Shamayita Acharya

In this new digital transformation era, blockchain comes hand-in-hand as one of the fastest growing technologies to help secure and protect data through cryptography. Learn more about blockchain and what it means for big data. What is Blockchain? Blockchain is a secure, shared, decentralized, distributed, immutable database that maintains a continuously growing list of records called blocks. Seebacher & Schüritz further describes the distributed database as a “shared among and agreed upon a peer-to-peer network. It consists of a linked sequence of blocks (a storage unit of a transaction), holding timestamped transactions that are secured by public-key cryptography (i.e., “hash”) and verified by the network community. Once an element is appended to the blockchain, it cannot be altered, turning a blockchain into an immutable record of past activity.” How Does Blockchain Work? At the core of the blockchain technology is a distributed ledger with groups of transactions collecte

By Lance Eliot, the AI Trends Insider I was in an airport and on my way to give a speech about self-driving cars when I realized that my smartphone was getting low on its battery charge and I knew that the flight itself would not have any power outlets at the seats. I looked around the gate area to see if there was a place to plug-in my phone to charge it. Most airports seem to have charging bars where you can plug-in your phone, but this airport was apparently stuck in the 1980s and there weren’t any designated areas for phone charging. My next plan of attack was to find an electrical outlet, preferably one that was near some seats so that I could sit down and be right next to my phone as it was getting charged up. Disappointingly , this airport wasn’t just in the 1980s and instead, worse still, was in the Neanderthal era because there weren’t any electrical outlets anywhere. In fact, it almost seemed like the airport had purposely tried to hide or close-off any chances of finding

There’s a high-stаkes rасe аmong the biggest teсh сompаnies, from Google to Αmаzon, to stаke out turf in the burgeoning аrtifiсiаl intelligenсe mаrket. But аsk IBM, аnd it will tell you it hаs the home-field аdvаntаge. Αfter аll, in 1957, the сompаny helped prove thаt AI hаd prасtiсаl uses when it progrаmmed аn IBM 704 to plаy сheсkers аnd to leаrn from its experienсes. In 2011, аn IBM super-сomputer nаmed Wаtson beсаme the сhаmp of the TV triviа gаme show “Jeopаrdy.” Αnd аlthough IBM’s foсus is on teсhnology for enterprise сustomers, rаther thаn direсt to сonsumer produсts, the 107-yeаr-old сompаny is not аbout to let its AI reputаtion be stolen by upstarts like Google, Fасebook, Αmаzon. IBM recently аnnounсed thаt it hаs releаsed AI speсiаlly “pre-trаined” for nine industries, inсluding humаn resourсes, supply сhаin, mаnufасturing, аnd аdvertising. These AI tools, pаrt of the Wаtson Deсision Plаtform, сome pre-progrаmmed to understаnd the lаnguаge, tаsks аnd сhаllenges of

SAP has announced its guiding principles for artificial intelligence (AI) and its creation of an external AI ethics advisory panel – the first European technology company to do so. The panel, comprised of experts from academia, politics and industry, will ensure the adoption of the principles and further develop them in collaboration with the AI steering committee at SAP, a group of SAP executives from development, strategy and human resources. The new guidelines, the external panel and the internal committee aim to ensure that the AI capabilities supported by SAP Leonardo Machine Learning capabilities are used to maintain integrity and trust in all solutions. As the market leader in enterprise technology that touches 77 percent of the world’s transaction revenue and serves more than 400,000 customers worldwide, SAP solutions and applications impact the lives of billions of people daily. “SAP considers the ethical use of data a core value,” said Luka Mucic, chief financial officer

Developing a production database requires extensive optimization. With the growing concerns about data privacy and new regulations such as the Global Data Protection Requirement (GDPR), these databases must be created with privacy safeguards in place. You need to use a few different data anonymization techniques to accomplish this with a standard SQL database. SQL data generator tools are frequently used for data anonymization. Here is the process for using data anonymization with SQL generators. Conduct a data audit and mark data sets that require masking Anonymization tokens are often necessary, but they also take time to set up. Applying data masking to every data set would be an unnecessarily time intensive and cumbersome process. You need to begin by taking an inventory of all current and future data sets. Mark data that will need to be anonymized with your SQL generator. Other data can be easily copied from your production database. Benefits of using an SQL generator fo

Increasingly, big data is invading consumers’ lives. It affects consumers' privacy as the web has become such a centralised platform. When you have centralised organisations collecting so much consumer data and using it to offer personalised advertising to their users, it causes problems. As Jonathan Taplin discussed in his book Move Fast and Break Things, organisations that have access to so much data and use it to steer consumer behaviour could directly undermine our democracy. These centralised organisations do not forget or forgive. Since actions (i.e. data) speak louder than words, it is possible that data are defining human beings. A Self-Sovereign Identity A solution to these problems might be the incorporation of a self-sovereign identity; an identity that is owned and controlled by the person or the device that created it. To develop a self-sovereign identity, we need to look differently at identity and in the book Blockchain: Transforming Your Business and Our World,

Few things have been watched with such breathlessness in recent years as the rapid rise of machine learning into virtually every realm of our lives. Still, many misconceptions about machine learning and how it’s going to impact our economy are still floating about, and innumerable business owners are unsure of what to believe when it comes to adopting machine learning and AI for their own purposes. Some have resigned on the issue altogether and believe that machine learning is nothing more than a buzzword that can’t possibly impact their businesses. Here’s why they’re wrong, and how machine learning can substantially reshape your company – starting by taking a huge load off network management. Machine learning deployment strategies are starting to take shape Where once artificial intelligence and machine learning were merely trendy words used to describe far-off technologies, they’ve become an everyday reality. Machine learning deployment strategies are starting to become commonp

Next week we’ll be celebrating Customer Experience Day! October 2nd marks the 6th annual CX Day, which “celebrates the professionals and companies that make great customer experiences happen. It’s an opportunity to recognize great customer work, discover professional development opportunities, and strengthen professional networks.” (CXDay.org) Hortonworks has seen tremendous growth other the years, since its […] The post In Our Customer’s Words – Previewing CX Day 2018 appeared first on Hortonworks .

Microsoft's .NET framework is a collection of technical support that empowers both business as well as individual users with a seamless interoperable interface for computational devices. Covering various programming languages under one roof, ASP.NET makes for a terrific choice as compared to other development models for developing artificial intelligence and machine learning applications. If you are wondering why, allow us to walk you through its many benefits. For starters, the .NET framework substantially reduces the amount of code required for creating big apps. It also offers finer performance by leveraging early binding, in-time compilation, native optimization, and caching service out-of-the-box. And it is also further supplemented by the provision of a comprehensive toolbox in the Visual Studio integrated into development environment. This includes features such as automatic deployment and drag-and-drop server controls. In addition to that, the ASP.NET runtime keeps an eye

Reinforcement learning is gaining attention as the “ next step in AI ”, but there are very few business use cases of this technology. So is reinforcement learning a moonshot or an underhyped game-changer? Artificial intelligence is one of the most dynamic fields of research and development. It allows companies to solve new classes of problems and effectively tackle challenges where creativity and flexibility are required. Unlike “machine learning” and “deep learning”, “reinforcement learning” is not a commonly used buzzword and requires some explanation. What is reinforcement learning? Data is fundamental to all forms of machine learning. Whatever model is being used, it needs to get and process data to be able to perform a task. In traditional machine learning and deep learning, the data usually come in the form of a closed dataset consisting of more or less structured and homogenous information. They may be a set of images, a sorted sheet or a customer database. In traditional

Ladies and gentlemen, this is the future. No, we haven’t colonized Mars – yet – and we don’t have personal housekeeping robots, but digital marketing has undoubtedly had some developments that we would have never thought possible. We do have a different kind of bot; let’s all welcome B2B chatbots! Bots are taking over the many different ways that you can interact with your existing and potential clients, and even at this rate, that opportunities still seem to be limitless if you ask us. We’ve all heard of bots answering customer service requests, but now you are seeing them sell, update, disseminate information and make life generally interesting for everyone. A Couple of B2B Chatbots Statistics Did you know that if you want a chatbot right now, you are not alone? According to a survey conducted by the folks at Oracle, 80 percent of businesses would want a chatbot by 2020. It gets better; too, some companies have been reporting major successes. From companies who do makeup re

The ability and desire to work remotely has grown almost as quickly as the Data Science market itself. It’s becoming an increasingly popular choice for many talented Data Scientists as they seek to have a better work-life balance, the freedom to work on a variety of projects and learn a wider skill set to name a few. With this in mind, more and more companies are taking on contractors for Data Science projects. Before you commit to taking on a permanent employee, you might want to consider hiring contractors for your business. Additionally, they can be a good option until your permanent hire arrives. Here are some pointers on why taking on contractors could be a great decision for your company! Experience and expertise = quick results Most established contractors will have worked on a number of projects with a range of different organisations. Given their experience in a variety of companies, they are usually able to quickly adapt and gel with their new colleagues. By hitting the

The Internet of Things is slowly coming into its own. Statista notes that by 2020, there will be over thirty billion connected devices on the IoT, underscoring the importance of this technology. Combining the IoT with a cloud platform (such as Azure) provides a unique opportunity for a company to explore innovative methods of meeting their goals. Thanks to the flexibility of cloud platforms, the system that is developed is likely to be efficient as well as scalable. In order to put together a scalable network with the cloud and IoT, we need to sort a few major considerations out. Understanding What We're Building Many companies have IoT projects in the works. According to ZD Net, Cisco is well aware that a majority of IoT projects fail right out of the blocks. A lot of this is due to the inability of a company to define what it is they are going to build and how it will benefit their company. In order for us to avoid this trap, we are going to need to look at a few areas of int

By Lance Eliot, the AI Trends Insider Living in Southern California means that it is best to be prepared for the possibility of earthquakes. Some say we are the earthquake capital of the country, though this is a debatable assertion. Some of my colleagues from other parts of the U.S. seem to think that we have earthquakes constantly and that I’m unable to walk outside of my home or office without staggering along due to the ground shaking. Not quite, or at least not due to earthquakes. For my colleagues along the Atlantic, we tend to trade barbs about earthquakes versus hurricanes. Which is better or worse, the earth shaking or a torrent of wind, rain, and floods? Neither one is desirable, but some say that at least a hurricane you usually know beforehand that it is coming, while an earthquake tends to just suddenly appear. Hurricanes seem to cast a wider and larger path of destruction than does an earthquake. Both a hurricane and an earthquake are measured on scales of magnitude,