This week's milestones in the history of technology include the coining of the term "artificial intelligence," the digitization of the Library of Congress, and the first penny paper. The first issue of Scientific American is published by Rufus Porter as a weekly broadsheet subtitled "The Advocate of Industry and Enterprise, and Journal of Mechanical and Other Improvements." In an era of rapid innovation, Scientific American founded the first branch of the U.S. Patent Agency, in 1850, to provide technical help and legal advice to inventors. A Washington, D.C., branch was added in 1859. By 1900 more than 100,000 inventions had been patented thanks to Scientific American.
A team of researchers from the University of Albany have developed a method of combating Deepfake videos, using machine learning techniques to search videos for digital "fingerprints" left behind when a video has been altered. One of the biggest concerns in the tech world over the past couple of years has been the rise of Deepfakes. Deepfakes are a type of fake video constructed by artificial intelligence algorithms run through deep neural networks, and the products of the deepfake technology are shockingly good – sometimes difficult to tell apart from a real, genuine video. AI researchers, ethicists, and political scientists are worried that the Deepfake technology will eventually be used to impact political elections, disseminating misinformation in a form more convincing than a fake news story. In order to provide some defense against the manipulation and misinformation that Deepfakes can cause, researchers from the University of Albany have created tools to assist in the detection of fake videos.
It's used internally and to me it's the perfect thickness of abstraction for DL research if you use TF. I write a lot of custom layers and while there are a few TF quirks you have to know, Sonnet has much less mental overhead than the TF.layers lib and is way more "hackable." I tried out all the other topper libs pretty extensively and Sonnet really stood out. The main issue with external adoption, is, well, that there is none _ . I tried looking up a DCGAN example in Sonnet and couldn't find an open source one...there are lots internally, though.
This article was written by a human being who click-clacked on a keyboard until she finished a draft and sent it to an editor. But more and more, computers are taking over. In fact, the Associated Press has used "automation technology" to cover college sports since 2015. The idea isn't new--humans have obsessed over artificial intelligence (AI) since at least the 18th century, when the "Mechanical Turk" hoax led many to believe that a machine could play chess against a person and win. About 250 years later, a machine can play chess against a person and win--every time.
Derpfakes uses the same tools from the controversial porn to make experimental face-swapped movie and TV footage. The account has posted videos from Toy Story, Star Trek, and The Room. Star Wars is also a favorite target because of the recent use of questionable CGI characters to stand-in for aged and deceased actors. The latest post tackles Solo, replacing star Alden Ehrenreich with a young Harrison Ford. The results aren't perfect, but it's impressive for something done with essentially no budget.
Nothing you've written is special enough to be worth selling or licensing, you can't use the code as proof of ability for a portfolio if you can't prove the code isn't plagiarized or badly designed and written, and it's certainly not any kind of tutorial. What you're doing doesn't fit any motives I can think of except a combination of stroking your own ego and delusion. What is your goal here, seriously?
Although developments in the field of artificial intelligence began around the 1950s, its capacities have significantly increased in the recent years. Owing to factors such as the development of faster computers, availability of open-source software and the access to vast amounts of computational data, AI has now branched into machine learning (ML), probabilistic predictions, chaos theory and evolutionary computation. Investing in artificial intelligence courses, therefore, prepares people to undertake not just one, but many AI applications. AI and ML already play a pivotal role in our day-to-day life, even without our realization. Netflix and Amazon use machine-learning algorithms to recommend shows and products based on our usage history.
IBM (NYSE: IBM) today introduced AI OpenScale, a new technology platform that addresses key challenges of artificial intelligence (AI) adoption, such as concerns over how AI applications make decisions, the global shortage of AI skills and the complexities of working with disparate AI tools from multiple vendors. IBM's new technology platform is the first of its kind. It will enable companies to manage AI transparently throughout the full AI lifecycle, irrespective of where their AI applications were built or in which environment they currently run. AI OpenScale can detect and address bias across the spectrum of AI applications, as those applications are being run. As part of AI OpenScale, IBM also will debut NeuNetS, a major scientific breakthrough in which AI builds AI – making it possible to create complex, deep-neural networks from scratch.