Ai-Applied - Artificial Intelligence and Virtual Assistant Specialists

Is 2014 the New Dawn of AI?

Is 2014 the New Dawn of AI?

Artificial Intelligence (AI) can deliver very real operational benefits for all businesses. Step change improvements to customer service, greater insight into customer behaviour and reductions in cost to serve are just a few of the benefits that are deliverable today.

Perhaps a good measure of just how serious business leaders should consider AI has been demonstrated on a global scale with the recent land grab of AI Companies by some of the world’s leading tech companies.

The AI technology tide is rising fast in 2014 with some tectonic investments and movements in the industry, if you didn’t get a chance to read about some of these high profile developments in recent months, here’s another chance.

Our favourite headline round-up to date is:

  • Google acquire the UK based AI business Deep Mind for $400 million
  • IBM launch The IBM Watson Group to focus on cognitive applications and services
  • The California based Vicarious FPC get billionaire funding from the industries elite
  • Facebook hire prominent NYU professor Yann LeCun as the new director of their AI lab
Deepmind
Google

In January, Google acquired The UK based start-up AI Company called Deep Mind for a reported $500 million. Google’s aquisition of DeepMind will help it compete against other major tech companies as they all try to gain business advantages by focusing on artificial intelligence and deep learning capability. DeepMind was founded by neuroscientist Demis Hassabis, a former child prodigy in chess, Shane Legg, and Mustafa Suleyman. Skype and Kazaa developer Jaan Tallin is an investor.

This is the latest move by Google to fill out its roster of artificial intelligence experts and, according to Re/code, the acquisition was reportedly led by Google CEO Larry Page. If all three of DeepMind’s founders work for Google, they will join inventor, entrepreneur, author, and futurist Ray Kurzweil, who was hired in 2012 as a director of engineering focused on machine learning and language processing.

Kurzweil has said that he wants to build a search engine so advanced that it could act like a “cybernetic friend.”

After Google acquired Nest earlier in January, critics voiced concerns about how much customer data the smart device maker would share. The company’s purchase of Boston Dynamics in December 2013 also sparked confusion about why a search company needs a robotics maker.

Google has responded by agreeing to establish an ethics board to ensure DeepMind’s artificial intelligence technology isn’t abused.

Watson
IBM

Nearly three years after its triumph on the television quiz show Jeopardy! IBM has advanced Watson from a game playing innovation into a commercial technology. Now delivered from the cloud and able to power new consumer and enterprise services and apps, Watson is 24 times faster, smarter with a 2,400 percent improvement in performance, and 90 percent smaller – IBM has shrunk Watson from the size of a master bedroom to three stacked pizza boxes.

Named after IBM founder Thomas J. Watson, IBM Watson was developed in IBM’s Research labs. Using natural language processing and analytics, Watson processes information akin to how people think, representing a major shift in an organization’s ability to quickly analyze, understand and respond to Big Data. Watson’s ability to answer complex questions posed in natural language with speed, accuracy and confidence is transforming decision making across a variety of industries.

In January, 2014 IBM announced the establishment of a new Watson business unit dedicated to the development and commercialization of cognitive computing innovations: The IBM Watson Group. IBM will invest more than $1 billion into the Watson Group, a cross-company unit focusing on development and research and bringing cognitive applications and services to market. This will include $100 million available for venture investments to support IBM’s recently launched Watson Developer Cloud, opening up the Watson platform to third party software application providers that aim to build a new class of cognitive apps powered by Watson.

Vicarious
Vicarious

Elon Musk made the electric car cool, Mark Zuckerberg created Facebook, Ashton Kutcher portrayed Apple founder Steve Jobs in a movie and in March this year the three joined together in a $40 million investment in Vicarious FPC, a secretive artificial-intelligence company based in California. The funding round; the second major infusion of capital for the company in two years, is the latest sign of life in artificial intelligence.

Vicarious has an ambitious goal: Replicating the neocortex, the part of the brain that sees, controls the body, understands language and does math. Translate the neocortex into computer code and “you have a computer that thinks like a person,” says Vicarious co-founder Scott Phoenix. “Except it doesn’t have to eat or sleep.”

Vicarious’s backers include a venture fund run by PayPal founder and Facebook investor Peter Thiel, which was among those who invested $1.2 million in 2010. In 2012, a new group of investors, including Facebook co-founder Dustin Moskovitz, injected $15 million. Kutcher’s investment comes via his fund, “A-Grade Investments.”

Yan
Facebook

By teaching a computer to think, Facebook hopes to better understand how its users do too. So just before Christmas the company announced that one of the world’s leading deep learning and machine learning scientists, NYU’s Professor Yann LeCun, will lead its new artificial intelligence laboratory.

MIT Technology Review first reported that Facebook would launch an Artificial Intelligence lab back in September, but now it has something of a celebrity scientist at its helm. Facebook’s AI research will be split across its Menlo Park headquarters, London office, and a new AI lab built just a block from NYU’s campus in Manhattan.

LeCun has been pioneering artificial intelligence breakthroughs since the 1980s when he developed an early version of the “back-propagation algorithm” that became the top way to train artificial neural networks. He went on to work for AT&T Bell Laboratories where he created the “convolutional network model” that mimics the visual cortex of living beings to create a pattern recognition system for machines. This model was used for optical character recognition and handwriting recognition that powered how many banks read checks in the late 1990s and early 2000s.

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