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  • What Machine Learning Can Learn from DevOps

    The fact that machine learning development focuses on hyperparameter tuning and data pipelines does not mean that we need to reinvent the wheel or look for a completely new way. According to Thiago de Faria, DevOps lays a strong foundation: culture change to support experimentation, continuous evaluation, sharing, abstraction layers, observability, and working in products and services.

  • Q&A on the Book Driving Digital Strategy

    The book Driving Digital Strategy by Sunil Gupta provides guidelines and advice for executing fundamental digital transformations in companies, based on lessons from digital transformation at Fortune 500 companies. To be successful you have to fundamentally change the core of your business and ensure that your digital strategy touches all aspects of your organization, argued Gupta.

  • Codefirst: The Future of UI Design

    User interface design has played a critical role in computing for decades. Flat and tactile design are current trends in application design. Voice user interfaces are emerging with Alexa, Siri, and Google. Augmented and virtual reality, and IoT lead to significant changes in designs. AI is poised to create significant changes by perfecting user interface designs.

  • The Rewards and Challenges of Predictive Maintenance

    Predictive maintenance is not new, but today more than ever, with advancements in industrial Internet of things (IIoT) and artificial intelligence (AI), predictive maintenance can result in significant savings for manufacturers.

  • Q&A on the Book Testing in the Digital Age

    The Book Testing in the Digital Age by Tom van de Ven, Rik Marselis, and Humayun Shaukat, explains the impact that developments like robotics, artificial intelligence, internet of things, and big data are having in testing. It explores the challenges and possibilities that the digital age brings us when it comes to testing software systems.

  • Cats, Qubits, and Teleportation: The Spooky World of Quantum Algorithms (Part 2)

    Quantum information theory really took off once people noticed that the computational complexity of quantum systems was actually a computational capacity, which could be applied to other problems, such as factorization, which is used within public key cryptography. This article explores quantum algorithms and their applicability.

  • Can People Trust the Automated Decisions Made by Algorithms?

    The use of automated decision making is increasing. These algorithms can produce results that are incomprehensible, or socially undesirable. How can we determine the safety of algorithms in devices if we cannot understand them? Public fears about the inability to foresee adverse consequences has impeded technologies such as nuclear energy and genetically modified crops.

  • How Technology Is Impacting the Future of Work through Fragmentation

    One of the side effects of technology’s evolution is that it fragments existing architectures and creates new structures in the process. AI and Blockchain are currently doing this, but this pattern has been seen before and will continue as tech evolves. According to Kary Bheemaiah, fragmentation is impacting the future of work; it’s a tech-lead reality to be observed and leveraged when possible.

  • Get More Bytes for Your Buck

    Lovethesales had to classify one million product data from 700 different disparate sources across a large domain. They decided to create a hierarchy of classifiers through utilizing machine learning, specifically Support Vector Machines. They learned that optimising the way in which the svms were connected together yielded vast improvements in the reuse of labeled training data.

  • InfoQ Call for Articles

    InfoQ provides software engineers with the opportunity to share experiences gained using innovator and early adopter stage techniques and technologies with the wider industry. We are always on the lookout for quality articles and we encourage practitioners and domain experts to submit feature-length (2,000 to 3,000 word) papers that are timely, educational and practical.

  • How AI Will Revolutionize These Five Job Roles by 2022

    AI is altering major job roles in the tech industry. From developers to managers to CIOs, established industry positions are being disrupted already. In five years many will be unrecognizable. What changes are coming? This article examines five key roles in tech and show how AI will remake them in the next five years.

  • The Problem with AI

    AI depends on "data janitorial" work, as opposed to science work, and there is a gulf between prototype and sandbox, and innovation and production.

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