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Machine learning-based applications have seen significant commercial success in several mainstream consumer applications in the recent past. Self-driving cars, stock-trading bots, robo-advisors, Amazon’s Alexa, and Apple’s Deep Fusion and Siri are some of the renowned examples of commercial success with artificial intelligence and machine learning. AI has also made our lives easier by improving the customer experience of the products we use. Google’s text generation software, Netflix’s recommendation engine, and Facebook and Twitter’s fake news detection are other prime examples. In fact, every single technology company uses AI in its mainstream applications either directly or indirectly. Non-technology companies are also using AI to improve customer experience, improve efficiency, and generate new revenue streams. Chatbots, robo-advisors, systems that predict system failures, and products that generate efficient supply chain routes are some of the prominent ways in which non-technology companies use AI. This is leads to a popular belief that AI and ML are primarily used by technology companies or they are being used by non-tech companies to build AI-based products.

This popular perception is not true. There are plenty of avenues in which AI/ ML is being used or can be used by non-tech and non-product-based groups to generate insights. In this article, I am going to share with you four ways in which you can augment advanced analytics into your analytics strategy to generate insights.

Source de l’article sur DZONE

Fake news has become a huge issue in our digitally-connected world and it is no longer limited to little squabbles — fake news spreads like wildfire and is impacting millions of people every day.

How do you deal with such a sensitive issue? Countless articles are being churned out every day on the internet — how do you tell real from fake? It’s not as easy as turning to a simple fact-checker which is typically built on a story-by-story basis. As developers, can we turn to machine learning?

Source de l’article sur DZONE

As the impact of fake news has grown, so too have attempts to detect and remove it. I wrote recently about an AI-driven approach developed by the University of Michigan, which is able to accurately spot fake news stories around 76% of the time.

A second system, developed by a team from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) and the Qatar Computing Research Institute (QCRI), are attempting to do likewise. Their approach focuses less on the reliability of individual claims and more on the general reliability of the news sources themselves.

Source de l’article sur DZONE

Do you or someone you know lives in Egypt and holds an account on Facebook, Twitter, or/and other social media platforms with more than 5000 followers? If yes, your account can be censored, suspended and is subject to prosecution for promoting or spreading the fake news through social media platforms. On July 16, the Egyptian parliament approved a new law that classifies a personal social


Source de l’article sur The Hacker News