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Generative Adversarial Networks (GANs) are a fascinating class of machine learning models used to generate new data that resembles the training data. They were first introduced by Ian Goodfellow and his colleagues in 2014. GANs are particularly popular in the field of image generation but have applications in other areas as well. Here’s how GANs Read More
Source: newatlas.com A pair of newly published studies are demonstrating how passive smartphone data can be used to effectively predict relapse episodes in schizophrenia patients. The research used machine learning to analyze behavioral data and predict schizophrenic relapses up to one month before they occurred. The data used in both new papers was gathered from Read More
Source: healthitanalytics.com A team from Stevens Institute of Technology has developed an artificial intelligence tool that can diagnose Alzheimer’s disease with more than 95 percent accuracy, eliminating the need for expensive scans or in-person testing. In addition, the algorithm is also able to explain its conclusions, enabling human experts to check the accuracy of its diagnosis. Alzheimer’s Read More
Source: unite.ai One of the less glamorous aspects of artificial intelligence is that it often requires a large amount of processing power and therefore it often has a large energy footprint. Recent work done by researchers at UCL has determined a method of improving an AI’s energy efficiency. Neural networks and machine learning are powerful Read More
Source: healthitanalytics.com A deep learning tool could improve genomic sequencing processes, identifying disease-causing mechanisms that might otherwise be missed by traditional screening methods, according to a study published in Nature Machine Intelligence. Researchers from Children’s Hospital of Philadelphia (CHOP) and New Jersey Institute of Technology (NJIT) developed the tool, which can help predict sites of DNA methylation – Read More
Source: healthitanalytics.com June 30, 2020 – An artificial intelligence algorithm can analyze electroencephalograph (EEG) electrodes to detect a seizure and accurately pinpoint its location, according to a study published in Scientific Reports. The researchers stated that epilepsy is one of the most common central nervous system disorders, with nearly four percent of people across different ages diagnosed with epilepsy during Read More
Source: scitechdaily.com Researchers in Italy have melded the emerging science of convolutional neural networks (CNNs) with deep learning — a discipline within artificial intelligence — to achieve a system of market forecasting with the potential for greater gains and fewer losses than previous attempts to use AI methods to manage stock portfolios. The team, led Read More
Source: newelectronics.co.uk British technology companies XMOS and Plumerai have agreed a new strategic partnership that will support the development of binarised neural network (BNN) capabilities, enabling AI to be embedded in a wide range of everyday devices efficiently at low power and at low cost. The partnership combines Plumerai’s Larq software library for training BNNs Read More
Source: cphi.com The utilisation of artificial intelligence (AI) by the pharmaceutical industry is gathering pace rapidly. The technology has evolved beyond simple neural networks and machine learning towards a deep learning approach geared at producing insights which should in theory enable better business decision making. AI’s remit is largely to tackle complex problems in ways similar Read More
Source: zmescience.com If you want a machine to learn to do something intelligent you either have to program it or teach it to learn. For decades, engineers have been programming machines to perform all sorts of tasks — from software that runs on your personal computer and smartphone to guidance control for space missions. But Read More
Source:bdtechtalks.com Two separate studies, one by UK-based artificial intelligence lab DeepMind and the other by researchers in Germany and Greece, display the fascinating relations between AI and neuroscience. As most scientists will tell you, we are still decades away from building artificial general intelligence, machines that can solve problems as efficiently as humans. On the path to Read More
Source: devclass.com AWS has quietly open sourced an open source tool kit it claims will “democratise” machine learning by removing much of the hand tooling data scientists currently fill their time with. The cloud to everything giant’s AutoGluon slipped onto GitHub last year, under the Apache 2 license, but AWS is only now cranking up the publicity Read More
Source:-analyticsindiamag.com As larger neural networks with more layers and nodes are considered, reducing their storage and computational cost becomes critical, especially for some real-time applications such as online learning and incremental learning In addition, recent years witnessed significant progress in virtual reality, augmented reality, and smart wearable devices, creating challenges in deploying deep learning systems Read More
Source: analyticsinsight.net The news nowadays is brimming with anecdotes about AI. Recently, we’re perceiving how deep fake strategies make changed and persuading videos, photographs or audio of individuals and how deep learning and neural networks succeed at the exceptionally complex strategy board game Go. Notwithstanding these sorts of applications, organizations keep on the struggle to Read More
Source:- cosmosmagazine.com Facebook automatically finds and tags friends in your photos. Google Deepmind’s AlphaGo computer program trounced champions at the ancient game of Go last year. Skype translates spoken conversations in real time – and pretty accurately too. Behind all this is a type of artificial intelligence called deep learning. But what is deep learning and Read More
Source – techcrunch.com We’ve already taken a look at neural networks and deep learning techniques in a previous post, so now it’s time to address another major component of deep learning: data — meaning the images, videos, emails, driving patterns, phrases, objects and so on that are used to train neural networks. Surprisingly, despite our world being Read More
