AI image recognition fooled by single pixel change. Image copyright Anish Athalye Computers can be fooled into thinking a picture of a taxi is a dog just by changing one pixel, suggests research. The limitations emerged from Japanese work on ways to fool widely used AI-based image recognition systems. Many other scientists are now creating "adversarial" example images to expose the fragility of certain types of recognition software. There is no quick and easy way to fix image recognition systems to stop them being fooled in this way, warn experts. Bomber or bulldog? In their research, Su Jiawei and colleagues at Kyushu University made tiny changes to lots of pictures that were then analysed by widely used AI-based image recognition systems. All the systems they tested were based around a type of AI known as deep neural networks.
The researchers found that changing one pixel in about 74% of the test images made the neural nets wrongly label what they saw. Image copyright Science Photo Library Deep issues "This is an open problem," he said. A computer was asked to predict which start-ups would be successful. The results were astonishing | World Economic Forum. In 2009, Ira Sager of Businessweek magazine set a challenge for Quid AI's CEO Bob Goodson: programme a computer to pick 50 unheard of companies that are set to rock the world. The domain of picking “start-up winners” was - and largely still is - dominated by a belief held by the venture capital (VC) industry that machines do not play a role in the identification of winners.
Ironically, the VC world, having fuelled the creation of computing, is one of the last areas of business to introduce computing to decision-making. Nearly eight years later, the magazine revisited the list to see how “Goodson plus the machine” had performed. The results surprised even Goodson: Evernote, Spotify, Etsy, Zynga, Palantir, Cloudera, OPOWER – the list goes on. The list featured not only names widely known to the public and leaders of industries, but also high performers such as Ibibo, which had eight employees in 2009 when selected and now has $2 billion annual sales as the top hotel booking site in India. Can We Quantify Machine Consciousness? 3. Engineering Cognition Imagine that at some time in the not-too-distant future, you’ve bought a smartphone that comes bundled with a personal digital assistant (PDA) living in the cloud.
You assign a sexy female voice to the PDA and give it access to all of your emails, social media accounts, calendar, photo album, contacts, and other bits and flotsam of your digital life. She—for that’s how you quickly think of her—knows you better than your mother, your soon-to-be ex-wife, your friends, or your therapist. Her command of English is flawless; you have endless conversations about daily events; she gets your jokes. She is the last voice you hear before you drift off to sleep and the first upon awakening. You panic when she’s off-line.
This, of course, is the plot of Her, a 2013 movie in which an anodyne Theodore Twombly falls in love with the software PDA Samantha. Over the next few decades such a fictional scenario will become real and commonplace. Or perhaps she won’t. Age of Aritificial Intelligence: How We’re Already Living In a Sci-Fi Future. What is AI? When we talk about artificial intelligence (AI) most people still imagine robots who can talk, act, and behave (to a certain extent) like a human being — like a C-3PO (Star Wars), sans the metallic look. Or maybe, a supercomputer that can read human behavior so well that it interacts seamlessly with us, while controlling the system — like Hal 9000 (2001: A Space Odyssey) or Auto (Wall-E). While, arguably, we may not be there yet in terms of our command of AI, we are not that far. AI is definitely the direction tech development is taking, as evidenced by most recent trends, including the formation of a partnership by tech giants to push the frontier of AI.
AI refers to intelligence exhibited by machines or computers, particularly as it pertains to the use of these computers to analyze and understand human intelligence — or approximate intelligent behavior. Perhaps the two most common behaviors are speech-recognition and image and pattern recognition. Today’s AI. Augmented Reality: Top 100 Influencers and Brands.
Augmented reality (AR) is a live direct or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. As a result, the technology functions by enhancing one’s current perception of reality. This is in contrast to virtual reality which replaces the real world with a simulated one. AR is in the early stages of an explosive growth cycle. The Pokemon Go phenomenon raised awareness and expectation for the vision of AR. Worldwide AR markets are poised to achieve significant growth with the use of smartphone apps and headsets or glasses to project digital information as images onto a game image or a work situation. Game Based and Industrial End-To-End Process IoT Augmented Reality markets are anticipated to reach $7 Trillion by 2027 according to Research and Markets.
We reached out to some of the top influencers on our list to ask them for their views on augmented reality. Deep Learning Race: A Survey of Industry Players’ Strategies. I’ve been working for quite a while now in trying to make sense of the research developments in Deep Learning. The methodology I’ve employed is through the cataloging of Design Patterns. It’s been quite effective in disentangling this ever growing complex field. In fact, as new surprising research is published by the giants in this field, my own conceptual understanding of how it all fits together continues to be tweaked. There are however certain patterns that I have observed that is actually outside that of a general understanding of Deep Learning. What I’ve observed is that the different leading research groups seem to emphasize different kinds of approaches in solving the riddle of artificial intelligence.
However, by just reading the research publications, that fortunately come out quite occasionally, one gets a sense that organizations favor one approach from the other. Google DeepMind Google Brain ($GOOG) Facebook FAIR ($FB) This is headed by Yann LeCun. Microsoft ($MSFT) OpenAI Uber. This is Amazon's Biggest Contribution to Artificial Intelligence So Far - 1re... Amazon recently announced three major services that are aimed at making things easier for developers to exploit Artificial Intelligence (AI) capabilities. AI has been one of the weakest links in Amazon’s robust stack of cloud infrastructure services which, incidentally, took the company to the top of the cloud industry due their breadth and depth offered. Meanwhile, tech majors Google, Microsoft and IBM, Amazon’s competitors in the cloud race, already have robust AI platforms that are constantly being upgraded and fine-tuned.
Google, for example, has been working on AI for a very long time, and even acquired DeepMind in 2014 to extend their capabilities in a big way. IBM’s strong push into the cloud segment is actually built around Watson, which goes much further and deeper than any of the traditional AI applications we have seen. Microsoft has been working on its own AI platform for many years – can anyone forget the meltdown their chatbot Tay had on Twitter? Amazon Lex Amazon Polly. What the AI Behind AlphaGo Can Teach Us About Being Human. By Cade Metz 05.19.16 Aja Huang dips his hand into a wooden bowl of polished black stones and, without looking, thumbs one between his middle and index finger. Peering through wire-rim glasses, he places the black stone on the board, in a mostly empty zone, just below and to the left of a single white stone. In Go parlance it is a “shoulder hit,” in from the side, far away from most of the game’s other action.
Across the table, Lee Sedol, the best Go player of the past decade, freezes. In the commentary room, about 50 feet away, Michael Redmond is watching the game via closed-circuit. “I thought it was a mistake,” says the other English-language commentator, Chris Garlock, vice president of communications for the American Go Association. A few minutes later, Lee walks back into the match room. Huang’s move was just the 37th in the game, but Lee never recovers from the blow. But Huang was not the true winner of this game of Go. But don’t weep for Lee Sedol in his defeat, or for humanity.
Forbes Welcome. Take the Poll: What Is AI’s Role in Your Organization? - CIO Journal. The use of artificial intelligence, which has been growing in fits and starts for years, is starting to play a much bigger role in business. The worldwide market for AI platforms and applications is expected to grow to $16.5 billion in 2019 from $1.6 billion in 2015, according to the International Data Corp. Faster and cheaper computing is helping fuel today’s AI revolution. But while many large tech firms and startups have been able to build new AI-influenced business models, many organizations, with access to much of the same computing power, are still grappling with how to best employ AI, CIO Journal’s Steven Norton writes in CIO Explainer: What is Artificial Intelligence?
A host of issues, from executive confusion over AI capabilities to concerns over the effect intelligent machines will have on a human workforce, could slow deployment. Let us know what role, if any, artificial intelligence plays in your company. Rob Thomas: A Practical Guide to Machine Learning: Understand, Differentiate, and Apply. Co-authored by Jean-Francois Puget (@JFPuget) Machine Learning represents the new frontier in analytics, and is the answer of how many companies can capitalize on the data opportunity.
Machine Learning was first defined by Arthur Samuel in 1959 as a “Field of study that gives computers the ability to learn without being explicitly programmed.” Said another way, this is the automation of analytics, so that it can be applied at scale. What is highly manual today (think about an analyst combing thousand line spreadsheets), becomes automatic tomorrow (an easy button) through technology. If Machine Learning was first defined in 1959, why is this now the time to seize the opportunity? A relative graphic to explain: Since the time that Machine Learning was defined and through the last decade, the application of Machine Learning was limited by the cost of compute and data acquisition/preparation.
These scenarios, and others like them, create a unique opportunity for machine learning. Toyota Invests $1 Billion in AI and Robots, Will Open R&D Lab in Silicon Valley. Today in Tokyo, Toyota announced that it is investing US $1 billion over the next five years to establish a new R&D arm headquartered in Silicon Valley and focused on artificial intelligence and robotics. The Toyota Research Institute (TRI) plans to hire hundreds of engineers to staff a main facility in Palo Alto, Calif., near Stanford University, and a second facility located near MIT in Cambridge, Mass. Former DARPA program manager Dr. Gill Pratt, an executive technical advisor at Toyota, was named CEO of TRI, which will begin operations in January. Toyota president Akio Toyoda said in a press conference that the company pursues innovation and new technologies “to make life better for our customers and society as a whole,” adding that he wanted to “work with Gill not just because he’s an amazing researcher and engineer, but because I believe his goals and motivations are the same as ours.”
We spoke to Dr. TRI’s initial focus is AI for cars and robots, Dr. Dr. The ultimate guide to AI. What does artificial intelligence mean to you? If you believe the movies, AI is something theoretical, futuristic…far away. It’s a rampaging robot or a piece of malign code intent on world domination. Recent fears about AI raised by the likes of Stephen Hawking, Elon Musk and Bill Gates have only served to feed that chilling – but pretty unlikely – sci-fi narrative. Or perhaps the AI you know is a clumsy robot failing spectacularly or a chatbot churning out gobbledegook: a long, long way from human intelligence. The truth is, artificial intelligence surrounds us already – it just doesn’t act in the way we expect The trouble with looking at AI in this way is that it obscures how the technology will actually change our lives.
We joke about our future robot overlords, then return to real, human life. That’s why BBC Future has decided to run a special series exposing the fictions and truth of AI. BBC Future’s Ultimate Guide to AI includes: Coming soon: South Korea’s chilling killer robots. How worried should you be about artificial intelligence? The Myth Of AI.
That mythology, in turn, has spurred a reactionary, perpetual spasm from people who are horrified by what they hear. You'll have a figure say, "The computers will take over the Earth, but that's a good thing, because people had their chance and now we should give it to the machines. " Then you'll have other people say, "Oh, that's horrible, we must stop these computers. " Most recently, some of the most beloved and respected figures in the tech and science world, including Stephen Hawking and Elon Musk, have taken that position of: "Oh my God, these things are an existential threat. They must be stopped. " In the past, all kinds of different figures have proposed that this kind of thing will happen, using different terminology.
Some of them like the idea of the computers taking over, and some of them don't. What do I mean by AI being a fake thing? For instance, we can talk about pattern classification. Let's go to another layer of how it's dysfunctional. This is not one of those. Mobile.nytimes. The AI Revolution: Our Immortality or Extinction. Note: This is Part 2 of a two-part series on AI. Part 1 is here. PDF: We made a fancy PDF of this post for printing and offline viewing. Buy it here. (Or see a preview.) We have what may be an extremely difficult problem with an unknown time to solve it, on which quite possibly the entire future of humanity depends. — Nick Bostrom Welcome to Part 2 of the “Wait how is this possibly what I’m reading I don’t get why everyone isn’t talking about this” series.
Part 1 started innocently enough, as we discussed Artificial Narrow Intelligence, or ANI (AI that specializes in one narrow task like coming up with driving routes or playing chess), and how it’s all around us in the world today. This left us staring at the screen, confronting the intense concept of potentially-in-our-lifetime Artificial Superintelligence, or ASI (AI that’s way smarter than any human, across the board), and trying to figure out which emotion we were supposed to have on as we thought about that.← open these i.e. Timeline. The AI Revolution: Our Immortality or Extinction. Research_priorities.pdf. Facebook AI Director Yann LeCun on His Quest to Unleash Deep Learning and Make Machines Smarter.
Artificial intelligence has gone through some dismal periods, which those in the field gloomily refer to as “AI winters.” This is not one of those times; in fact, AI is so hot right now that tech giants like Google, Facebook, Apple, Baidu, and Microsoft are battling for the leading minds in the field. The current excitement about AI stems, in great part, from groundbreaking advances involving what are known as “convolutional neural networks.” This machine learning technique promises dramatic improvements in things like computer vision, speech recognition, and natural language processing. You probably have heard of it by its more layperson-friendly name: “Deep Learning.” Few people have been more closely associated with Deep Learning than Yann LeCun, 54. More recently, Deep Learning and its related fields grew to become one of the most active areas in computer research.