Lars Hard of Beta News recently wrote, “Artificial intelligence (AI) has become a bit of a buzzword among technology professionals (and even within the mainstream public) but truthfully, most people do not know how it works or how it is already being integrated within leading enterprise businesses. AI for businesses is today mostly made up of machine learning, wherein algorithms are applied in order to teach systems to learn from data to automate and optimize processes and predict outcomes and gain insights. This simplifies, scales and even introduces new important processes and solutions for complex business problems as machine learning applications learn and improve over time. From medical diagnostics systems, search and recommendation engines, robotics, risk management systems, to security systems, in the future nearly everything connected to the internet will use a form of a machine learning algorithm in order to bring value.” Read more
Posts Tagged ‘AI’
Katherine Noyes of Tech News World reports, “The inventors of Apple’s Siri personal assistant have launched an independent effort that could make their first offspring look kind of dumb. Billed by its creators as ‘the global brain,’ Viv aims to radically simplify the world by providing an intelligent interface to everything. ‘They are trying to abstract Siri’s [natural-language processing] interface so you could apply it into other applications and domains,’ Raj Singh, CEO and founder of Tempo AI, told TechNewsWorld. ‘For example, what if I wanted to integrate a Siri-like interface into the Yelp app or the Expedia app?’ Currently, ‘there isn’t a good facility to do this,’ he said. Read more
Will a robot take your job in the future? Given their increasing sophistication, it’s not surprising if the topic is of growing concerns to more people. The Semantic Web Blog has reported, for example, on robots that are learning to do tasks in response to humans’ natural language, and a talking robot on a space journey, covering the gamut from personal assistant to astronaut.
The Pew Research Center released a report last week entitled AI, Robotics and the Future of Jobs. It raises the question of whether advances in robotics and artificial intelligence will displace more jobs than they create by 2025, but the experts the report draws upon for their opinions haven’t reached a consensus on that point yet. Forty-eight percent believe both blue- and white-collar worker jobs are at risk, and that the future will see greater income inequality, more permanent unemployment and greater social disruption as a result. The other 52 percent see a lot of jobs that currently require real people will be taken over by robots or digital agents, as well – but with the happier prospect that humans will figure out new jobs and industries to replace the livings they can no longer make with their own brains or hands.
A recent press release revealed that, “There are signs indicating that Chinese Internet users might be the very first group of people to truly reap the benefits of artificial intelligence. The Singularity Is Near: When Humans Transcend Biology, written by Ray Kurzweil, painted us a picture of artificial intelligence. Kurzweil describes his law of accelerating returns which predicts an exponential increase in technologies; in the book he says this will lead to a technological singularity in the year 2045, a point where progress is so rapid it outstrips humans’ ability to comprehend it. Baidu, the leading Chinese search service provider, recently announced their ground-breaking Light App (a modified kind of web app), the Baidu Exam-Info Master. Using the artificial intelligence of their search engine, Baidu seeks to offer some practical help to high school seniors when it comes to applying for their dream college after the National College Entrance Examination. This service has soon become wildly popular among users, and may grow into a key motivation for Baidu to duplicate this kind of method into a far broader area.”
An article written by Eugene Joseph of Gamasutra reveals that, “Bot Colony is an episodic single player adventure game that we launched on Steam’s Early Access on June 17. It has the distinction of being the first game that integrates unrestricted English dialogue into the game experience. While the Bot Colony Natural Language Understanding (NLU) pipeline cannot yet handle everything a player throws at it, it is able to understand enough that cooperative players can complete the game’s episodes (versions of the first two are available now on Steam Early Access). Language understanding is not limited to the minimum required to play the game – we actually hope that players will explore the boundaries of AI understanding and probe just how much a Bot Colony robot understands.”
[Editor's Note: This guest article comes to us from Dr. Nathan Wilson, CTO of Nara. ]
There once was a time when the busiest and greatest minds –the Jeffersons, Hemingways and Darwins – would have time in their day for long walks, communion with nature, and leisurely handwritten correspondence. Today we awaken each day to an immediate cacophony of emails, tweets, websites and apps that are too numerous to navigate with full consciousness. Swimming in wires, pixels, data bits, and windows with endless tabs is toxic to you and to me, and the problem continues to escalate.
How do you connect to this teeming network without electrocuting your brain? “Filtering” is a simple, but ultimately blinding, approach that shields us from important swaths of knowledge. “Forgetting faster” is potentially a valid solution, but also underserves our mindfulness.
A History of Attempted Solutions So Far: How have we tried to solve information glut so far, and why is each solution inadequate?
Phase 1 – The Web as a Linnaean Taxonomy (1994-2000)
The first method to deal with our information explosion came in “Web 1.0” when portals like Yahoo! arose to elegantly categorize information that you could explore at your leisure. For instance, one could find information on the New England Patriots by following a trail of breadcrumbs from “Sports” to “Football” to “AFC East” and finally “New England Patriots” where you were presented with a list of topical websites.
Previously, it was reported on SemanticWeb.com that Google had acquired Nest Labs. Steve Lohr of The New York Times recently opined that: “Google did not pay $3.2 billion for Nest Labs this year just because it designed a smart thermostat that has redefined that humble household device. No, Google also bought into the vision of Nest’s founders, Tony Fadell and Matt Rogers, a pair of prominent Apple alumni, that the Nest thermostat is one step toward what they call the conscious home. That means a home brimming with artificial intelligence, whose devices learn about and adapt to its human occupants, for greater energy savings, convenience and security. Last Friday, Nest moved to broaden its reach in the home, buying a fast-growing maker of Internet-connected video cameras, DropCam, for $555 million. And on Tuesday, Nest is expected to announce a software strategy backed by manufacturing partners and a venture fund from Google Ventures and Kleiner Perkins Caufield & Byers.”
The author added: “Nest’s is the third high-profile announcement this month about software to link devices in the home in a network known as the consumer Internet of Things. At its Worldwide Developers Conference this month, Apple introduced HomeKit, its technology for linking and controlling smart home devices. HomeKit uses the iOS operating system, the software engine of iPhones and iPads. Quirky, a start-up that manufactures and sells products based on crowdsourced ideas, on Monday announced the creation of a separate software company, Wink. Its initiative has attracted the backing of a major retailer, Home Depot, and manufacturers like General Electric, Honeywell and Philips.
Read more here.
Photo courtesy: flickr/jbritton
Signe Brewster of Gigaom recently wrote, “In 2012, Google hired Ray Kurzweil to build a computer capable of thinking as powerfully as a human. It would require at least one hundred trillion calculations per second — a feat already accomplished by the fastest supercomputers in existence. The more difficult challenge is creating a computer that has a hierarchy similar to the human brain. At the Google I/O conference Wednesday, Kurzweil described how the brain is made up of a series of increasingly more abstract parts. The most abstract — which allows us to judge if something is good or bad, intelligent or unintelligent — is an area that has been difficult to replicate with a computer. A computer can calculate 10 x 20 or tell the difference between a person and a table, but it can’t judge if a person is kind or mean. To get there, humans will need to build computers that can build abstract consciousness from a more concrete level. Humans will program them to recognize patterns, and then from those patterns they will need to be smart enough to learn to understand more.”
Brandon Bailey of San Jose Mercury News reports, “The latest Silicon Valley arms race is a contest to build the best artificial brains. Facebook, Google and other leading tech companies are jockeying to hire top scientists in the field of artificial intelligence, while spending heavily on a quest to make computers think more like people. They’re not building humanoid robots — not yet, anyway. But a number of tech giants and startups are trying to build computer systems that understand what you want, perhaps before you knew you wanted it. ‘It’s important to position yourself in this market for the next decade,’ said Yann LeCunn, a leading New York University researcher hired to run Facebook’s new A.I. division in December. ‘A lot is riding on artificial intelligence and content analysis, and on being smarter about how people and computers interact’.” Read more
Hong Kong, Hong Kong (PRWEB) April 03, 2014–Ipselex, until now a secretive Hong Kong artificial intelligence company, today announced the launch of its web platform. The platform offers API-like access to a brain in the cloud that has taught itself to understand and make predictions about patents and patent applications.
Combining state of the art natural language processing with neural network technology designed to simulate a human brain, the AI at the core of Ipselex has learned what makes a good patent through a mix of self-study and guidance from an experienced patent attorney. It can, for example, analyze products for infringement and, in certain industry sectors, estimate the likelihood that a given patent application will be granted. Read more
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