artificial intelligence News for August 10 2017

Great Debate – Artificial Intelligence: Who is in control? (OFFICIAL) (Part 01)

Part 02 – https://youtu.be/eXc5cWEkb4Y Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, …

Artificial intelligence and the coming health revolution

Artificial intelligence is rapidly moving into health care, led by some of the biggest technology companies and emerging startups using it to diagnose and respond to a raft of conditions. McCarthy said advances in artificial intelligence has opened up new possibilities for “Personalized medicine” adapted to individual genetics. AI is better known in the tech field for uses such as autonomous driving, or defeating experts in the board game Go. But it can also be used to glean new insights from existing data such as electronic health records and lab tests, says Narges Razavian, a professor at New York University’s Langone School of Medicine who led a research project on predictive analytics for more than 100 medical conditions. NYU researchers analyzed medical and lab records to accurately predict the onset of dozens of diseases and conditions including type 2 diabetes, heart or kidney failure and stroke. Google’s DeepMind division is using artificial intelligence to help doctors analyze tissue samples to determine the likelihood that breast and other cancers will spread, and develop the best radiotherapy treatments. Amazon meanwhile offers medical advice through applications on its voice-activated artificial assistant Alexa. IBM has been focusing on these issues with its Watson Health unit, which uses “Cognitive computing” to help understand cancer and other diseases. When IBM’s Watson computing system won the TV game show Jeopardy in 2011, “There were a lot of folks in health care who said that is the same process doctors use when they try to understand health care,” said Anil Jain, chief medical officer of Watson Health. It’s not just major tech companies moving into health. Research firm CB Insights this year identified 106 digital health startups applying machine learning and predictive analytics “To reduce drug discovery times, provide virtual assistance to patients, and diagnose ailments by processing medical images.” San Francisco’s Woebot Labs this month debuted on Facebook Messenger what it dubs the first chatbot offering “Cognitive behavioral therapy” online-partly as a way to reach people wary of the social stigma of seeking mental health care. Lynda Chin, vice chancellor and chief innovation officer at the University of Texas System, said she sees “a lot of excitement around these tools” but that technology alone is unlikely to translate into wide-scale health benefits. More important, she said, is integrating data in health care delivery where doctors may be unaware of what’s available or how to use new tools. Explore further: Artificial intelligence predicts patient lifespans.
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Elon Musk’s Billion-Dollar Crusade to Stop the A.I. Apocalypse

Google’s search engine from the beginning has been dependent on A.I. All of these small advances are part of the chase to eventually create flexible, self-teaching A.I. that will mirror human learning. Elon Musk began warning about the possibility of A.I. running amok three years ago. Elon Musk smiled when I mentioned to him that he comes across as something of an Ayn Rand-ian hero. His sometimes quixotic efforts to save the world have inspired a parody twitter account, “Bored Elon Musk,” where a faux Musk spouts off wacky ideas such as “Oxford commas as a service” and “Bunches of bananas genetically engineered” so that the bananas ripen one at a time. After the so-called A.I. winter-the broad, commercial failure in the late 80s of an early A.I. technology that wasn’t up to snuff-artificial intelligence got a reputation as snake oil. Greg Brockman, of OpenAI, believes the next decade will be all about A.I., with everyone throwing money at the small number of “Wizards” who know the A.I. “Incantations.” Guys who got rich writing code to solve banal problems like how to pay a stranger for stuff online now contemplate a vertiginous world where they are the creators of a new reality and perhaps a new species. Last June, a researcher at DeepMind co-authored a paper outlining a way to design a “Big red button” that could be used as a kill switch to stop A.I. from inflicting harm. At times, Musk has expressed concern that Page may be naïve about how A.I. could play out. Musk’s disagreement with Page over the potential dangers of A.I. “Did affect our friendship for a while,” Musk says, “But that has since passed. We are on good terms these days.” Three weeks after Musk and Altman announced their venture to make the world safe from malicious A.I., Zuckerberg posted on Facebook that his project for the year was building a helpful A.I. to assist him in managing his home-everything from recognizing his friends and letting them inside to keeping an eye on the nursery. Clearly throwing shade at Musk, he continued: “Some people fear-monger about how A.I. is a huge danger, but that seems far-fetched to me and much less likely than disasters due to widespread disease, violence, etc.” Or, as he described his philosophy at a Facebook developers’ conference last April, in a clear rejection of warnings from Musk and others he believes to be alarmists: “Choose hope over fear.” “There are some very deeply tricky questions around this …. If you really push on how do we make A.I. safe, I don’t think people have any clue. We don’t even know what A.I. is. It’s very hard to know how it would be controllable.” The 54-year-old British-American expert on A.I. told me that his thinking had evolved and that he now “Violently” disagrees with Kurzweil and others who feel that ceding the planet to super-intelligent A.I. is just fine. Don’t get sidetracked by the idea of killer robots, Musk said, noting, “The thing about A.I. is that it’s not the robot; it’s the computer algorithm in the Net. So the robot would just be an end effector, just a series of sensors and actuators. A.I. is in the Net …. The important thing is that if we do get some sort of runaway algorithm, then the human A.I. collective can stop the runaway algorithm. But if there’s large, centralized A.I. that decides, then there’s no stopping it.”
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Artificial Intelligence and Machine Learning are two very hot buzzwords right now, and often seem to be used interchangeably. So I thought it would be worth writing a piece to explain the difference. Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “Smart”. Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves. Artificial Intelligence has been around for a long time – the Greek myths contain stories of mechanical men designed to mimic our own behavior. Very early European computers were conceived as “Logical machines” and by reproducing capabilities such as basic arithmetic and memory, engineers saw their job, fundamentally, as attempting to create mechanical brains. As technology, and, importantly, our understanding of how our minds work, has progressed, our concept of what constitutes AI has changed. Rather than increasingly complex calculations, work in the field of AI concentrated on mimicking human decision making processes and carrying out tasks in ever more human ways. Artificial Intelligences – devices designed to act intelligently – are often classified into one of two fundamental groups – applied or general. Applied AI is far more common – systems designed to intelligently trade stocks and shares, or manoeuvre an autonomous vehicle would fall into this category. It is also the area that has led to the development of Machine Learning. Often referred to as a subset of AI, it’s really more accurate to think of it as the current state-of-the-art. Two important breakthroughs led to the emergence of Machine Learning as the vehicle which is driving AI development forward with the speed it currently has.
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What is Artificial Intelligence?

Artificial intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized. Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering. Initiating common sense, reasoning and problem-solving power in machines is a difficult and tedious approach. Machine learning is another core part of AI. Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Classification determines the category an object belongs to and regression deals with obtaining a set of numerical input or output examples, thereby discovering functions enabling the generation of suitable outputs from respective inputs. Mathematical analysis of machine learning algorithms and their performance is a well-defined branch of theoretical computer science often referred to as computational learning theory. Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object and gesture recognition. Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning and mapping.
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Artificial Intelligence Engineer

Learn to Build the Impossible Welcome to the Artificial Intelligence Nanodegree program, where virtually anyone on the planet can study to become an AI engineer! We’ve collaborated with leading innovators in the field to bring you world-class curriculum, expert instructors, and exclusive hiring opportunities. This Nanodegree program consists of two terms of three months each. Each term costs $800, paid at the beginning of each term. At this time, there are no scholarships or financial aid available. Apply now, view the frequently asked questions, or learn more about the program.
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Inside the Artificial Intelligence Revolution: Pt. 1 …

Has the artificial intelligence revolution taken us to the verge of witnessing the birth of a new species? How long until machines become smarter than us?
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Artificial intelligence

Artificial intelligence is getting smarter by leaps and bounds – within this century, research suggests, a computer AI could be as “Smart” as a human being. Says Nick Bostrom, it will overtake us: “Machine intelligence is the last invention that humanity will ever need to make.” A philosopher and technologist, Bostrom asks us to think hard about the world we’re building right now, driven by thinking machines. Will our smart machines help to preserve humanity and our values – or will they have values of their own?
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Artificial Intelligence Tutorial

This tutorial provides introductory knowledge on Artificial Intelligence. It would come to a great help if you are about to select Artificial Intelligence as a course subject. This tutorial is prepared for the students at beginner level who aspire to learn Artificial Intelligence. The basic knowledge of Computer Science is mandatory. The knowledge of Mathematics, Languages, Science, Mechanical or Electrical engineering is a plus.
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