A British computer scientist who earned the nickname "the Godfather of AI" warned that the dangers of artifical intelligence made famous in films like "The Terminator" could become more reality than fiction. "I think in five years' time, it may well be able to reason better than us," Geoffrey Hinton, a British computer scientist and cognitive psychologist, said during an interview with "60 Minutes," according to a report from Yahoo News. Hinton, who became well known for his work on the framework for AI, urged caution in the continued development of AI technology, questioning whether humans can fully understand the technology that is currently seeing rapid development. "I think we're moving into a period when for the first time ever, we have things more intelligent than us," Hinton said. Hinton argued that while humans develop the algorithm AI tools use to learn, they have little understanding of how that learning actually takes place.

From mobile work to security and maintenance, perhaps no company has done more for the advancement of technology in today's society than SkyNet, a promising start up out of Austin, Texas that has made great strides during the COVID-19 pandemic. Last year, their T-400 model of home assistant swept the country, combining at home personal assistants with a walking talking android that actually helped with chores and tasks around the house. We had the opportunity to sit down with Barry Snow, the CEO of the skyrocketing company, about SkyNet's future and some of the backlash to what some have called "unnecessarily violent home assistants." Can I have one of those waters? So, your company was already gaining steam a few years ago, but it really seems that during the pandemic you pulled ahead of a lot of your peers with your home androids.

In this post, you will discover the top 10 books available right now on deep learning. There are quite a few available online in which you may purchase. The book Deep Learning with Python written by Keras creator and Google AI researcher François Chollet introduces the field of Deep Learning using python with the powerful and Keras library. It was written in order to build the knowledge and minds of individuals using intuitive explanations and practical examples. The purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

The vast vacant lot along the Monongahela River has been a scar from Pittsburgh's industrial past for decades. It was once the site of the Jones and Laughlin steelworks, one of the largest such facilities in the city back when steel was the dominant industry there. Most of the massive structures are long gone, leaving behind empty fields pocked with occasional remnants of steelmaking and a few odd buildings. Next to the sprawling site is one of Pittsburgh's poorer neighborhoods, Hazelwood, where a house can go for less than $50,000. As with many of the towns that stretch south along the river toward West Virginia, like McKeesport and Duquesne, the economic reasons for its existence--steel and coal--are a fading memory. These days the old steel site, called Hazelwood Green by its developers, is coming back to life.

Deep learning is one of the most exciting elements of artificial intelligence, but it's also one of the slowest moving. IBM Fellow Hillery Hunter calls deep learning, which enables computers to extract meaning from images and sounds with no human intervention, a "rarified thing, off in an ivory tower," but a recent breakthrough by the company promises to make it more accessible -- and a lot faster too. Last week IBM Corp. (NYSE: IBM) announced that its software was able to take the speed of training deep neural networks down from weeks to hours, or hours to minutes depending on the use case, while also improving the accuracy. It accomplished this by increasing the scalability of its training applications across 256 Nvidia Corp. (Nasdaq: NVDA) GPUs in 64 IBM Power systems. IBM was looking specifically at image recognition and was able to train its model in 50 minutes.

Written by Ophir Gottlieb and Jason Hitchings PREFACE It's coming. It will impact almost everything: communication will be revolutionized, entertainment will expand, business structures will be transformed. It is one of the revolutionary themes, one of the fundamental shifts coming in the very near future that will change how we live, work, and play. " This is a technology whose consumer base looks increasingly like [all of] humanity. Source: Dave Thier, Forbes Facebook (NASDAQ:FB), Alphabet (NASDAQ:GOOGL), Amazon (NASDAQ:AMZN), Apple (NASDAQ:AAPL), Microsoft (NASDAQ:MSFT), International Business Machine (NYSE:IBM) and China's Baidu (NASDAQ:BIDU) are already in. Google acquired deep learning research group DeepMind for half a billion dollars in 2014. IBM acquired AlchemyAPI last year and Apple made two acquisitions in just four days. The next "big thing" is Virtual Reality --it's larger than anyone is forecasting, and the likely victor will not be any of the companies we just listed above. This is the opportunity so many investors say they welcome -- say they search for. The opportunity to find the "Next Apple," or the "next Google." Friends, it's coming right now, and it lies in the depths of technology's core. " Recent breakthroughs in GPU-accelerated deep-learning techniques have made it possible to reach exceptional improvements in pattern recognition.