To demonstrate the viability of our method, we predicted reaction outcomes with substrate combinations and catalysts different from the training data and simulated a situation in which highly selective reactions had not been achieved. In the first demonstration, a model was constructed by using support vector machines and validated with three different external test sets. The first test set evaluated the ability of the model to predict the selectivity of only reactions forming new products with catalysts from the training set. The model performed well, with a mean absolute deviation (MAD) of 0.161 kcal/mol. Next, the same model was used to predict the selectivity of an external test set of catalysts with substrate combinations from the training set.

In an attempt to skill Indian youths in Artificial Intelligence, Microsoft India has taken an initiative to train five lakh youths. The company aims to train five lakh youths in AI across the country and would set up AI labs in 10 universities. Additionally, the company plans to upskill 10,000 developers in emerging technology areas like AI, IoT, etc. Microsoft also started Intelligent Cloud Hub Program to equip research and higher education institutions with AI infrastructure, build curriculum and help both faculty and students to build their skills and expertise in cloud computing, data sciences, AI and IoT. Anant Maheshwari, President, Microsoft India shares, "We believe AI will enable Indian businesses and more for India's progress, especially in education, skilling, healthcare, and agriculture. Microsoft also believes that it is imperative to build higher awareness and capabilities on security, privacy, trust, and accountability. The power of AI is just beginning to be realized and can be a game-changer for India."

ABB's future of mining infographic shows how to drive profits World's largest flotation cells improve copper and molybdenum recovery in Mexico PRESS RELEASE: The solution will be released in early 2019 as part of MICROMINE's fleet management and mine control solution, Pitram. Using the processes of computer vision and deep machine learning, on-board cameras are placed on loaders to track variables such as loading time, hauling time, dumping time and travelling empty time. The video feed is processed on the Pitram vehicle computer edge device, the extracted information is then transferred to Pitram servers for processing and analyses. ABB's future of mining infographic shows how to drive profits World's largest flotation cells improve copper and molybdenum recovery in Mexico MICROMINE Chief Technology Officer Ivan Zelina explained the solution intelligently considered the information gathered to pinpoint areas of potential improvement that could bolster machinery efficiency and safety. "Pitram's new offering takes loading and haulage automation in underground mines to a new level," Mr Zelina said.

BENGALURU: Microsoft India on Wednesday announced to set up Artificial Intelligence (AI) labs in 10 universities and train five lakh youth across the country in disrupting technologies. The company also said it will upskill over 10,000 developers over the next three years. "We believe AI will enable Indian businesses and more for India's progress, especially in education, skilling, healthcare and agriculture," said Anant Maheshwari, President, Microsoft India. Microsoft AI today is fuelling digital transformation for over 700 customers and 60 per cent customers are large manufacturing and financial services enterprises. Over 700 partners have geared up to support the AI ecosystem, said the company.

I'll use a very interesting dataset presented in the book Machine Learning with R from Packt Publishing, written by Brett Lantz. My intention is to expand the analysis on this dataset by executing a full supervised machine learning workflow which I've been laying out for some time now in order to help me attack any similar problem with a systematic, methodical approach. If you are thinking this is nothing new, then you're absolutely right! I'm not coming up with anything new here, just making sure I have all the tools necessary to follow a full process without leaving behind any big detail. Hopefully some of you will find it useful too and be sure you are going to find some judgment errors from my part and/or things you would do differently. Feel free to leave me a comment and help me improve! Let's jump ahead and begin to understand what information we are going to work with: "In the field of engineering, it is crucial to have accurate estimates of the performance of building materials. These estimates are required in order to develop safety guidelines governing the materials used in the construction of building, bridges, and roadways. Estimating the strength of concrete is a challenge of particular interest. Although it is used in nearly every construction project, concrete performance varies greatly due to a wide variety of ingredients that interact in complex ways. As a result, it is difficult to accurately predict the strength of the final product. A model that could reliably predict concrete strength given a listing of the composition of the input materials could result in safer construction practices. For this analysis, we will utilize data on the compressive strength of concrete donated to the UCI Machine Learning Data Repository (http://archive.ics.uci.edu/ml) by I-Cheng Yeh. According to the website, the concrete dataset contains 1,030 examples of concrete with eight features describing the components used in the mixture. These features are thought to be related to the final compressive strength and they include the amount(in kilograms per cubic meter) of cement, slag, ash, water, superplasticizer, coarse aggregate, and fine aggregate used in the product in addition to the aging time (measured in days)."

This article was originally published by Ozy. In 2016, Houston's petrochemical industry had countless job positions that were unfilled. And at the same time, a number of the city's residents were looking for work. So, how was Houston going to fix this? In an effort to help match eligible candidates with open positions, private companies began to step in.

God might just as well have begun with a toaster oven. A few years ago at a yard sale, Nicholas Hud spotted a good candidate: A vintage General Electric model, chrome-plated with wood-grain panels, nestled in an old yellowed box, practically unused. The perfect appliance for cooking up the chemical precursors of life, he thought. He bought it for $5. At home in his basement, with the help of his college-age son, he cut a rectangular hole in the oven's backside, through which an automated sliding table (recycled from an old document scanner) could move a tray of experiments in and out. He then attached a syringe pump to some inkjet printer parts, and rigged the system to periodically drip water onto the tray.

The world's largest robot has been unveiled and it is a completely autonomous railway system. AutoHaul has been developed by a mining firm and is being used to transport iron ore from mines to shipping ports 500 miles away (800 km) in Western Australia. This journey can be completed in just 40 hours, including the loading and dumping of the ferrous cargo. Its deployment is the end result of a project which has so far cost $940 million (£740 million). Rio Tinto, the corporation that built the infrastructure and hardware for the locomotive, says this could be the first step in transforming the firm's 1,000-mile (1,700-kilometre) network connecting 16 iron ore mines and two ports.

Effects of the peptide were occluded in Syt3 knockout mice, implicating Syt3 in a GluA2-3Y–dependent mechanism of AMPA receptor internalization. Our data give rise to a model in which Syt3 at postsynaptic endocytic zones is bound to AP-2 and BRAG2 in the absence of calcium. GluA2 could then accumulate at endocytic zones by binding Syt3 in response to increased calcium during neuronal activity. This would potentially bring GluA2 into close proximity to BRAG2, where a transient interaction could activate BRAG2 and Arf6, and promote endocytosis of receptors via clathrin and AP-2 (10, 32). PICK1 is also important for AMPA receptor endocytosis, raising the question of the interplay of Syt3 and PICK1.

Artificial Intelligence (AI) has the power to transform how we live and work, providing businesses with powerful new tools to make their operations more efficient. However, academics and technologists have multiple concerns about the ethics of AI. Q - How are organisations currently using AI? KL: AI is being used to automate an increasing number of numerical, formulaic and repetitive processes. One of the most talked about applications for AI to-date is for self-driving or autonomous vehicles. Codelco, for example, is a Chilean copper mining company that has been a global pioneer in the use of autonomous trucks.