Earlier than May-18-2017


You've heard about it, but do you understand? Everything you need to know about machine learning

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Looking through this lens, ML seems to be a lot like statistical modelling. In statistical modelling, we collect data, verify that it is clean -- in other words, that we have completed, corrected, or deleted any incomplete, incorrect, or irrelevant parts of the data -- and then use this clean dataset to test hypotheses and make predictions and forecasts. The idea behind statistical modelling is the attempt to represent complex issues in relatively generalizable terms, which is to say, terms that explain most events studied. Effectively, we programme the algorithm to perform certain functions based on the data we submit. Put differently, the algorithm is static.


Google's Second AI Chip Crashes Nvidia's Party

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Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. Google is getting more serious about chips. On Wednesday at its annual developers conference, the tech giant announced the second generation of its custom chip, the Tensor Processing Unit, optimized to run its deep learning algorithms.


Perpetuating Bias: Why We Should Think Critically About Artificial Intelligence in Marketing

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The debate surrounding the use of artificial intelligence in marketing is usually a controversial one. In the eyes of pop culture, advanced technology, like artificial intelligence, evokes views of imminent dystopias. One of the most memorable books I read recently was Dave Eggers' chilling dystopia The Circle, which was released as a movie last month. The story revolves around ambitious young go-getter Mae Holland who joins a growing tech company that aims to complete the "circle" of information sharing (which would eliminate any notions of privacy). This is a world in which advanced technology is a ubiquitous and seamless part of everyday life, so much so that we don't stop to question its existence.


5 Amazing Things IBM's Watson Can Do - Disruption

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Watson, IBM's supercomputer, is most well known for beating two quizmasters on popular quiz show Jeopardy! in 2011. The impressive artificially intelligent software was developed to advance machine learning capabilities, including natural language processing, reasoning and knowledge retrieval. Watson can access information from an endless list of sources, from literature to databases. As AI continues to attract investment and R&D, it will impact our lives in so many ways. It's not surprising, then, that Watson has rather expanded its repertoire since its Jeopardy!


Fight Against Cancer with Artificial Intelligence and Big Data - OpenMind

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This company has developed a new anti-cancer drug (against pancreatic, breast, liver or brain cancer) called BPM 31510, which has been discovered by an algorithm. The major technology companies are using millions of people data to find treatments. In addition to the start-ups, all major technology companies have already begun to apply Big Data and artificial intelligence to the service of health. Big Data and artificial intelligence, combined with genetic analysis, allow researchers to search for and find patterns among patients with rare diseases, who may be separated by distance but carry the same mutation.


Google Rattles the Tech World With a New AI Chip for All

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In a move that could shift the course of multiple technology markets, Google will soon launch a cloud computing service that provides exclusive access to a new kind of artificial-intelligence chip designed by its own engineers. CEO Sundar Pichai revealed the new chip and service this morning in Silicon Valley during his keynote at Google I/O, the company's annual developer conference. This new processor is a unique creation designed to both train and execute deep neural networks--machine learning systems behind the rapid evolution of everything from image and speech recognition to automated translation to robotics. Google says it will not sell the chip directly to others. Instead, through its new cloud service, set to arrive sometime before the end of the year, any business or developer can build and operate software via the internet that taps into hundreds and perhaps thousands of these processors, all packed into Google data centers.


AI and Machine Learning Microsoft Build 2017

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Democratization of Artificial intelligence, Microsoft's promise to take the AI and Machine learning from the ivory towers and make it accessible for all, is starting to take shape quite effectively. Let's face it; resource constraints around AI/ML is a real problem. Most companies with real-world AI use cases just don't have enough runway to build their own artificial intelligence offerings, and Microsoft cognitive services provide a sophisticated yet easy to use abstraction which fills this gap. Microsoft has also announced AI as an MVP category (http://aka.ms/AIMVP) Being a Microsoft MVP for Data Platforms, I have had the front row seat to see how Cognitive Services, a collection of powerful APIs and toolkits unfold to fulfill the promise of AI democratization.


Twitter Ranking Tweets With Machine Learning

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Machine learning is entering production at Twitter as a way of ranking tweets and boosting engagement. Twitter engineers this week unveiled the social media platform's ranking algorithm driven by deep neural networks. In a blog post, company engineers said their approach leverages an in-house artificial intelligence platform that includes new modeling capabilities. Among the results, wrote Nicolas Koumchatzky, a software engineer with Twitter's AI team called Cortex, are "more relevant timelines now, and in the future, as this opens the door for us to use more of the many novelties that the deep learning community has to offer, especially in the areas of [natural language processing], conversation understanding and media domains." Currently, Twitter (NYSE: TWTR) timelines are arranged chronologically based on a user's last visit.


Singapore launches national Artificial Intelligence programme

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The initiative will be driven by a government-wide partnership comprising NRF, the Smart Nation and Digital Government Office (SNDGO), the Economic Development Board (EDB), the Infocomm Media Development Authority (IMDA), SGInnovate, and the Integrated Health Information Systems (IHiS). AI:SG will bring together research institutions, AI start-ups and companies developing AI products, to grow knowledge, create tools and develop talent to power Singapore's AI efforts. AI.SG will work with companies to use AI to raise productivity, create new products, and translate and commercialize solutions from labs to the market. Mr Tan Kok Yam, Deputy Secretary, Smart Nation and Digital Government Office, said: "Through AI.SG, we intend to work with AI research performers, start-ups and companies to audaciously tackle tough challenges in areas such as transportation and urban management.


Artificial Intelligence: Embracing the Revolution – Becoming Human

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It's 2017 and unless you've been living under a rock, you will have seen that Artificial Intelligence is everywhere, and having an impact on (pretty much) everything. Artificial Intelligence is the here and now; it's making leaps and bounds throughout the world of tech and beyond. But what exactly is AI and why should we be embracing it? Defining AI can be pretty tricky and is often heavily disputed. If we're speaking via textbook definitions, then we can define AI as the development of computers that can embody and perform the same so-called'intelligent' actions of humans.