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2022 Trends in Intelligent Bots: Knowledge Worker Empowerment - insideBIGDATA

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Whether in the form of Robotic Process Automation, chatbots, or some other type of digital assistants, the presence of intelligent bots is substantially increasing across the data ecosystem … in more ways than one. The diversification of the number of tasks these bots can perform is multiplying, as is the intrinsic complexity of those jobs, which unambiguously benefits knowledge workers worldwide. Whether dynamically engaging in natural language interactions with contact center agents, for example, or issuing and answering queries from a certified knowledge base, intelligent bots are integral for not only automating these data exchanges, but also implementing the ensuing action required to complete workflows. "Over the next one to two years we'll see tens of thousands more knowledge workers deploy digital assistants to reduce complexity, achieve error-free work, help their customers by drastically reducing their'on-hold' times and, most importantly, eliminate the frustration that arises from performing repetitive, manual tasks," presaged Automation Anywhere CTO Prince Kohli. These capabilities, of course, are naturally augmented by coupling intelligent bots with the sundry of Artificial Intelligence manifestations that are more pervasive today than they ever were before.


The use of Augmented Reality in Real Estate is no longer a gimmick

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Technology has completely infiltrated the built environment. Between IoT connectivity in buildings, indoor wayfinding and virtual tours, real estate is no longer the tech-averse industry it once was. In the context of digitization, there are new uses for Augmented Reality (AR). The technology has evolved from a marketing gimmick to a solid strategy for asset managers to improve their built environments. The premise of AR technology is the real-time integration of digital information to "augment" the user's physical experience.


Artificial Intelligence in Everyday Life

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Artificial intelligence (AI) is transforming every walk of life. Ever wondered about artificial intelligence examples that the common man is enjoying? Artificial Intelligence is a technology that has evolved so much in itself in the past few years. We can say that it has'truly' become intelligent. Artificial intelligence is a technology that makes a device smart and allows it to perform actions that simulate human beings.


Artificial Intelligence will make Indian roadways safer to travel on

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The Indian Ministry of Science and Technology said this unique approach uses the predictive power of AI to identify road hazards and a collision warning system to communicate timely alerts to drivers, to make various safety-related improvements. Artificial intelligence (AI)-powered solutions may soon make roads in India a safer place to drive. The Indian government announced on Tuesday that an AI-powered technology could reduce the risk of road accidents in the country, which have killed more than a lakh people in 2020. In a bid to prevent this from happening, the Indian government said the AI approach will use a first-of-its-kind dataset consisting of 10,000 images. He said that this dataset is finely annotated with 34 classes collected from 182 driving sequences on Indian roads obtained from a front-facing camera attached to a car driving through the cities of Hyderabad, Bangalore and their outskirts.


AI research lab inspired by computer's internal components

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Construction work is currently underway on a new artificial intelligence research laboratory designed by PLP Architecture. Located in Shanghai, China, the building's overall form is inspired by a computer motherboard and CPU. The Shanghai World Laureates Association Artificial Intelligence Lab is part of a Lingang New Area district in the city that will host research and innovation, which also happens to be where the Ring project by Ennead Architects is being constructed. The building will be situated next to a lake and feature extensive landscaping. Its interior will measure 32,000 sq m (roughly 344,000 sq ft), which will be spread over the two distinct "motherboard" and "CPU" areas.


Data on Machine Learning Described by Researchers at University of New South Wales (Learning from machines to close the gap between funding and expenditure in the Australian National Disability Insurance Scheme): Machine Learning

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By a News Reporter-Staff News Editor at Insurance Daily News -- New research on artificial intelligence is the subject of a new report. According to news reporting originating from Canberra, Australia, by NewsRx correspondents, research stated, "The Australian National Disability Insurance Scheme (NDIS) allocates funds to participants for purchase of services." Our news reporters obtained a quote from the research from University of New South Wales: "Only one percent of the 89,299 participants spent all of their allocated funds with 85 participants having failed to spend any, meaning that most of the participants were left with unspent funds. The gap between the allocated budget and realised expenditure reflects misallocation of funds. Thus we employ alternative machine learning techniques to estimate budget and close the gap while maintaining the aggregate level of spending. Three experiments are conducted to test the machine learning models in estimating the budget, expenditure and the resulting gap; compare the learning rate between machines and humans; and identify the significant explanatory variables."


John Deere closes in on fully autonomous farming with latest AI acquisition

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John Deere is announcing the acquisition of a state-of-the-art algorithm package from artificial intelligence startup Light. For those of you wondering when driverless vehicles will truly begin to make their mark on society, the answer is: today. Up front: No, you won't be seeing green tractors rolling themselves down city streets anytime soon. But the timeline for fully autonomous farming is being massively accelerated. Today's purchase is all about John Deere's need for speed -- and accuracy, but first let's talk about rapid development.


Why Artificial Intelligence Is Set Up To Fail LGBTQ People - AI Summary

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And for LGBTQ people, often marginalised by traditional systems, we need to be wary of how AI could filter us out. Indeed, one expert in the field, anthropologist Mary L. Gray, believes AI will "always fail LGBTQ people." She believes it will be up to us, to forever make sure AI not only reflects us, but the way we want our world to look too. So to understand why AI is, at least currently, set up to fail LGBTQ people, it's essential to take a step back and understand that – like in all things – it sits within a system. In Amsterdam people gathered Sunday night during a rally which was a call-to-action to all to members and allies of the trans, LGBQIA, black and brown resistance, immigrant and social justice movements to stand side by side with trans men, trans women and non-binary & intersex people, and to send a message of resistance and strengthen around the world.


Understanding Agent Environment in AI - KDnuggets

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Before starting the article, it is important to understand what an agent in AI is. The agent is basically an entity that helps the AI, machine learning, or deep reinforcement learning to make a decision or trigger the AI to make a decision. In terms of software, it is defined as the entity which can take decisions and can make different decisions on the basis of changes in the environment, or after getting input from the external environment. In simpler words, the quick agent perceives external change and acts against it the better the results obtained from the model. Hence the role of the agent is always very important in artificial intelligence, machine learning, and deep learning.