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AI and the future of tech support

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A few years ago, one of our high-tech manufacturing clients found their tech support staff was responding to a high volume of L1 support calls from users about whether particular applications were down, or to reset passwords or provisioning access to new applications. The client wanted to explore solutions through our innovation center of excellence to see whether there was a more efficient way to handle routine requests without impacting user satisfaction. In response, we developed TEKsystems.sAIge, For example, if a user types, "I can't access the lead management system," the machine understands the intent of the message and passes on the context to an AI engine to analyze. If the machine is down, the chatbot communicates the reason to the user--or restarts the services through automation scripts that are predesigned to execute tasks.


Artificial skin heals wounds and makes robots sweat

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Imagine a dressing that releases antibiotics on demand and absorbs excessive wound exudate at the same time. Researchers at Eindhoven University of Technology hope to achieve just that, by developing a smart coating that actively releases and absorbs multiple fluids, triggered by a radio signal. This material is not only beneficial for the health care industry, it is also very promising in the field of robotics or even virtual reality. TU/e-researcher Danqing Liu, the lead author of this paper, and her Ph.D. student Yuanyuan Zhan are inspired by the skins of living creatures. Human skin secretes oil to defend against bacteria and sweats to regulate the body temperature.


Fraud Detection with AI and Machine Learning

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Obviously, the methods of past years have ceased to be effective. Even Fraud Detection with AI and Machine Learning is neither a magic pill nor an absolute guarantee of protection. However, nothing better was invented at the moment, so it makes sense to learn how ML solutions and fraud detection analysis can make your business more secure, and your customers more confident in your services. The very concept of detecting fraud using machine learning is based on the idea that legitimate and illegal actions have different characteristics. Moreover, these signs can be completely invisible to the human eye. The machine learning system for recognizing fraud proceeds from its knowledge of the legitimate operation, compares this knowledge with events occurring in real-time and draws a conclusion about the validity or illegality of a certain action.


How AI Is Impacting Operations At LinkedIn

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LinkedIn has been at the cutting edge of AI for years and uses AI in many ways users may not be aware of. I recently had the opportunity to talk to Igor Perisic, Chief Data Officer (CDO) and VP of Engineering at LinkedIn to learn more about the evolution of AI at LinkedIn, how it's being applied to daily activities, how worldwide data regulations impact the company, and some unique insight into the changing AI-related work landscape and job roles. Very early on at LinkedIn, data was identified as one of the company's core differentiating factors. Another differentiating factor was a core company value of "members first" (clarity, consistency, and control of how member data is used) and their vision to create economic opportunity for every member of the global workforce. As LinkedIn began finding more and more ways to weave AI into their products and services, they also recognized the importance of ensuring all employees were well-equipped to work with AI as needed in their jobs.


19 Frameworks, Libraries, and Tools That Developers Love (and Hate)

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Developers generally exhibit a strong affinity (usually paired with an equally strong hatred) for certain frameworks, libraries, and tools. But which ones do they love, dread, and want the most? Stack Overflow, as part of its enormous, annual Developers Survey, asked that very question, and the answers provide some interesting insights into how developers work. Some 65,000 developers responded to the survey, and the sheer size of that sample makes these breakdowns a bit more interesting to parse. For example, although game developers might have strong opinions about Unreal Engine and Unity 3D (which placed high on the following lists), those aren't used at all by the bulk of developers concerned with A.I. and machine learning, who have strong feelings about TensorFlow that many other developers might not share.


Security Think Tank: Get your house in order before deploying AI

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It is true to say that AI and ML offer great promise when it comes to organisational security measures. A predictive security stance may be some way off for many businesses and the belief that AI or ML will dissolve existing poor practice or protocols is as widespread as it is erroneous. Before really talking about AI and ML, we must talk about bias and the impact it has on quality outcomes from either technology. Bias will simply double down on any practice or protocol in place and reinforce it, good or bad. You don't have to look very far to see an example of how it can go wrong if you have not considered the bias problem – Amazon was forced to scrap its experimental AI recruitment tool, as it eventually decided the best people for its roles were pretty much just men.


Experimental AI regime to be introduced in Moscow

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Moscow City Hall has been instructed to determine the conditions, requirements and procedure for the development, creation, introduction and implementation of artificial intelligence technologies, as well as the cases and procedures for using the results of the application of artificial intelligence. It is expected that large IT companies using artificial intelligence in the field of medicine, urban infrastructure, face recognition and other uses will take part in the experiment. The Law separately outlines certain provisions relating to the storage and processing of personal data that will be obtained during the experiment. As a result, the Law makes it possible to use the previously anonymised personal data of individuals participating in the experiment to increase the effectiveness of the state or municipal government. However, the Law specifically establishes that such personal data can only be transferred to participants in the experiment and must be stored in Moscow.


How the cloud transforms customer experience in financial services

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A McKinsey survey looking at the banking, auto insurance, retail energy, health insurance, and mobile communications sectors found that the quality and availability of digital interactions have a significant impact on customer satisfaction. Adding digital offerings is crucial to what consumer-facing companies must do to remain competitive in the face of increased customer expectations. However, some organisations still only offer basic digital services, and not all have created integrated, omnichannel experiences. Companies that use technology to transform customer experience have increased customer satisfaction by 15 to 20%, reducing cost to serve by 20 to 40%, and boosting conversion rates and growth by 20%. As consumers have come to expect the same experience of their financial services providers that they have elsewhere in their lives, traditional financial institutions (FIs) are increasingly looking for ways to improve customer service and deepen engagement.


Artificial Intelligence In Wealth Management To Provide Hybrid Services

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Artificial Intelligence (AI) refers to intelligent machines that work and react like humans. AI helps to deliver insights to complex client questions in real time through its virtual conversational interface between business and clients. AI enabled applications such as natural language generation (NLG) is closing the gap between data analysis and investment decisions, providing real-time insights through automated trading strategies. For instance, according to a survey in 2018 by Forbes, 34% of wealth management companies have currently deployed AI within their firms and around 99% plan on deploying AI within the next 3 years. Companies such as Wells Fargo and Bank of America have already deployed AI services to better serve clients.


The Impact of Artificial Intelligence on Human Rights

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Adopting AI can affect not just your workers but how you deal with privacy and discrimination issues. As humans become more reliant on machines to make processes more efficient and inform their decisions, the potential for a conflict between artificial intelligence and human rights has emerged. If left unchecked, artificial intelligence can create inequality and can even be used to actively deny human rights across the globe. However, if used optimally, AI can enhance human rights, increase shared prosperity, and create a better future for us all. It is ultimately up to businesses to carefully consider the opportunities new technologies provide and how they can best leverage these opportunities while being conscious of the impact on human rights.