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AI--Changing what's Possible for Business - IT Peer Network

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This week at the Intel Shift Conference in New York, I had the opportunity to listen to my colleague Amir Khosrowshahi, CTO of the Intel AI Products group, speak to a gathering of business executives about the transformative impacts of AI. Amir explained how artificial intelligence (AI) can change what organizations do and how they do it, creating new business opportunities. Every company is in some phase of their AI adoption course: evaluating and understanding the opportunities, testing AI use cases and its outcome on their business, or fully integrating AI systems that are increasingly driving business metrics. AI concepts have been around for more than 60 years, but we now have the technology to make AI a reality. AI is predicated on the simple idea that with the right training a computer can simulate human decision making.


When Artificial Intelligence Becomes Commonplace

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AI and computer learning is quickly gaining use, so what happens when AI becomes commonplace? Before we dive into this it is important to understand what AI can and can't do today and what aspect of it is already common. Computer learning is a subset of AI, but the two are often discussed together or interchanged. Computer learning is a method where a computer is trained on a set of data and then uses that training to learn a task. Facial feature recognition is a common computer learning task where the computer is trained to recognize the various features (eyes, lips, nose and mouth) of anyone's face.


Is Facebook Building An Autonomous Car?

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Facebook seems to have a strategy of leveraging its capabilities in social marketing, AR & VR and interestingly, who would have thought of it, leveraging its advanced AI and deep learning capabilities to support the development of autonomous vehicles. Potential car buyers spend anywhere between 30 to 50 minutes every day on Facebook and that has helped the social business make significant inroads in digital prospecting and omni-channel commerce. Facebook believes that car companies are focusing more on the connected car, rather than the connected consumer. With every new customer car buying journey now beginning online, it is possible through Facebook's huge data on a customer's social behavior, to make that experience personalized and completely customized.


Deep Learning – what is it? Why does it matter?

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This is why in the image you can see that both models result in some errors with reds in the blue zone and blues in the red zone. The theory is that the more hidden layers you have the more you can isolate specific regions of data to classify things. GPU based processing allows for parallel execution, on large numbers of relatively cheap processors, especially when training an artificial neural network with many hidden layers and a lot of input data. That means having them able to understand images, understand speech, understand text etc.


The subtle, invisible AI that big Indian start-ups are using to get to know consumers better

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So, ShopClues plans to use advanced technologies to make it easier for shoppers to find the right size when buying clothes online, according to Utkarsh Biradar, vice-president of product at the company. It's also applying these technologies to help advertisers expand their reach effectively, using machine learning to identify "lookalike" targets that are similar to existing users as well as figuring out what kinds of ads users don't want to see. Ola, one of India's leading ride-hailing apps, is using data science and machine learning to track traffic, improve customer experience, understand driver habits and extend the life of a vehicle. Machine learning models log each customer's gender, brand affinity, store affinity, price preference, frequency, volume of purchases, and more, which become more accurate as the company collects more data.


The subtle, invisible AI that Indian unicorns have made a part of consumers' lives

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So, ShopClues plans to use advanced technologies to make it easier for shoppers to find the right size when buying clothes online, according to Utkarsh Biradar, vice-president of product at the company. It's also applying these technologies to help advertisers expand their reach effectively, using machine learning to identify "lookalike" targets that are similar to existing users as well as figuring out what kinds of ads users don't want to see. Ola, one of India's leading ride-hailing apps, is using data science and machine learning to track traffic, improve customer experience, understand driver habits and extend the life of a vehicle. Machine learning models log each customer's gender, brand affinity, store affinity, price preference, frequency, volume of purchases, and more, which become more accurate as the company collects more data.


Uber Adds AI Labs Division, Acquires Machine Learning Startup

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Uber has taken another definitive step toward eliminating human drivers from its fleet of vehicles. This week, the ride service pioneer created a research division, known as AI Labs, while simultaneously acquiring machine learning startup Geometric Intelligence for an undisclosed sum. The new lab will become the incubator for products and technology that Uber can use to further automate the operation of its vehicles and service. The new lab will be initially populated by the 15 employees that made up Geometric Intelligence, a New York-based startup that assembled a team of young AI university researchers and enthusiasts. Heading the new Uber lab will be Geometric Intelligence founding CEO Gary Markus, a professor at NYU.


Global Bigdata Conference

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Over the past few years, the term "deep learning" has firmly worked its way into business language when the conversation is about Artificial Intelligence (AI), Big Data and analytics. And with good reason – it is an approach to AI which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries. Deep Learning is used by Google in its voice and image recognition algorithms, by Netflix and Amazon to decide what you want to watch or buy next, and by researchers at MIT to predict the future. The ever-growing industry which has established itself to sell these tools is always keen to talk about how revolutionary this all is. But what exactly is it?


Flipboard on Flipboard

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What Is The Difference Between Deep Learning, Machine Learning and AI? Over the past few years, the term "deep learning" has firmly worked its way into business language when the conversation is about Artificial Intelligence (AI), Big Data and analytics. And with good reason – it is an approach to AI which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries. Deep Learning is used by Google in its voice and image recognition algorithms, by Netflix and Amazon to decide what you want to watch or buy next, and by researchers at MIT to predict the future. The ever-growing industry which has established itself to sell these tools is always keen to talk about how revolutionary this all is.


AI Is Now with

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Back in the pre-iPhone era, investors would rally around the word'mobile' as the'next big thing'. It was clear that mobility and doing things on small-screen devices would affect the lives of many for years to come, but what wasn't clear was how. How were applications going to get smart enough to add value on the go? How were web standards going to evolve fast enough to accommodate all the different kinds of devices available in the market? Which platforms across the myriad of non-compatible platforms (Symbian, WinCE, RIM, Java etc), should developers invest their time?