AI

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. →

http://tech.newstatesman.com/news/conscious-machines-way-off  Breakthroughs in narrow AI, no progress towards general AI. I think he’s a bit optimistic on self-driving cars, at least for Finnish winter driving  “We’re beginning to get there with better ideas about the brain, but all the progress in AI over the last decade which is real and exciting has been on narrow →

https://techcrunch.com/2017/10/08/comparing-alexa-google-assistant-cortana-and-siri-smart-speakers/  The smart home assistant race has been building to a fever pitch over the course of the last couple of years. Things really came to head this past two weeks, when Amazon, Google and Sonos all held big events highlighting their latest smart speaker plays, making the already busy field a heck of a lot more crowded. →

https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/?utm_campaign=add_this&utm_source=twitter&utm_medium=post We are surrounded by hysteria about the future of artificial intelligence and robotics—hysteria about how powerful they will become, how quickly, and what they will do to jobs. A story in ­MarketWatch that said robots will take half of today’s jobs in 10 to 20 years. The claims are ludicrous. Today’s robots and AI systems are incredibly narrow in what they →

https://techcrunch.com/2017/09/30/ai-hype-has-peaked-so-whats-next/?ncid=rss&utm_source=tcfbpage&utm_medium=feed&utm_campaign=Feed%3A+Techcrunch+%28TechCrunch%29&utm_content=FaceBook&sr_share=facebook Year 2017 has been the year of AI, reaching a fever pitch of VC and corporate investment. But, as with any hot technology, AI is outgrowing this phase of experimentation and hype. According to research firm Gartner, we’re past the “peak of inflated expectations.”  Next up is a necessary recalibration of the space—one that →

https://sc5.io/posts/use-machine-learning/?utm_content=59645558&utm_medium=social&utm_source=facebook Did you know that without a single hour invested in development, you can approximate the usefulness of machine learning techniques in your product or digital service by answering two simple questions. Read and learn! →

Most pop music is pretty much produced using computers. Is ‘Algorithm Idol’ poised to take its place in the pop music mill? Pop music automation is a field of study among musicians and computer scientists with a goal of producing successful pop music algorithmically. It is often based on the premise that pop music is →