Data Science: Machine Learning algorithms in Matlab

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In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.


An Artificial Intelligence Roadmap For Contact Centers

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There are many innovations that are rapidly changing the landscape of the contact center. From being able to offer an omnichannel customer experience across multiple channels to internet-enabled devices connecting directly to contact centers to provide proactive service, there is no doubt that the days of the single channel call center are long gone. One of the most interesting innovations that is being increasingly discussed by visionaries and industry experts is artificial intelligence. While there are multiple definitions for artificial intelligence or "AI," the term is most commonly applied when a Machine uses leading-edge technology to perform or mimic "cognitive" functions that are intuitive within the human brain, such as problem-solving and learning. Some of the most recognizable current forms of AI are self-driving cars and computers that can beat even professional players in chess.


Improve Automation in the Enterprise with Augmented Intelligence

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Many are claiming that we are in the era of automation. Discussions around the self-driving car are heating up, IBM Watson is making headway, and the Internet of Things is making quite the splash in all aspects of our lives, from the smart home to smart cities. But what is automation's role in the workplace? A recent report from McKinsey and Company says that nearly half of work activities "could be automated using already demonstrated technology." With more businesses looking to adopt advanced tools that increase efficiency, the real value is still in the hands of humans, which hold the key in the form of decision making.


The Secret to AI Could be Little-Known Transfer Learning - InformationWeek

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Consumers have spoken, artificial intelligence is a profitable industry. From Amazon to Google to Apple, major tech companies have made inroads, crafting intelligent software -- housed in sleek, accessible hardware -- that has drawn massive customer attention. This trend is set to soon move out of home devices, like Echo and Google Home, and onto the streets, where self-driving cars leverage major breakthroughs in computer vision so passengers can ride easy, knowing their vehicles will "see" and react to objects and road signs in real time without their input. In fact, cars with these features are already popular with consumers, and by 2020 10 million cars with self-driving attributes will be on roadways. But while there are plenty of ways for consumers to leverage AI, enterprises are asking themselves how they can get in on this wave of innovation.


How Google is using big data to protect the environment

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For many people, Google is simply the gateway to a vast archive of facts and memories. For those who pay closer attention to its business dealings, the company also invests billions to find new ways to use the power of computers: it's developing robots, virtual reality gear and self-driving cars. Remember all the hubbub about Google Glass? Google has been using the same approach in sustainability – spreading its wealth in a variety of projects to cut its waste and carbon footprint, initiatives which may one day generate profits. During the SXSW Eco conference this week, I caught up with Google's sustainability officer, Kate Brandt, to find out more.