https://www.techrepublic.com/article/github-here-are-the-biggest-open-source-project-trends-well-see-in-2018/ Cross-platform development, new skills, and deep learning communities are seeing the most growth on GitHub. Developers are also heading to the site to look at deep learning projects as artificial intelligence continues to grow. →
http://www.iflscience.com/brain/artificial-intelligence-recreates-images-from-inside-the-human-brain/?utm_source=Editorial&utm_medium=Static&utm_campaign=JC This looks like wild sci-fi: A team of researchers say they have used machine-learning to recreate images in our brains, from pictures subjects were looking at to things they remember seeing. Using functional magnetic resonance imaging (fMRI), the team said they were able to reconstruct images seen by our brains. →
https://ml-cheatsheet.readthedocs.io/en/latest/index.html Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources. →
https://enterprisersproject.com/article/2017/12/3-ai-misconceptions-it-leaders-must-dispel?sc_cid=7016000000127ECAAY Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain. AI doesn’t think in our sense of the word at all, →
https://blogs.sas.com/content/subconsciousmusings/2017/04/12/machine-learning-algorithm-use/?utm_source=facebook&utm_medium=cpc&utm_campaign=analytics-global&utm_content=US_interests-conversions This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. →
http://www.iflscience.com/technology/sophia-the-worlds-first-android-citizen-says-she-wants-to-have-a-kid/ This strange story becomes even more bizarre: Last month Saudi Arabia granted citizenship to an android called Sophia? Well, stuff just got a little bit stranger. In a recent interview with The Khaleej Times, Sophia suggested she wants to start her own family. Are we going to be replaced with robots in this science fiction fairy tale? Wild →
https://developers.googleblog.com/2017/11/announcing-tensorflow-lite.html?m=1 Google has announced TensorFlow machine learning for Android and iOS devices: “we’re happy to announce the developer preview of TensorFlow Lite, TensorFlow’s lightweight solution for mobile and embedded devices! TensorFlow has always run on many platforms, from racks of servers to tiny IoT devices” TensorFlow already supports mobile and embedded deployment of models through →
http://www.ibmbigdatahub.com/blog/5-tips-machine-learning-success-outside-silicon-valley This article has a few concrete suggestions for those hearing about the machine learning efforts in Silicon Valley, but who work elsewhere. →
https://securityintelligence.com/man-with-machine-harnessing-the-potential-of-artificial-intelligence/?cm_mmc=PSocial_Facebook-_-Security_Detect%20threats%20-%20QRadar-_-WW_WW-_-23012462_Tracking%20Pixel&cm_mmca1=000017NK&cm_mmca2=10004134&cm_mmca4=23012462&cm_mmca5=48989195&cm_mmca6=bdfe5818-7fea-4ba1-a728-fef91b396b4d&cvosrc=social%20network%20paid.facebook.WW%20Newsfeed%20Job%20Title%20CISO%20Discover%20SI%20Blog%20Engagement%20SI%20Watson%20Man%20With%20Machine%20AI%20Watson1%20_SD%20Behav_DesktopMobile%20Tablet_1x1&cvo_campaign=000017NK&cvo_pid=23012462 When we think of artificial intelligence (AI), we think of robots — machines that mimic human behavior or thought. This is partly the influence of comics, novels, movies and other pop culture tidbits, but the boundaries of AI have progressed far beyond this basic personification. At its most basic level, machine learning, a subset of →
https://m.dpreview.com/news/2842585992/researchers-teach-algorithm-about-textures-to-create-high-res-versions-of-low-res-images Upsampling image and video files usually leads to pixelation and soft textures, simply because algorithms are not capable of replacing non-existing image detail. But scientists at the Max-Planck Institute for Intelligent Systems in Germany have come up with a clever solution that is capable of producing better results than anything we’ve seen so far. →