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Korean AI startup alliance aims to take on Google, Facebook

#artificialintelligence

A group of financial technology startups under Dayli Financial Group, a startup alliance in Seoul, have joined hands to offer AI services that could give "practical help" to financial firms. "Unlike Google's AlphaGo, IBM's Watson and Facebook's AI Research lab, which are more like pure research, our AI-based services are focused on addressing issues facing businesses," said Sophie Eom, who heads machine learning-based analytics solution firm Solidware, at a press conference in Yeouido, Seoul on Feb. 22. Solidware is one of the seven startups that have joined forces to form the startup group, called Dayli Intelligence. Each of the seven startups under the group, including Leevi and Heenam, is specialized in different fintech segments, but together they can offer better services, according to Eom, who also serves as a chief of the group's AI division. "After a series of meetings with corporate customers, I have found there is demand for a bundle of solutions, not just a single service," she said. The group will provide AI-based solutions for data analysis, natural language processing, and data scraping, which can be tailored for banks, insurance firms, and credit rating agencies.


Why AI will determine the future of fintech

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More investors are setting their sights on the financial technology (Fintech) arena. According to consulting firm Accenture, investment in Fintech firms rose by 10 percent worldwide to the tune of $23.2 billion in 2016. China is leading the charge after securing $10 billion in investments in 55 deals which account for 90 percent of investments in Asia-Pacific. The US came second taking in $6.2 billion in funding. Europe, also saw an 11 percent increase in deals despite Britain seeing a decrease in funding due to the uncertainty from the Brexit vote.


Data Virtualization: A Supermarket for Data

@machinelearnbot

Here's an analogy using a concept that we can all relate to: a supermarket. Picture the scene: Shopping list in one hand, shopping basket in the other, you're ready to tackle your weekly shopping in your local supermarket. Your items range from fruit and vegetables to washing detergent, perhaps with some free-range eggs thrown in for good measure. Quite the eclectic mix, but you know that you'll be able to find all you need under one roof. The fact that this is possible is in itself quite remarkable.


Advanced Machine Learning with Basic Excel

@machinelearnbot

In this article, I present a few modern techniques that have been used in various business contexts, comparing performance with traditional methods. The advanced techniques in question are math-free, innovative, efficiently process large amounts of unstructured data, and are robust and scalable. Implementations in Python, R, Julia and Perl are provided, but here we focus on an Excel version that does not even require any Excel macros, coding, plug-ins, or anything other than the most basic version of Excel. It is actually easily implemented in standard, basic SQL too, and we invite readers to work on an SQL version. In short, we offer here an Excel template for machine learning and statistical computing, and it is quite powerful for an Excel spreadsheet.


Game Changes for IoT, Robotics, & Artificial Intelligence in Manufacturing

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According to one of Maurice Conti's TED presentations, we arrived to a new, augmented age, in which Artificial Intelligence gains a new role. The future holds a generated era in which artificial intelligence comes up with its own designs, its own ideas, its own products instead of all our tools being passive, us telling them what to do and them doing it. From now on, tasks will be executed by robots, AI and humans cooperating, robots providing perfect execution, AI the design and humans making the necessary decisions. But in order to get to this point it is crucial to build a "nervous system" for robots through sensors. Industry 4.0 has introduced the concept of data exchange withing manufacturing, opening countless business opportunities, some that were previously unimaginable. By implementing sensors experts will be able to make use of data of all type which were not at hand before, making products become even services as well.


IoT news headlines, before and after DDoS attacks

@machinelearnbot

The famous cartoon series "The Jetsons" predicted 53 years ago how our lives would look like in 2063 when all our "daily devices" such as home appliances or cars would be connected to the internet. In 2016, the Internet of Things (IoT) is still evolving to a convergence of multiple technologies, including wireless communication, real-time analytics, machine learning, commodity sensors, embedded systems, automation, and more. On October 21, a series of Distributed Denial of Service (DDoS) attacks caused widespread disruption of internet activity across Europe and the US. This attack was also unique because it targeted IoT devices due to the fact they have soft security profiles. As the awareness of what impact connected objects would have on our lives and on our security.


Big data's power is terrifying. That could be good news for democracy George Monbiot

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Has a digital coup begun? Is big data being used, in the US and the UK, to create personalised political advertising, to bypass our rational minds and alter the way we vote? The short answer is probably not. A series of terrifying articles suggests that a company called Cambridge Analytica helped to swing both the US election and the EU referendum by mining data from Facebook and using it to predict people's personalities, then tailoring advertising to their psychological profiles. These reports, originating with the Swiss publication Das Magazin (published in translation by Vice), were clearly written in good faith, but apparently with insufficient diligence.


MWC- The Great Illusionists Show

@machinelearnbot

First of all, I will explain the reason for the post title. For those who have not seen the films, I summarize: "A group of four illusionists win year after year to the public with their incredible magic shows and even mocking the FBI. GSMA is a great illusionist and MWC is their principal magic show. We are invited year after year to visit an event with unique keynote speakers, an enormous list of exhibitors, amazing performances and a great LinkedInplace where we can meet in person some of our social media contacts. What else can we ask for? I know that it is very ruthless to compare the GSMA with illusionists and the MWC as their greatest magic show, but at least I see quite a few reasonable resemblances, you don t. If in 2015 I wrote " MWC 2015: Everything Connected, Tapas and Jamon", and I argued as one the reasons to attend MWC was the fact it was celebrated in Barcelona. In 2016, in my post "GSMA need to think how to reinvent MWC" I justify the reasons why the MWC needed to reinvent itself. One thing has become clear to me after many years attending MWCs, this is the world's biggest phone and mobile networks show, with manufacturers set to unveil a raft of new phone handsets and new technology. However, the GSMA had insisted on introducing more and more distractions like Internet of Things (IoT), Connected Living, Connected Car, AR/ VR, Robots. Maybe the reason is because Telecom operators do not have the DNA to change. Still, many telecom operators take a dim view of some of the aggressive moves being made by these peers, especially when it comes to business models based on commercializing customer data. "I expected to see less hype and a dose of common sense" Starting by the announcement of Spain's Telefonica to introduce a broad plan "4th Platform" to help both consumer and business customers keep greater control over their data rather than giving it away to web giants Google, Facebook and Amazon. "I expected to see more applications where IoT will become a lot less exciting, but more useful and profitable.


Google launches machine learning competition with Data Collective, Emergence Capital

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At its Google Cloud Next conference in San Francisco today, Google announced the launch of a machine learning startup competition, the winner of which will receive cloud credits and $1 million from well-regarded Silicon Valley venture capital firms. The program is open to startups in the U.S. that have raised less than $5 million and use machine learning software, in any industry vertical. Entrants' use of the Google Cloud Platform public cloud infrastructure is "encouraged but not required," according to the application form. The winning startup gets $1 million in Google Cloud Platform credits, which can cover the cost of computing and storage services as well as fully managed machine learning tools. Employees will get G Suite subscriptions, which includes Gmail, Google Drive, Google Calendar, and other applications -- and Google engineers will help startup employees improve their machine learning models.


Global Bigdata Conference

#artificialintelligence

The media often likes to proclaim "The Year of This" or "The Year of That." With the greater attention given to advancing capabilities in artificial intelligence and machine learning, it seemed like a no-brainer to declare 2017 "The Year of AI." However, in the interest of truth and the pursuit of all things real, it appears we may have been all wrong. According to a new report from big data management company Talend, 2017 will not be the year of AI, but will actually be the year of (wait for it) real-time analytics. This finding, which is based on a survey of 189 people who attended a Talend event in Paris last fall, may run counter to the prevailing wisdom that AI and ML are taking off in big ways, and that they are doing so right now.