This fake news detection algorithm outperforms humans

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When researchers working on developing a machine learning-based tool for detecting fake news realized there wasn't enough data to train their algorithms, they did the only rational thing: They crowd-sourced hundreds of bullshit news articles and fed them to the machine. The algorithm, which was developed by researchers from the University of Michigan and the University of Amsterdam, uses natural language processing (NLP) to search for specific patterns or linguistic cues that indicate a particular article is fake news. This is different from a fact checking algorithm that cross-references an article with other pieces to see if it contains inconsistent information – this machine learning solution could automate the detection process entirely. No offense to the Michigan/Amsterdam team but building an NLP algorithm to parse sentence structure and hone in on keywords isn't exactly the bleeding edge artificial intelligence work that drops jaws. Getting it to detect fake news better than people, however, is.


Qualcomm buys Dutch research outfit to bolster artificial intelligence expertise

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Qualcomm announced that it has purchased Dutch artificial intelligence research company Scyfer to boost its expertise in machine learning. The price was not disclosed. Scyfer has built artificial intelligence systems for companies in manufacturing, healthcare, finance and other industries. Founded in 2013, Scyfer is a spinoff of the University of Amsterdam. Professor Max Welling co-founded the company and will continue to work both as a professor and an artificial intelligence researcher for Qualcomm.


Thalesians Seminar (Canary Wharf) -- Svetlana Borovkova -- AI: Sentiment in News and Social Media

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ABSTRACT The availability of powerful Natural Language Processing techniques led to the emergence of AI tool that reads and interprets unstructured textual information, such as news and social media messages. The sentiment of finance-related content influences trading and investment decisions of players in financial markets and hence, moves the prices of assets. Dr. Svetlana Borovkova has been working for several years in the area of sentiment analysis and its relation to financial markets; applications of sentiment analysis range from commodity trading to systemic risk to quantitative investment strategies. In this talk, Dr. Borovkova will give an overview of this exciting field and show, among other things, how media sentiment can be used to forecast global financial distress, to generate sector and country rotation investment strategies and to help enhance machine learning applications to intraday trading. SPEAKER Dr. Svetlana Borovkova is an Associate Professor of Quantitative Finance in Vrije Universiteit Amsterdam and Head of Quantitative Modelling in risk advisory firm Probability & Partners.


IBM Watson is creepily good at guessing what's in photos

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IBM announced that its Watson AI is getting image recognition capabilities earlier in the year, but this site that lets you feed in your own photos to see what it thinks is in them is both impressive and scary. The visual recognition demo lets you give Watson an image URL or upload a photo and it'll come back in a few seconds with what it thinks it sees. This year's edition of TNW Conference in Amsterdam includes some of the biggest names in tech. In my tests I fed Watson a few random photos I had on hand and the accuracy was quite surprising. It could figure out what was in landscape shots, animals (down to the breed) and even what's in the background.


How AI is Shaping the Future of Customer Experience

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Booking.com, a brand within Priceline Group, is planning to begin using artificial intelligence (AI) to create personalized travel options for customers. According to Seeking Alpha, Booking.com will begin using AI within its mobile apps to provide travelers with instant recommendations for local events and attractions once they've reached a destination. Booking Experiences tool, which has been launched on its iOS and Android apps in Amsterdam with planned rollouts in Dubai, London, Paris, and New York over the next few months, makes suggestions based on a user's personal experience and from having analyzed millions of personal likes and dislikes and how these experiences impact the buying decisions for various venues. For instance, chatbots powered by AI are able to field and answer questions from customers on a variety of subjects, from generating recommendations on gift purchases to locating the nearest Chinese restaurant. As with other forms of automation, some have questioned whether AI will replace customer service reps and people in other types of customer-facing roles.