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The Future of Enterprise Billing

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The connectivity benefits of 5G are expected to make businesses more competitive and give consumers access to more information faster than ever before. Connected cars, smart communities, industrial IoT, healthcare, immersive education--they all will rely on unprecedented opportunities that 5G technology will create. The enterprise market opportunity is driving many telecoms operators' strategies for, and investments in, 5G. Companies are accelerating investment in core and emerging technologies such as cloud, internet of things, robotic process automation, artificial intelligence and machine learning. IoT (Internet of Things), as an example, improving connectivity and data sharing between devices, enabling biometric based transactions; with blockchain, enabling use cases, trade transactions, remittances, payments and investments; and with deep learning and artificial intelligence, utilization of advanced algorithms for high personalization.


Write a Few Lines of Code and Detect Faces, Draw Landmarks from Complex Images MediaPipe

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It's time to make our hands dirty with a hands-on face detection model using MediaPipe. To perform face detection you have to install MediaPipe at first in your machine. If you are a windows user then you can run the below code in your computer's command prompt. You also need to install OpenCV for webcam or image input. If you are a windows user, you can run the below code in your command prompt.


Reasons for the Rise of Voice AI Strategy Adoption in Businesses

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The latest Voice AI trend has been evolving day by day by adding value to third-party platforms such as Alexa or Google for implementing omnichannel voice AI experiences with the help of voice assistants to enhance customer experiences. According to the latest survey, 46% of the businesses across various industries are not sure about the change voice technology could bring into their organizations. Though this is the same case with the consumers, over the adoption of voice user interfaces emerges to increase at an expanding rate. According to Statista, the number of digital voice assistants is likely to reach 8.4billion units by 2024, which is more than the world's population. This is due to the increasing demand for Voice AI assistants for better convenience and accessibility.


Now You Can Use Any Language With IBM Watson Assistant

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When venturing into the field of chatbots and Conversational AI, usually the process starts with a search of what frameworks are available. Invariably this leads you to one of the big cloud Chatbot service providers. Most probably you will end up using IBM Watson Assistant, Microsoft LUIS/Bot Framework, Google Dialog Flow etc. There are advantages…these environments offer easy entry in terms of cost and a low-code or no-code approach. However, one big impediment you often run into with these environments, is the lack of diversity when it comes to language options. This changed 17 June 2021 when IBM introduced the Universal language model.


An AI-Controlled Drone Racer Has Beaten Human Pilots For The First Time

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Drone racing is an increasingly popular sport with big money prizes for skilled professionals. New control algorithms developed at the University of Zurich (UZH) have beaten experienced human pilots for the first time – but they still have significant limitations. In the past, attempts to develop automated algorithms to beat humans have run into problems with accurately simulating the limitations of the quadcopter and the flight path it takes. Traditional flight paths around a complex drone racing course are calculated using polynomial methods which produce a series of smooth curves, and these are not necessarily as fast as the sharper and more jagged paths flown by human pilots. A team from the Robotics and Perception Group at UZH has developed a trajectory planning algorithm to calculates the optimal route at every point in the flight, rather than doing it section by section.


Discourse on the Philosophy of Artificial Intelligence and the Future Role of Humanity

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Artificial intelligence can be defined as "the ability of an artifact to imitate intelligent human behavior" or, more simply, the intelligence exhibited by a computer or machine that enables it to perform tasks that appear intelligent to human observers (Russell & Norvig 2010). AI can be broken down into two different categories: Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI), which are defined as follows: ANI refers to the ability of a machine or computer program to perform one particular task at an extremely high level or learn how to perform this task faster than any other machine. The most famous example of ANI is Deep Blue, which played chess against Garry Kasparov in 1997. AGI refers to the idea that a computer or machine would one day have the ability to exhibit intelligent behavior equal to that of humans across any given field such as language, motor skills, and social interaction; this would be similar in scope and complexity as natural intelligence. A typical example given for AGI is an educated seven-year-old child.


The Basic Idea of Machine learning, Deep Learning, and Artificial Intelligence

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The basic idea of machine learning, deep learning, and AI is to abstract real-life problems into computerized models, then use mathematical methods, statical analysis, or computer algorithms to solve real-life problems.


The Adoption of AI and Machine Learning in Healthcare: What is the Right Way to Proceed?

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The artificial intelligence (AI) and machine learning is getting stronger than ever. Many applications and projects have been developed based on AI already. Take the example of Apple Siri or the advertising algorithms that pushes products and services based on our Google search. The question though is, can AI take the place of a human and replace him or her?! Some believe we will be able to teach a robot or artificial material to perform tasks quickly and efficiently than a human. The idea falls on the line of a screwdriver where we use it because we cannot unscrew just by using our bare hands.


Using Machine Learning to Increase the Accuracy of your Questionnaire or Calculator

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In this article, I will help you use machine learning alongside your calculator or questionnaire to learn more about your users. After reading, you will know everything you need to fill in the blanks of optional questions with educated guesses as to what users might have responded. I used Python Pandas to do so, but all concepts should carry over to any language you're using. Thus, continue reading if you check the following boxes. You want to improve the accuracy of your calculator or quiz's results Great -- lets dive in!


Natural Language Processing: NLP In Python with Projects

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We have covered each and every topic in detail and also learned to apply them to real-world problems. There are lots and lots of exercises for you to practice and also 2 bonus NLP Projects "Sentiment analyzer" and "Drugs Prescription using Reviews". In this Sentiment analyzer project, you will learn how to Extract and Scrap Data from Social Media Websites and Extract out Beneficial Information from these Data for Driving Huge Business Insights. In this Drugs Prescription using Reviews project, you will learn how to Deal with Data having Textual Features, you will also learn NLP Techniques to transform and Process the Data to find out Important Insights. You will make use of all the topics read in this course. You will also have access to all the resources used in this course. Enroll now and become a master in machine learning.