretty dangerous place, it's also incredibly inspirational. If you take science fiction as your model--which we often do--people are at their best when faced with a seemingly insurmountable challenge.

Each of these trucks is the size of a small two-story house. None has a driver or anyone else on board. Mining company Rio Tinto has 73 of these titans hauling iron ore 24 hours a day at four mines in Australia's Mars-red northwest corner. At this one, known as West Angelas, the vehicles work alongside robotic rock drilling rigs. The company is also upgrading the locomotives that haul ore hundreds of miles to port--the upgrades will allow the trains to drive themselves, and be loaded and unloaded automatically.

Machine learning and artificial intelligence are all the rage today in venture capital circles. We've seen spectacular exits in the past few years, from Google absorbing Deepmind in 2014 for $500 million, to Twitter buying TellApart in 2015 for $533 million, and Intel swallowing Nervana in 2016 for $400 million. But these were all IT plays. Berkeley-based Lygos is engineering and designing microbes that convert low-cost sugar into high-value, specialty chemicals. Ultimately, the ability to design and optimize microbes, or program them, is becoming faster and cheaper than ever before.

Orange is a component based data mining and machine learning software suite written in the Python language. It is an Open source data visualization and analysis for novice and experts. Data mining can be done through visual programming or Python scripting. It has components for machine learning. There are add ons for bioinformatics and text mining.