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Big data

    Why Our Fast-Changing World Requires Us to Change Collaboration



    The world around us is changing faster than ever before. It is changing politically (Brexit), socially (generation Z hitting the labour market), technologically (AI, quantum computing, blockchain and IoT coming our way), economically (continuous trade wars between US and China and the upcoming economic powerhouse China) as well as environmentally (climate change). This is a significant challenge for citizens to deal with.

    As a result, we see a movement towards populism, nationalism and in-ward looking politics (make America great again, and Brexit are perfect examples of this). After all, most people do not like change, and if their world is changing rapidly as it is doing today, they tend to hold on to what they know and feel comfortable with. Although this might seem like a logical thing to do, it does not bring you anything. If we want to move forward, we have to embrace change. It is not going away by burying our head into the sand. Especially not with change happening in so many areas.

    Data Changes How We Collaborate

    My area of interest is how we can use technology to improve our world and deal with these changes. I am not an economist nor a politician, but I believe ...

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    Hunting for Data: a Few Words on Data Scraping



    No matter how intelligent and sophisticated your technology is, what you ultimately need for Big Data Analysis is data. Lots of data. Versatile and coming from many sources in different formats. In many cases, your data will come in a machine-readable format ready for processing — data from sensors is an example. Such formats and protocols for automated data transfer are rigidly structured, well-documented and easily parsed. But what if you need to analyze information meant for humans? What if all you have are numerous websites?

    This is the place where data scraping, or web scraping steps in: the process of importing information from a website into a spreadsheet or local file saved on your computer. In contrast to regular parsing, data scraping processes output intended for display to an end-user, rather than as input to another program, usually neither documented nor structured. To successfully process such data, data scraping often involves ignoring binary data, such as images and multimedia, display formatting, redundant labels, superfluous commentary, and other information which is doomed irrelevant.

    Applications of Data Scraping

    When we start thinking about data scraping the first and irritating application that comes to mind is email harvesting — uncovering people’s email addresses to sell them on to spammers or ...

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    IoT in e-Commerce: How a Connected World Can Change Trade



    The Internet of Things is one of the hottest topics today that penetrates all spheres of life from healthcare to commerce. The commercial sector was among the first to adopt the idea of intelligent devices monitoring goods: Coca-Cola, for example, was implementing vending machines that reported how much stock they had left and whether the drinks were cold as early as 1982!

    Such great interest and enthusiasm are indicators of the potential of the IoT in commerce even before it moved to the Internet. Nowadays, when e-commerce is getting more and more of the market, the possibilities for the IoT application become boundless.

    E-commerce, or internet commerce, refers to the activity of buying and selling goods or services via the internet, as well as the transfer of money and data to execute these transactions. E-commerce is often used in connection with the sale of physical products online, but it can describe any kind of commercial transaction made online, using such technologies as mobile commerce, electronic funds transfer, supply chain management, Internet marketing, online transaction processing, electronic data interchange, inventory management systems, and automated data collection systems.

    With such a broad scope of e-commerce, it goes without saying it may benefit from the Internet ...

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    Seven Guidelines to Ensure Ethical AI



    The organisation of tomorrow will be built around data, and it will require artificial intelligence to make sense of all that data. Artificial intelligence is a broad discipline with the objective to develop intelligent machines.

    AI consists of several subfields: Machine learning (ML), a subset of AI that enables machines to learn from data. Reinforcement learning, which is a subset of ML and focuses on artificial agents that use trial and error to improve itself. And deep learning, also a subset of ML that aims to mimic the human brain to detect patterns in large datasets and benefit from those patterns.

    Artificial intelligence has been around since the 1950s, thanks to the work of Alan Turing, who is widely regarded as the father of theoretical computer science and artificial intelligence. Back then, Alan Turing already dreamed of machines that would eventually “compete with men in all purely intellectual fields”.

    In the past years, we have come to a lot closer to Turing's dream. Thanks to billions of dollars in research spent by tech giants such as Google, Facebook, Tencent, Baidu, Apple and Microsoft, there has been increased attention on AI. Resulting in a variety of ever-more intelligent AI applications in almost every domain.

    The ...

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    Genderless Voice AI Could Provide Major Step in Combating Implicit Bias



    Implicit in any technical process or system are the biases of those writing the code that will govern the actions of that respective technical system or process. I’m not throwing shade at developers in saying that, but rather highlighting that we all suffer from implicit biases — whether known or not — and those biases get baked into the software solutions we develop and deliver. 

    We’ve written about it before, but I think it bears repeating because there are some pretty fascinating solutions on deck aimed at combatting some common but probably unrecognized variants of this. Namely, the interface of the future, natural language processing (NLP), is confined to binary voice characteristics unnecessarily. Enter the genderless voice AI ‘Q’.

    Why do our vocal assistants’ voices matter?

    Quoting a great paragraph from Mark Wilson in Fast Company:

    “Voice assistants like Apple’s Siri and Amazon’s Alexa are women rather than men. You can change this in the settings, and choose a male speaker, of course, but the fact that the technology industry has chosen a woman to, by default, be our always-on-demand, personal assistant of choice, speaks volumes about our assumptions as a society: Women are expected to carry the psychic burden of schedules, birthdays, and phone numbers; they ...

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    How the Internet of Things and AI will Transform Sports?



    This is an abstract of my presentation in Dubai on the 23rd April 2019.

    In 2016 in my article “ The future of “The Internet of Olympic Games”, I considered Rio as the first Internet of Things (IoT) Olympic games. In Rio, we saw how athletes, coaches, judges, fans, stadiums and cities benefited from IoT technology and IoT solutions and this somehow changed the way we see and experience sports.  Next year we will have the opportunity to verify if my predictions for Tokyo 2020 will become a reality and we will name Tokyo as the first Artificial Intelligent (AI) Olympic Games.

    During my presentation in Dubai, I explained the audience the incredible way IoT and AI technologies are impacting sports. I dedicated some time explaining how IoT and AI are playing an increasingly significant role in boosting talent, managing health and improving coaching and training.  Today these technologies are already enabling athletes to improve performance, coaches to better prepare games, judges to fail less, fans enjoyed with new exciting experiences. I also remarked about the importance that teams clubs and cities collaborate to make the stadiums more secure and more exciting for fans.

    I emphasized how we are creating smart things, the ...

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    How FinTech Companies Are Challenging the Biggest Banks



    The global financial crisis in 2008, which led to a full-blown international banking crisis, was considered the most serious crisis since the Great Depression. And while it was a downfall for traditional banking systems, it paved the way to the emergence and rapid success of FinTech companies.

    FinTech Companies

    Financial technology, also known as FinTech, is an innovative approach to traditional financial methods used by brick-and-mortar banks and financial institutions. FinTech has given rise to a range of new business models, applications, and processes.

    Modern financing companies heavily rely on technology. They use it for various processes, such as processing application, screening candidates, collecting repayments, and even offering financial advice. All FinTech banks follow the same business model and that is the integration of technology-enabled innovation.

    The indispensable use of technology is what sets FinTech companies from traditional banks. These companies can be categorized under banking, as well as insurance or asset management. They are also subject to relevant regulation and supervision.

    Impact of FinTech to Traditional Banking

    The FinTech industry is enormously growing at an annual CAGR of 22%. In the first half of 2018, investments in FinTech companies worldwide totaled $57.9 billion and is expected to reach $70 billion by 2020.

    How has FinTech changed ...

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    5 Blockchain Trends for You to Consider this Year



    The blockchain ecosystem is rapidly expanding. New blockchains or different consensus mechanisms are announced continuously, resulting in a more mature ecosystem. For blockchain technology to achieve wide-scale adoption, a decentralised ecosystem has to be developed. To achieve a decentralised society, many more components need to be built, requiring global standards and large investments. I estimate that it will take another 3–5 years before the ecosystem is ready for full-scale, enterprise adoption. Apart from the different industry layers that need to be developed, we will also continue to see new distributed ledger technologies and more exciting decentralised applications. The blockchain ecosystem consists of multiple layers, which you see in below infographic. With the blockchain ecosystem evolving, new applications and technologies come into play as well. Therefore, here are five blockchain trends that you should consider in the coming year:

    Trend 1: The convergence of blockchain and other emerging information technologies

    Blockchain is not a standalone technology. Especially the convergence of blockchain and technologies such as big data analytics, IoT or AI will be disruptive. This convergence will greatly affect how organisations should approach data and how they can derive insights from it. It will require new solutions and approaches from organisations, regulators, ...

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    Could Blockchain Prevent the Internet of Vulnerable Things?



    The Internet of Things is coming. Unfortunately, connected devices have a variety of vulnerabilities and almost any smart device is a vulnerable device. Security issues include technical problems (outdated software, insecure data transmissions, etc.) and people problems (simple and default passwords, public Wi-Fi, etc.). As more devices connect to the internet and each other without proper security, the Internet of Things will quickly become the Internet of Vulnerable Things.

    With the Internet of Things being around the corner now, it is time to start securing connected devices. Especially, because the main driver behind the Internet of Things is nearing completion in the coming years: 5G. 5G will be the main driver behind the Internet of Things, and without it, the Internet of Things will remain an illusion. So why do need 5G and how can we prevent the Internet of Vulnerable Things?

    Why the IoT Needs 5G?

    The benefits of 5G compared to 4G are substantial. 5G will not only offer network speeds as high as 10Gbps but also enable lower communication latency – up to 1 millisecond. The combination of high speed and such low latency will enable new products, applications and services that are currently not possible. Simply, because currently, it ...

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    DevOps Is Great, But You Can Make It Better



    The job of a developer is never complete, as old code must be updated to fit into new frameworks, new code is always waiting on the sidelines, and fixes take time to test before they can be deployed. Organizations now know to use DevOps models for continuous deployment, which integrates developers and operations team members more closely, streamlining this process by seeking to establish routines that reduce bottlenecks.

    Even with an efficient DevOps-powered development cycle, however, there’s always room for improvement in any organization. The following strategies are key for reducing speedbumps in your operation’s development efforts.

    Define Metrics to Help You Track Efficiency

    While it is an overarching paradigm—a discipline rather than a business flow—DevOps need to be able to define what they’re doing right and wrong, and it isn’t always immediately obvious. Narrowing down a handful of the most valuable DevOps efficiency metrics lets you employ data to verify how your efforts are performing and establish a culture of feedback that is necessary for continued success. If you want your IT teams to deliver software in a streamlined fashion, as DevOps promises to do, they’ll need a clear path built on measurable milestones and actionable insights.

    Most IT veterans know how difficult ...

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