Shamayita Acharya

Imitation is the sincerest form of flattery. But brands that lose billions to counterfeit products don’t feel it that way.  Cambridge dictionary defines counterfeiting as “something that is made to look like the original of something else, usually for dishonest or illegal purposes”. Basically, it is the practice of creating fake versions of products at a low cost and selling them at a high value.  It is a nuisance for the fashion industry as both the brand’s reputation and revenue streams suffer as a result. According to the Global Brand Counterfeiting Report 2018, the losses suffered due to online counterfeiting amounted to $323 billion in 2017. Luxury brands such as Gucci and Louis Vuitton incurred $30.3 billion in the same period.  Why Counterfeiting Is Massive in the Fashion Industry Counterfeiting is higher in the fashion industry. Since the attraction of most items is the brand and not the quality, dubious retailers simply slap logos of globally popular br...

Data is the new oil -- pretty sure you have heard that like a million times by now. But it's true -- the information is, indeed, among the most precious commodities in the world. This truth, in turn, has put the focus on technologies, tools, and resources that enable entities across the globe to make the most efficient use of what can practically be described as gold mines of data. It is why ETL has gained so much favor with stakeholders across the entire ecosystem. If you are wondering, well what is ETL? Allow us to explain. Short for Extract, Transform, Load, ETL is a strategy comprised of a three-step process that enables one to, first, Extract data from a variety of sources, such as JSON, XML, RDBMS, and more with the use of minimal resources. During this phase, it is imperative that the source system's performance and response time. Then comes the Transformation of this data into a uniform format to facilitate analysis. To 'transform' this data, companies make us...

By Allison Proffitt, Editorial Director, AI Trends Nearly everyone believes that AI can help in drug discovery within the next three years, but the devil is in the details. That’s according to the new survey on AI in Drug Discovery from AI Trends. We asked readers about how they are using AI in their jobs and what opportunities and challenges they see ahead for the technology as applied to drug discovery. Almost unanimously respondents believe that AI can assist in drug development. But the specifics get murkier. This year about one-third of our survey-takers represented biotech and pharma and one-third hailed from academia. The rest came from hospitals, government labs, technology providers and more. 59% reported that they use AI already in their role, with machine learning, pattern recognition, deep learning, and image recognition leading the applications. Compared to our 2018 survey, personal concerns spread more evenly across many options. We asked if survey takers had AI-rela...

Contributed Commentary by Hamza Ghadyali, AI Specialist at SAS Human beings are not suited to perform repetitive and tedious tasks, no matter how important, skillful, or critical they might be. Imagine watching hours of surveillance footage with extremely rare instances of anomalous activity. Or being a doctor who must manually review volumes of medical imaging to identify tumorous cells. Similarly, in manufacturing, inspecting products for defects is exceedingly mundane when only one in a million needs to be pulled. As human beings, we are curious at our core, and our work should play to that strength. Fortunately, today’s analytics and AI capabilities are perfect for such tasks. AI has had a resurgence in the last five years because new machine learning techniques are now solving three particular problems in ways that are similar to humans and with comparable accuracy: playing games (reinforcement learning), reading and understanding natural language (text analytics), and analyzi...

By John P. Desmond, AI Trends Editor A new wave of AI Storytelling tools is ushering in an era that includes created characters who have relationships, are in stories, and can adapt to react to how audiences play. Charisma.ai for instance offers “a new dimension of storytelling: re-playable, interactive conversations with crafted characters.” Components include a “hyper-advanced” story editor and a chat engine. Characters have emotions, memories and voices. The company’s partners include the BBC, Playstation, King’s College of London and Brunel University in London. Charisma.ai’s technology platform was developed by the games studio To Play For. Founder and CEO Guy Gadney, in a response to a query from AI Trends , described his team as coming from, “a diverse background of cutting edge tech, product design, and philosophy.” Asked to describe the problem his company was created to solve, Gadney said, “We created Charisma.au for writers, and everything we do is filtered through tha...

Alex Muller is working on creating a consumer interface that aims to incorporate AI to learn about customers and deliver a continuously improving user experience. After selling his company, GPShopper, to Synchrony Financial in 2017, Muller is now Senior Vice President, Entrepreneur in Residence, Synchrony Financial, where he is leading this development effort. The team is working to define new roles and come up with an original development process. “Are you familiar with the waterfall development model?” he asked an audience at the AI World Conference & Expo held recently in Boston. “Don’t you know you’re not supposed to know that anymore?” Alex Muller, Senior Vice President, Entrepreneur in Residence, Synchrony Financial Waterfall was followed by agile development, noted for its “sprint” between project milestones. “But it was still too slow and it’s a one-size-fits-all approach,” he said. “The future of development is a self-evolving product,” he posited. “It’s evolving t...

By Lance Eliot, the AI Trends Insider The duck won’t quack. Allow me to elaborate by first providing some helpful background. Today’s children are growing up conversing with a machine. The advent of Alexa and Siri has not only made life easier for adults, it also has enabled children to get into the game of talking with an automated system. These automated systems contain relatively advanced NLP (Natural Language Processing) capabilities, which many consider part of the AI umbrella of technologies. Improvements in NLP over the last decade or so has made them much less stilted and much more conversational. That being said, we all have undoubtedly experienced the rather quick and rough edges of even today’s best NLP. If you ask a straightforward question such as who is the current president of the United States, the odds are that those utterance of words can be parsed and that the context of the question can be surmised. But, if you twist around the verbs and nouns, and use slang o...

Big data is no longer some nascent trend riding a cycle of media hype. It’s here to stay, and it’s transforming how businesses make decisions, build products, and engage customers. In fact, the ability to distill mountains of data into actionable insights has become a sustainable competitive advantage, separating the “Netflixes” from the “Blockbusters” in every industry. But you knew that, right? Most industries are well-acquainted with big data’s disruptive power. What’s news to most is the fact we’ve neglected big data’s brother, “little data.” In so doing, we’ve diluted the value big data offers our businesses. Fundamentally, big data isn’t about the amount of data captured. It’s not even about the new types of data you can collect. It’s about turning transaction-level information – which represents the most accurate observations of what’s really happening “on the ground” – into business insights to support decision making. In this way, little da...

We have reached the end of 2019 and just like in previous years, I am looking ahead to see what organisations can expect next year. 2019 was the year of truth, with many enterprises developing blockchain proof of concepts, Google confirming a quantum supremacy breakthrough and more data breaches with the latest breach containing 1.2 billion records. Now for the 8th year in a row, I offer you my technology predictions for the next year, which I hope will help you prepare for 2020. At the start of this century, 2020 still seemed so far away. To me, it felt that in 2020 we would live in a futuristic society, where we would fly from London to Sydney in a few hours, we would have flying cars, and the internet would be a place where people, organisations and machines would interact in a safe, private and secure way. Unfortunately, none of this came true. Instead, we face numerous significant societal challenges including climate change, nationalism, fake news, an AI and quantum computing...

Most companies today rely heavily on analytics, and those that can effectively understand massive amounts of data can stay on top of their industry. In just a few years, our society shifted from “analog” to “digital.” Now, it is necessary to collect information on almost anything to get much-needed value for a business. Among all this data, probably the most important is event information or what we’ve come to know as the “Internet of Events” (IoE). What Is IoE? IoE refers to all available event data. For example, in a warehouse setting, it can refer to events that occur inside a conveyor belt or an automated vehicle. It can also refer to happenings inside a transportation system. That includes checking in to a flight or buying a ticket. Essentially, these events can be machine or life events or both. IoE is a combination of: Internet of Things (IoT): This refers to all tangible objects that can connect to a network. It includes devices that can be specifically identified in ...

ScyllaDB is an open-source distributed NoSQL data store, reimplemented from the popular Apache Cassandra database. Released just four years ago in 2015, Scylla has averaged over 220% year-over-year growth in popularity according to DB-Engines. We’ve heard a lot about this rising database from the DBA community and our users, and decided to become a sponsor for this years Scylla Summit to learn more about the deployment trends from its users. In this ScyllaDB Trends Report, we break down ScyllaDB cloud vs. on-premise deployments, most popular cloud providers, SQL and NoSQL databases used with ScyllaDB, most time-consuming management tasks, and why you should use ScyllaDB vs. Cassandra. ScyllaDB vs. Cassandra ScyllaDB Cloud vs. ScyllaDB On-Premises Most Popular Cloud Providers for ScyllaDB Databases Most Commonly Used with ScyllaDB Most Time-Consuming ScyllaDB Management Tasks ScyllaDB vs. Cassandra – Which Is Better? Wondering which wide-column store to use for your...

Abnormal data trends rarely occur on their own. Influencing or related metrics are usually involved. For example, let’s say that a remote data center goes offline and doesn’t come back up. The anomaly in this case isn’t just a power failure, it’s a power failure plus a failure in a backup generator.  Some systems might show you one of these anomalies, leaving you to search for other affected metrics which can take hours, days or even weeks. Correlation, on the other hand, instantly lists related anomalies so you can quickly and painlessly understand what the leading dimension is and which metrics are impacted. If you don’t use anomaly detection, you won’t understand the cause of your outage until a support crew reaches the site. With anomaly detection, however, you can quickly discover both related anomalies, making it that much easier for you to get back online.  Finding related metrics and anomalies Behavioral topology learning provides a method for data scientists t...

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Modern consumers face a conundrum. How can they balance the benefits of technology with the risks of their sensitive data falling into the wrong hands? We are now in the era of information. Data is raising the interest of business leaders – and the concern of citizens. Every minute, over 70,000 transactions and nearly 4 million Google searches take place. Meanwhile, massive data security debacles – such as the Cambridge Analytica scandal – have left many consumers worried about the safety of their sensitive information. The Straw That Broke the Camel’s Back The 2018 Cambridge Analytica scandal shined a revealing and unsettling light on the lax data security practices of major corporations. News of the data breach first emerged through the combined investigative journalism of the New York Times, the Guardian and the London Observer in May and April of that year. The investigations revealed that a researcher purchased the private information of Facebook users from Cambridge Ana...

We write a lot about open problems in Natural Language Processing. We complain a lot when working on NLP projects. We pick on inaccuracies and blatant errors of different models. But what we need to admit is that NLP has already changed and new models have solved the problems that may still linger in our memory. One of such drastic developments is the launch of Google’s Bidirectional Encoder Representations from Transformers, or BERT model — the model that is called the best NLP model ever based on its superior performance over a wide variety of tasks. When Google researchers presented a deep bidirectional Transformer model that addresses 11 NLP tasks and surpassed even human performance in the challenging area of question answering, it was seen as a game-changer in NLP/NLU. BERT comes in two sizes: BERT BASE, comparable to the OpenAI Transformer and BERT LARGE — the model which is responsible for all the striking results. BERT is huge, with 24 Transformer blocks,...

By Lance Eliot, the AI Trends Insider Seat belts. Some people love them and feel reassured to be wearing one while inside a moving car. Others hate them and feel trapped, at times even trying to find clever ways to avoid wearing them. Most of us now know that as a driver, you ought to be wearing your seatbelt, and for which modern day cars will usually put up quite a holler if you aren’t wearing one. Grandparents Opinions About Seat Belts I remember my grandparents telling me when I was young that they normally did not wear a seat belt. They indicated that when Congress passed the Federal Motor Vehicle Safety law in the mid-1960’s making seat belts mandatory in cars, they nearly went to Washington DC to protest. Indeed, they defiantly refused to wear seat belts at all, and made a proud show of disdain for seat belts every time they got into a car. They had experienced primarily lap belts for most of their driving life. I vividly recall them buckling all of the lap belts that w...