The long, arduous process of narrowing down millions of chemical compounds to just a select few that can be further developed into mature drugs, may soon be shortened, thanks to new artificial intelligence (AI) software. Genedata, a bioinformatics solutions company headquartered in Basel, Switzerland, has created Imagence, a high content screening image analysis workflow based on deep learning that cuts image analysis times, while increasing data quality and reproducibility of results. "We have software systems which can more or less analyze almost every assay that you need there, can construct and organize the data, store the data, federate the data and make a decisions along this process," said Stephen Steigele, the head of science at Genedata said in an exclusive interview with R&D Magazine "What we have now specifically solved is we developed a software where we use artificial intelligence to make a part of this research process extremely easy." The task of analyzing high content screening images is often labor-intensive and time-consuming, involving several different levels of expertise with several manual steps, like the selection of extracted features or correct detection of cells. This process, which can take many weeks, is reduced to only a few hours using the new technology.
Education is one of the most powerful predictors of future success that human society has at its disposal. How we gather, process, and disseminate knowledge to each successive generation impacts not just individual success, but a host of other related factors such as economic growth, political empowerment, and technological innovation. It is no secret that access to more effective education for individual students is a key factor in the overall betterment of society – and to women's role in society. I've long been a proponent of better education for women – from my early career days working for CARE, to becoming the Chief Strategy Officer of Top Scholar, contributing to the book "Innovating Women" and to founding a non-profit to help the disadvantaged attain better education. Recently, I've been looking around globally for innovative solutions that can leapfrog women's education forward.
HDFC Bank, arguably India's best managed bank in terms of risk mitigation and sustained profitability metrics, heavily uses machine learning technologies to create accurate credit risk models. The bank also has to its credit innovations such as 10 second loans, for which it uses algorithms. To boost its machine learning and AI capability, the bank has launched a hackathon on HackerEarth. "Under the Centre of Digital Excellence (CODE), the Bank is organising the Hackathon challenge to hire data scientists. The top talent that emerges out of this challenge will be offered the chance to work in the Bank in the risk analytics team. We are looking at specialisation in coding and machine learning. This initiative is part of the Bank's endeavour to remain at the cutting edge of leading technologies like AI, ML etc. We hope to harness the potential talent that exists outside to enhance our capabilities in digital and technology," said Nitin Chugh, Country Head – Digital Banking, HDFC Bank.
Hi-Rez founder and CEO Erez Goren is stepping down and handing the reigns to Stewart Chisam. Chisam joined Hi-Rez as VP of operations in 2008 and has most recently led the company's transition into publishing. The change comes after an impressive year of commercial growth for the company, which is best known for its free-to-play games Smite and Paladins. "This is something that Erez and I have been planning for a while - really since I took the President role in 2014," Chisam told GamesIndustry.biz.-- "With the company in good shape and entering its next stage of growth, we thought now was a good time to make the change. Many people may not realize it, but Erez is a very successful entrepreneur that has started multiple successful companies in several industries. Over the past year or two, he has taken more and more interest in solving some healthcare industry problems using machine learning technology, as well as one or two other outside interests. The CEO change at Hi-Rez gives him the opportunity to spend the time he needs to with his other companies to help ensure their success, while still being engaged in the high level strategy."
Business analysts today have more tools than ever at their disposal thanks to the use of artificial intelligence and machine learning technologies. The basic idea is that AI and machine learning are available to improve performance data by learning from it over time. By introducing the concept of automation is possible for AI systems to identify various trends within a business and even make suggestions on how a business can run more efficiently. Business analysts are commonly known as being professionals that regularly look in on businesses and create solutions using data that can improve businesses in almost any industry. By introducing machine learning and AI tools, it could be possible for a business to police itself basically and have an ongoing software analysis on how they could run more efficiently.
It feels like this week wouldn't end, but Friday's finally here. Congrats -- you made it. With the weekend upon us, we've rounded up the best deals from Amazon, Walmart, Best Buy, and Macy's on laptops and accessories, home products like cookware and floor care, and Amazon devices and tablets for video streaming and home security. You can save $110 off a pair of Beats by Dre Studio3 headphones at Best Buy and save $73 off the Instant Pot DUO50 and $20 off the Instant Pot DUO30, both on Amazon. Also, we found deals on Udemy online courses to continue your education into adulthood.
About This Game ABOUT THE GAME while True: learn() is a puzzle/simulation game about even more puzzling stuff: machine learning, neural networks, big data and AI. In this game, you play as a coder who accidentally found out that their cat is extremely good at coding, but not as good at speaking human language. Now this coder (it's you!) must learn all there is to know about machine learning and use visual programming to build a cat-to-human speech recognition system. Learn how machine learning works in real life The game is loosely based on real-life machine learning technologies: from goofy Expert Systems to mighty Recurrent Neural Networks, capable of predicting the future. Don't worry: it all plays out as a puzzle game.
Prof. Shawn Graham's research profile will change your vision of what is to be an archeologist. Originally trained in the traditional study of Roman archaeology, Graham's scholarly career has evolved to focus on the sophisticated fields of digital archaeology, digital history, and the digital humanities. The Department of History's Graham is an active public voice on Twitter and a variety of open access channels like www.electricarchaeology.ca, where he shares, among other things, his research, experiments, ruminations on the modern academy, progressive teaching, and his thoughts and experiences using new learning technology. Woven through his writings are cleverly placed odes to popular art and culture which serve as useful tools to ground and situate the often complex and avant-garde ideas he presents. Notably, Graham is also the founder and editor of the innovative online space Epoiesen: A Journal for Creative Engagement in History and Archaeology.
This AI will tell people when theyre likely to die -- and thats a good thing. Thats because scientists from the University of Adelaide in Australia have used deep learning technology to analyze the computerized tomography (CT) scans of patient organs, in what could one day serve as an early warning system to catch heart disease, cancer, and other diseases early so that intervention can take place. Using a dataset of historical CT scans, and excluding other predictive factors like age, the system developed by the team was able to predict whether patients would die within five years around 70 percent of the time. The work was described in an article published in the journal Scientific Reports. The goal of the research isn't really to predict death, but to produce a more accurate measurement of health, Dr. Luke Oakden-Rayner, a researcher on the project, told Digital Trends.
FDNA, a leader in artificial intelligence and precision medicine, in collaboration with a team of influential scientists and researchers published a milestone study on the use of facial analysis in detecting genetic disorders. The findings in this paper suggest that this type of technology adds significant value in personalized care and will become a standard among deep learning based genomic tools. The paper, titled "Identifying Facial Phenotypes of Genetic Disorders Using Deep Learning", was published in the peer-reviewed journal Nature Medicine (January 07, 2019) as the product of three years of research. The deep learning technology discussed, DeepGestaltTM, is a novel facial analysis framework that highlights the facial phenotypes of hundreds of diseases and genetic variations. "This is a long-awaited breakthrough in medical genetics that has finally come to fruition," said Dr. Karen Gripp, CMO at FDNA and co-author of the paper.