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Mechanisation of Thought Processes: Artificial Intelligence in the 21st Century – Video

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Mechanisation of Thought Processes: Artificial Intelligence in the 21st Century
Professor Murray Shanahan gives his talk titled #39;Mechanisation of Thought Processes: Artificial Intelligence in the 21st Century #39;. Recorded at NPL on 20th Ju...

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Mechanisation of Thought Processes: Artificial Intelligence in the 21st Century - Video

The Artificial Intelligence Company You Should Watch

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Boris Sofman is the cofounder and CEO of Anki, a startup that had been in stealth for five years until it unveiled its first product with a bang as the headline demo at this years WWDC. Before founding Anki, Boris worked at iRobot and earned his sci-fi creds by getting a PhD from the Robotics Institute of Carnegie Mellon University. Here, he talks to Michael Grothaus about the future of AI.

Lets get this one out of the way first, because its every developers dream. You were chosen to be the opening demo at this years WWDC. How did that feel?

It was such an exciting experience! And an honor as well. We'd been working on Anki for over five years without publicly announcing anything, so to finally be able to share with the world in such a way was simply incredible. We'd actually been working with Apple for a while already regarding selling Anki Drive in Apple stores. There really seemed to be an excitement at Apple not just around Anki Drive, but how we're using their devices in ways no one has used them before.

What is AI exactly?

AI is the science of using data to allow systems to behave with intelligence and with a purpose. This can be purely in software (a video game character, a chess program, voice recognition), but the most exciting application for us is when you combine it with robotics to make physical things behave with a level of intelligence never before possible.

Will any computers ever have true intelligence that operates at a human level?

The core approach to any AI problem is to represent the structure and constraints of the problem in a way that is computable. This is harder for some problems than others, and as a result there are areas where AI is already superior to a human, but others where it will be a long time before AI can come close to a human's capabilities. We're nowhere close to a general-purpose AI that can do everything a human can, but we're increasingly capable of addressing complex challenges and we're knocking off problems that were previously untouchable.

And your company, Anki, is working on some of those challenges?

Yes. Anki is an artificial intelligence and robotics company that is taking these technologies out of the lab and into peoples everyday lives. With these technologies, we're able to program physical objects to be intelligent, adapt and interact with their surroundings, and to surprise people with what is possible. Consumers have never before fully benefited from these technologies, which promise to make all aspects of our lives more fun, more useful, and more efficient. Anki Drive, which is a video game programmed for the real world, is the first step for us and demonstrates whats possible with Anki technology.

You made some breakthroughs with Anki Drive. Tell me about them.

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The Artificial Intelligence Company You Should Watch

Magisto Upgrades Artificial Intelligence Algorithm Introduces Emotion Sense Technology

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NEW YORK, June 20, 2013 /PRNewswire/ -- CE Week --Today, Magisto introduced a new component of its patent-pending artificial intelligence technology that furthers its mission to forever improve the personal movie-making process: helping a movie 'make itself.'

Based on the company's proprietary artificial intelligence algorithm, Magisto's Emotion Sense Technology (EST) is able to unlock the emotional power of video editing and production from any smartphone.

The camera phone first made its commercial debut in the mid 1990s. Today with more than a billion smartphones on the planet, myriad devices can shoot and disseminate video in increasingly sophisticated ways. Surprisingly, the actual process of editing and producing movies has changed relatively little since its inception in the early 1900s.

"After more than 100 years,video is fast becoming the mostpopular mediumfor chronicling everyday experiences," said Oren Boiman, CEO and founder of Magisto. "Since few of us are born directors or movie producers, making a movie that conveysthe true feelings of an experience isreally hard.With Magisto'sEmotion Sense Technology, ourusersmovies make themselves, breaking down an extremely sophisticated process into a few clicks, and turningaveragevideo into beautiful stories."

TheMagistoalgorithmgeneratesa deep understanding of what's actually occurring within the scenes of a video. Using that understandingand minimal input from the user,Magisto adjusts its decision making parameters,altering edits, time warpingactions,featuring audioand visualhighlightsand ultimatelydefiningthe arc of astoryline. It thenascribestheselectedmusic and graphical theme for capturing and sharing the emotion in an instant;as easy as snapping a photo.

Over a six-month beta test, which included over 60 million videos, Magisto EST has become smarter, faster and more intuitive in analyzing, identifying and replicating a user's intended mood. Magisto has been able to refine its artificial intelligence in part because it relies on relatively long-form video and multiple photos, which contain lots of information and inferred guidelines for movie making, unlike shorter, disposable, video that delivers one-dimensional vignettes from a single point in time.

In a recent Magisto poll, 81.8 percent of users agree that their recent Magisto videos match the emotion they intended to convey. Examples of videos that have been created with different mood filters and a video news release can be found here in the Magisto VNR.

Kicking off summer, Magisto also announced that it has added two new themes to its "emotion sensing" catalogue. These themes can assist creators in conveying the appropriate mood in their video stories. "Summer Party" and "Fourth of July" will help users set a hot and carefree tone for the summer. Now Magisto users can create movies from pictures and videos and accurately convey the emotions they feel.

About MagistoDriven by artificial intelligence and simple user experience, Magisto is a cloud based service for creating and sharing professional quality personal movies. It automatically selects the most compelling moments and, like an expert video editor, weaves them together to convey a story with customized styles and music. Magisto can be used across iOS, Android and the Web, and is the highest-rated video creation app in the Google Play and iOS App Stores. More information is available at http://www.magisto.com/how-it-works

The company is funded by Horizons Ventures and Magma Venture Partner and maintains its headquarters in Tel Aviv, Israel with offices in New York and California. To learn more, visithttp://www.magisto.com,

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Magisto Upgrades Artificial Intelligence Algorithm Introduces Emotion Sense Technology

Grand Challenge Dilemma: Synthetic Life; Robotics and Artificial Intelligence – Video

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Grand Challenge Dilemma: Synthetic Life; Robotics and Artificial Intelligence
Our group Grand Challenge output on "The creation of new life forms - a dangerous future or the way forward for humanity?" dilemma. Synthetic Life: Robotics ...

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Grand Challenge Dilemma: Synthetic Life; Robotics and Artificial Intelligence - Video

GE wants to use artificial intelligence to predict the future of hospitals

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Jun. 17, 2013 - 3:18 PM PDT Jun. 17, 2013 - 3:18 PM PDT

Around the world, the health care system is rife with inefficiencies, and General Electric thinks it can help solve the problem using data. Only its not talking about bureaucrats looking at reports: GE has built an artificial intelligence system called Corvix that uses historical data to predict the future, including everything from how diseases will spread to the cities where hospitals will be needed the most.

It might sound futuristic, but the techniques behind Corvix have actually been around for a while. The platform uses agent-based modeling to build, essentially, a reasonable facsimile of some sort of complex system and then simulate its evolution over time. The agents represent the atomic units of those systems, such as individual people in the case of human populations or perhaps cells in the case of a biological simulation. They act according to a set of rules in any given situation, which is how the models are able to keep the simulations progressing.

However, thanks to the advent of big data, GE Healthcare Chief Economist Mitch Higashi thinks the time is right for a platform like Corvix to provide some real value to real-world decisions. Theres enough raw computing power, machine intelligence and data-modeling expertise to start doing fast, accurate simulations over very large and complicated datasets. Also, advances in user-interface design have made these types of models more consumable: GEs Corvix uses a game-like UI that any 10-year-old can figure out how to use in 10 minutes, Higashi said.

The first live run for Corvix happened in the state of Andhra Pradesh in India, where the system simulated a population of 80 million people in order to figure out where to build hospitals and medical training centers over the coming years. The GE team used two census datasets and one health care survey in order to build what Higashi calls a reasonable representation of 80 million people, as well as a map of Indias existing hospital and energy grid. Health care analysts studying the problem of where to build can drag a new hospital over an area on the map and see how the situation plays out, Higashi explained.

The original plan, said Chaitanya Sarawate, GEs head of health economics and reimbursement for India, was for the Public Health Foundation of India to invest $2 billion building training institutions in different cities over the next five years. Corvix suggested some possible changes in location of those institutions, including placing two institutions in the countrys most-populous state, Uttar Pradesh, instead of just one as was originally planned. The advice is part of a report from the foundation to Indias Minstry of Health, which will make the ultimate decision.

Developing countries such as India are great places to use this type of technology, Higashi explained, because they are doing greenfield investing in areas such as health infrastructure and a lot of good can happen if they get it right off the bat. The problem, Sarawate noted, is that they often lack detailed data that can help governments make objective comparisons thats the kind of stuff a company like GE, in this case, can track down and try to feed into a model that takes into account its relative importance.

In fact, GE is already working on projects with other governments in India, as well as with private organizations and governments in other developing countries.

GE has bigger plans for Corvix, though, including deployments in countries like the United States, and possibly into different areas within health care and some outside of health care. Ruslan Horblyuk, director of health economics for GE Healthcare, said deploying Corvix in developed economies will probably be a bit easier because theres often more data available to choose from when building the models.

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GE wants to use artificial intelligence to predict the future of hospitals

Computerized brain made of GPUs could be the future of artificial intelligence

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For decades computer scientists have been struggling to design an artificial intelligence sophisticated enough that it could pass for a living being. The fruits of that labor so far are snarky chatbots and systems that can crunch large amounts of data and spit out factoids. Google began working on a new method of replicating neural networks using 1,000 computers tied together. Now, one of the researchers that helped Google do it has laid out the framework for an even better brain model that costs a fraction as much. The key to true AI might be the GPU.

Traditional artificial intelligence computing has relied on bundling as many processors together as possible. With increase throughput, researchers believed the problem of machine thinking could eventually be brute-forced. It now seems that approach will only get so far, hence the project at Google with so-called Deep Learning. The modest goal was to get a system that learned what a cat looked like, and was able to spot them in YouTube videos. On this count, Google succeeded.

A Stanford researcher by the name of Andrew Ng worked with Google on the cat project, but was dismayed at the cost of the system. Ng believed if AI was to take off, it needed to come down in price. He recently published a paper laying out his vision for a cheaper AI test bed based on GPUs instead of CPUs. This isnt the first use of GPU computation, but it might be one of the most ambitious. While CPUs are easy to network and blend, GPUs are much more temperamental.

By utilizing GPUs as the muscle behind an AI program, Ng claims first-generation rigs could cost as little as $20,000. Thats definitely out of reach of the consumer market, but well within the budgets of many computer science researchers. The original Google Deep Learning system cost over $1 million. The goal here is to do for AI research what Apple and Microsoft did for the personal computer.

To test his hypothesis about GPU-driven Deep Learning, Ng and his team built a larger version of the proposed platform costing about $100,000. It utilized 64 Nvidia GTX 680 GPUs on 16 computers. It was able to accomplish the same cat-spotting tasks the Google system, which needed 1,000 computers to operate.

Deep Learning might be the best route to a true AI system if scientists are able to harmonize GPU computing. Ng and his team are working on custom Nvidia CUDA code that makes the magic happen by efficiently combining resources and allowing for fast task switching among the connected graphics processors.

Ng has not yet decided if the specialized software and hardware designed to test his hypothesis will be open source. Even if it isnt, the paper explains some of the algorithms and techniques involved. Other AI researchers are sure to follow up if only to prove Ng wrong.

Now read:IBM takes a step towards building artificial semiconductor synapses

Research paper: Deep learning with COTS HPC systems(PDF)

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Computerized brain made of GPUs could be the future of artificial intelligence

Artificial Intelligence Platform Parakweet Raises $2 Million in Angel Funding

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San Francisco (PRWEB) June 18, 2013

Parakweet, Inc. today announced it secured $2 million in funding. The company has developed a proprietary artificial intelligence platform that uses social media- specific natural language processing (NLP) to detect and extract meaning from millions of unstructured conversations and accurately identify consumer behavior, intent and sentiment. Parakweet will use the funds for new product innovation and continued development of BookVibe, its recently launched book discovery engine.

The funding was led by a group of high-profile investors including Scott Banister, an early investor in PayPal, Zappos and Powerset; Alan Braverman, co-founder of Yammer and Eventbrite; David Jeske, former Director of Engineering at Google; and other angel investors and entrepreneurs.

Parakweets platform is fine-tuned for specific vertical markets, in order to best extract meaning from short, unstructured social media updates. BookVibe, Parakweets consumer-facing book recommendations product, scans a users social graph and extracts tweets that are actually about books with 96 percent accuracy. It also detects and distinguishes the persons sentiment about the booknot the overall tweet. For example, if a tweet reads: "Im reading War and Peace since the weather is lousy," BookVibe understands that lousy refers to the weather, not the book. Some of the behaviors BookVibe identifies include "intent to read," "read" and "recommend." Furthermore, the Parakweet platform does not require users to join or recreate yet another social network.

"We started Parakweet to distill actionable insights from the unstructured language of social media," said CEO and co-founder Ramesh Haridas. "Today, were providing consumers with book recommendations based on a users personal interests and the interests and affinities of the people they follow. Our platform also allows companies to tap into the behavioral signals consumers are generating across social media and uncover actionable and competitive insights."

Added Haridas, "Were inspired to have the backing and support of such a notable group of angel investors and tech entrepreneurs. With this funding, weve taken a decisive step to transform how meaning and understanding is derived from massive amounts of social media, which often includes slang, abbreviations and no punctuationsomething that Parakweet is using natural language processing to solve."

Investor Scott Banister added, "Parakweets disruptive technology gets under the hood of social media language and captures human behaviors with remarkable accuracy. Books and movies are just the tip of the iceberg for applications of Parakweets natural language processing engine."

Parakweet was founded by a team of successful entrepreneurs and computer scientists including serial entrepreneur Ramesh Haridas; machine learning and search technologist Kiam Choo; and artificial intelligence software architect Ilmars Poikans.

About Parakweet Founded in 2010 and headquartered in San Francisco, Parakweet is a platform that offers product recommendations to consumers and social media analytics and metadata to global media companies. Parakweets proprietary artificial intelligence platform uses natural language processing technology to extract meaning from unstructured social content and accurately identify associated behaviors, intent and sentiment. Parakweets first product BookVibe is a social discovery and book recommendation engine for consumers launched in 2013. For more information, please visit http://www.parakweet.com.

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Artificial Intelligence Platform Parakweet Raises $2 Million in Angel Funding

Home – Stock Assault 2.0™ – Artificial Intelligence Stock Market – Video

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