Dr Rao Kambhampati Lecture - "Winding Our Way Down to Wall-E: Adventures in Artificial Intelligence"
Part of the 2014-2015 Honors Lecture Series at Barrett, the Honors College at Arizona State University. Recorded September 22, 2015. For Dr. Kambhampati #39;s sl...
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UC4U - PeterSatera - Artificial Intelligence - [Epic]
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The Fifth Generation of Computer(Artificial Intelligence)
Sjb CST-2E STUDENT (final exam)(Sept 22, 2014) VIDEO PRESENTATION OF THE 5 GENERATION OF COMPUTER . by :Marsjoy Gallego ,Emmanuel Aguas,Danver Medalla, Brix ...
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Artificial Intelligence Profit Bot - See A I Profit Bot At Work- Demo Before Funding An Account
Artificial Intelligence Profit Bot - See A I Profit Bot At Work - You can demo the bot before funding an account. http://BinaryOptionsProducts.com/AIP Eric Stevens #39; Artificial Intelligence...
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Leveraging Artificial Intelligence to Improve Customer Experience
Join AIIM Minnesota for Thirsty Thursday to learn how a global logistics company, a global electronics manufacturer, and a leading mortgage processing organi...
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David Bates, "Thinking Technologies: An Artificial History of Natural Intelligence"
This event was held at the Center for Science, Technology, Medicine Society at the University of California, Berkeley. "Thinking Technologies: An Artificial History of Natural Intelligence"...
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Artificial intelligence programs may already be capable of specialized tasks like flying planes, winning Jeopardy, and giving you a hard time in your favorite video games, but even the most advanced offerings are no smarter than a typical four-year-old child when it comes to broader insights and comprehension. It makes sense, then, that researchers at the University of Gothenburg have developed a program that imitates a child's cognitive development.
"We have developed a program that can learn, for example, basic arithmetic, logic, and grammar without any pre-existing knowledge," says Claes Strannegrd. Starting from a set of simple and broad definitions meant to provide a cognitive model, this program gradually builds new knowledge based on previous knowledge. From that new knowledge it then draws new conclusions about rules and relations that govern the world, and it identifies new patterns to connect the insight to.
The process is similar to how children develop intelligence. A child can intuit, for example, that if 2 x 0 = 0 and 3 x 0 = 0 then 5 x 0 will also equal 0, or they could draw the conclusion that the next number in the series "2, 5, 8" will be 11. And the same kinds of intuition carry across to other areas, such as grammar, where it's easy to identify rules for standard verb conjugations from examples like sing becoming sang and run becoming ran in the past tense.
"We postulate that children learn everything based on experiences and that they are always looking for general patterns," Strannegrd says.
The researchers' system, which they call O*, follows the principle of Occam's razor that you should favor short and simple explanations over long and complex ones. It identifies patterns by itself and combines them with prior knowledge to solve problems.
Sometimes this will lead to errors, such as when children say "I brang my lunch" instead of "I brought my lunch," but O* managed not only to learn arithmetic from scratch, but also to perform above the average human level on propositional logic problems. And given enough information the researchers hope their program could learn and reason its way to correct conclusions across a range of domains without any need for a programmer to explicitly formulate which rules it should apply in a given situation.
"We are hoping that this type of program will eventually be useful in several different practical applications," says Strannegrd. "I think a versatile household robot would be tremendously valuable, but were not there yet."
Strannegrd and his colleagues presented a paper describing O* at the Seventh Conference on Artificial General Intelligence in August.
Source: University of Gothenburg
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15 hours ago by Nick Bostrom
Biological brains are unlikely to be the final stage of intelligence. Machines already have superhuman strength, speed and stamina and one day they will have superhuman intelligence. This is of course not certain to occur it is possible that we will develop some other dangerous technology first that destroys us, or otherwise fall victim to some existential risk.
But assuming that scientific and technological progress continues, human-level machine intelligence is very likely to be developed. And shortly thereafter, superintelligence.
Predicting how long it will take to develop such intelligent machines is difficult. Contrary to what some reviewers of my book seem to believe, I don't have any strong opinion about that matter. (It is as though the only two possible views somebody might hold about the future of artificial intelligence are "machines are stupid and will never live up to the hype!" and "machines are much further advanced than you imagined and true AI is just around the corner!").
A survey of leading researchers in AI suggests that there is a 50% probability that human-level machine intelligence will have been attained by 2050 (defined here as "one that can carry out most human professions at least as well as a typical human"). This doesn't seem entirely crazy. But one should place a lot of uncertainty on both sides of this: it could happen much sooner or very much later.
Exactly how we will get there is also still shrouded in mystery. There are several paths of development that should get there eventually, but we don't know which of them will get there first.
Biological inspiration
We do have an actual example of generally intelligent system the human brain and one obvious idea is to proceed by trying to work out how this system does the trick. A full understanding of the brain is a very long way off, but it might be possible to glean enough of the basic computational principles that the brain uses to enable programmers to adapt them for use in computers without undue worry about getting all the messy biological details right.
We already know a few things about the working of the human brain: it is a neural network, it learns through reinforcement learning, it has a hierarchical structure to deal with perceptions and so forth. Perhaps there are a few more basic principles that we still need to discover and that would then enable somebody to clobber together some form of "neuromorphic AI": one with elements cribbed from biology but implemented in a way that is not fully biologically realistic.
Pure mathematics
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Summer STEM Camp: Dr. Richard Sutton
Dr. Richard Sutton is here to talk with the STEM campers about Artificial Intelligence! Follow us on Twitter! https://twitter.com/VROCcanada Like us on Facebook! https://www.facebook.com/SummerS...
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Artificial Intelligence a threat to humanity?
The day machines become human, and humans become redundant is not unimaginable anymore. The Contrarian finds out how AI can change the very course of human existence for time to come. Watch...
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AS Francisco Herrera, an international model in the field of artificial intelligence
More videos at http://www.andalusianstories.com Francisco Herrera studied Mathematics, as it was what he liked most, but the specialized in Computer Science. He confesses that the first computer...
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AOL #39;s digital prophet, David Shing on programmatic creativity artificial intelligence in ads
AOL #39;s digital prophet, David Shing talks to The Drum about his views on how programmatic advertising can help drive creative engagement, while also offering ...
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Nick Bostrom: Superintelligence - Authors@Google
Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understandin...
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A I Profit Bot Review - Eric Stevens Artificial Intelligence Profit Bot - AIP Scam?
Artificial Intelligence Bot review - Is A I Profit Bot a scam? You can get all the facts here. http://BinaryOptionsProducts.com/AIP Too many new binary options robots require you to sign...
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A I Profit Bot Review - Eric Stevens Artificial Intelligence Profit Bot - AIP Scam? - Video
'Person of Interest' returns to CBS Tuesday night.
Image: Giovanni Rufino/Warner Bros. Entertainment Inc.
By Sandra Gonzalez2014-09-23 19:45:48 UTC
For three seasons, CBS's Person of Interest has tried to raise questions about who's watching us. But starting Tuesday, the show will shine a light on a subject producers think no one is keeping an eye on quite enough: artificial intelligence.
"Since the show initially premiered [in 2011], we used to get a lot of questions about [surveillance] and whether it was a real thing or not, and I think what initially seemed like a science fiction concept became factual and something people know is pervasive," said executive producer Greg Plageman, referring largely to the 2013 Edward Snowden leaks.
"Now that everyone understands that, we said, 'What's the next thing coming along that's interesting, the next big thing happening and a little bit under the table now but clearly imminent?' And that is artificial intelligence."
The subject has always been of interest to creator Jonathan Nolan, but in plotting Season 4, which debuts Tuesday night, it was hard to ignore the flurry of activity in the AI community, particularly Google's January acquisition of Deep Mind, the company's addition of leading AI researcher Ray Kurzweil, and Facebook's interest in the realm.
Forced to take on new identities created by Root, the team, including Harold Finch (Michael Emerson) tries to adapt to their new lives in the season premiere of 'Person of Interest.'
Image: Giovanni Rufino/Warner Bros. Entertainment Inc.
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'Person of Interest' Season 4 Will Tackle Big Questions About Artificial Intelligence
IBMs senior vice president says Watson could find success with commercial apps in wealth management, call centers, and medicine.
Michael Rhodin speaks with MIT Technology Reviews editor in chief Jason Pontin yesterday at EmTech.
Three years after its artificial-intelligence engine Watson made its high-profile win on Jeopardy!, IBM is adapting the technology as it seeks practical commercial uses, an IBM executive explained yesterday at EmTech, a conference organized by MIT Technology Review.
The original version of Watson was built around a question-and-answer format optimized for the game show, but that turned out to be just the first building block in an emerging artificial-intelligence system, said Mike Rhodin, senior vice president of the IBM Watson Group.
Rhodin said IBM is refining Watson to make it more adept at providing the correct answer to a specific question in a specific domainfor example, by learning from previous queries. Just as [computer operating system] platforms emerged in the 1960s, we are seeing the beginnings of that kind of a system emerge in the information age, he said.
In the past year, despite skepticism in some quarters, the company has announced it was making more investments in the Watson platform (see Facing Doubters, IBM Expands Plans for Watson). It has also opened the platform to app developers (see Trained on Jeopardy!, Watson Is Headed for Your Pocket).
Some results of that strategy are now emerging. In one recent competition run by IBM, a startup called Majestyk came up with an app that added Watson functionality to a stuffed animal so that it could converse with a child and give feedback to educatorspotentially revealing whether the child might have learning disabilities.
We never would have thought of it; we dont have that DNA, he said. It validated the idea that we needed to open up the platform and make it available to the startup marketplace.
Ultimately, Rhodin said, IBM will pursue a revenue-sharing model for any effort that reaches market.
The company also continues to pursue applications in the medical, financial, and legal sectors. Using Watson to examine thousands of documents could, for example, help doctors see different diagnoses in order of probability and rule out things they didnt think of, Rhodin said.
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Highlights from Prof. Jennifer Neville #39;s "Dawn or Doom" talk
Computer Science and Statistics Prof. Jennifer Neville discussed machine learning and artificial intelligence during her talk, "Are We Too Smart for Our Own Good: How Large-Scale Machine Learning...
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38 minutes ago by Catharina Jerkbrant
The computer programmes used in the field of artificial intelligence (AI) are highly specialised. They can for example fly airplanes, play chess or assemble cars in controlled industrial environments. However, a research team from Gothenburg, Sweden, has now been able to create an AI programme that can learn how to solve problems in many different areas. The programme is designed to imitate certain aspects of children's cognitive development.
Traditional AI programmes lack the versatility and adaptability of human intelligence. For example, they cannot come into a new home and cook, clean and do laundry.
In artificial general intelligence (AGI), which is a new field within AI, scientists try to create computer programmes with a generalised type of intelligence, enabling them to solve problems in vastly different areas. Gothenburg has a leading research team in this domain. In August, 'exceptional contributions to the AGI field' earned a team of researchers from the University of Gothenburg and Chalmers University of Technology the Kurzweil Prize for the second straight year.
No pre-existing knowledge
'We have developed a programme that can learn for example basic arithmetic, logic and grammar without any pre-existing knowledge,' says Claes Strannegrd, a member of the research team together with Abdul Rahim Nizamani and Ulf Persson.
The best example of general intelligence that we know of today is the human brain, and the scientists' strategy has been to imitate, at a very fundamental level, how children develop intelligence. Children can learn a wide range of things. They build new knowledge based on previous knowledge and they can use their total knowledge to draw new conclusions. This is exactly what the scientists wanted their programme to be able to do.
Children learn based on experience
'We postulate that children learn everything based on experiences and that they are always looking for general patterns,' says Strannegrd.
A child who for example is learning multiplication and who knows that 2 x 0 = 0 and 3 x 0 = 0 can identify a pattern and conclude that also 17 x 0 = 0. However, sometimes this method backfires. If the child knows that 0 x 0 = 0 and 1 x 1 = 1, he or she can incorrectly conclude that 2 x 2 = 2. As soon as the child realises that a certain pattern can lead to incorrect conclusions, he or she can simply stop applying it.
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Seattle, WA (PRWEB) September 23, 2014
Utrip, a free travel planning platform that creates personalized itineraries in minutes, announced today it has launched its first five U.S. destinations: Seattle, Portland, San Francisco, Los Angeles, and Dallas. Visitors to these cities are now able to quickly create personalized itineraries, based on their interests and budget. Once an itinerary is created, Utrips companion mobile app allows travelers to view their itinerary and receive additional personalized recommendations while on the go.
When researching a new destination, Utrip identifies local area experts, who help curate each citys offerings and create featured trips highlighting their favorite venues. For the Seattle launch, Tom Douglas, celebrated chef and author, has created several culinary-oriented trips, including Eat Your Way Through Seattle, and Seafood Lovers Seattle. For San Francisco, Mark Dommen, of Michelin starred One Market, has created Culinary San Francisco for Bay Area travelers. Neiman Marcuss Fashion Director Ken Downing has created the Dallas Shopping and Art trip featuring his favorite Big D hotspots.
I love being able to help promote Seattle to travelers worldwide. Utrip makes it easy for travelers to experience the destination highlights that most interest them, be it food, art or history. Just like a culinary experience, every palate is different, and Utrip is all about personalizing travel for their users, said Tom Douglas, James Beard award-winning chef and owner of many of Seattles finest restaurants.
The Utrip platform uses a travelers interests, preferences and budget to create complete, personalized itineraries, including sites, activities and restaurant recommendations. Earlier this month, Utrip released a white-label version of its travel planning platform, Utrip PRO, which allows DMOs and hospitality groups to offer personalized travel planning on their own sites.
We are so excited to be unveiling U.S. destinations to answer the demand for, and enthusiasm from, our existing and new customers, said Gilad Berenstein, chief executive officer and founder of Utrip. Thousands of European travelers have been able to simplify and personalize their travel planning with Utrip, and now it is time to bring our platform to the U.S. market.
About Utrip Utrip is a free travel planning platform that brings together the best in artificial intelligence and human experience, making it easy for travelers to create their perfect trip. Founded in Seattle, WA in 2011, Utrips predictive technology works on a vast travel database that has been curated by local experts. Once a traveler indicates their interests and budget, Utrips algorithm sorts through millions of combinations of must-see sites, activities, and restaurants recommendations to deliver personalized itinerariesin minutes. Travelers may then book lodging and share their itineraries with friends. Utrips companion mobile app provides access to itineraries, directions and personalized recommendations on the go. Utrip PRO, the white-labeled version, allows businesses to offer personalized travel planning on their sites. To learn more about Utrip or to plan your next adventure, visit Utrip.com.
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