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.
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.
For many people, speaking off the cuff to a large audience does not come easily. But without professional feedback, rehearsing speeches and presentations can be a tough process. A psychologist, a management scientist and an IT specialist have developed an online training tool that uses artificial intelligence to evaluate users' speaking skills and personal characteristics. The team has now established the start-up Retorio at the Technical University of Munich (TUM) to launch the software on the market. It's a scenario many people can relate to – standing all alone in front of an audience, clutching a microphone with clammy hands and finding one's mouth has gone dry.
It goes without saying that artificial intelligence is changing the nature of industries from transportation to finance, and education is no different with the prospect of personalized learning quickly becoming a reality. As more and more of a student's education is experienced through a computer, data on their educational progress can be collected, leading to more personalized learning plans while assisting the teacher in identifying problem areas for students. While artificial intelligence in education might appear unnerving for some, the benefits are too great to ignore. There are few spaces in life that haven't been touched in some form by computer software. Whether it's shopping, dating, or just keeping up with old friends, everything we do seems to be mediated in some form by computers.
This course is about deep learning fundamentals and convolutional neural networks. Convolutional neural networks are one of the most successful deep learning approaches: self-driving cars rely heavily on this algorithm. First you will learn about densly connected neural networks and its problems. The next chapter are about convolutional neural networks: theory as well as implementation in Java with the deeplearning4j library. The last chapters are about recurrent neural networks and the applications!
Innovations in artificial intelligence development and usage are influencing sectors far beyond the tech world, leaving few areas untouched. Even the educational field will soon be reaping many benefits of AI applications. In this article, we will discuss seven ways educators can use artificial intelligence. This may be the most promising application area of AI in education. AI in schools could track individual students' progress and either adjust the coursework or notify the teacher that a student is having difficulties understanding the material.
Machine learning is an incredibly broad and diverse field, with a non-stop increase on research, along a multitude of applications. Thus writing a list enlisting the best machine learning researchers on the field proves challenging for a number of reasons. Please mind that this list encompasses researchers who are currently working on the field. Also, please mind that this list is by no means ranked. Everyone listed below has done extraordinary work to advance humanity's state of AI further.
Artificial intelligence can quickly and accurately rate the amount of atrophy in parts of the brain, which can help in the diagnosis and research of dementia. A new study reported in arXiv.org, It is an inexpensive way to quantify brain atrophy and helps improve the specificity and sensitivity of diagnosis. These visual atrophy ratings aren't used widely because the ratings are inherently subjective, researchers note. Radiologists performing them need to be experienced in such work, and the assessments are tedious and time consuming--it takes several minutes per image for a neuroradiologist to perform the rating.
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