Robotic Process Automation (RPA) and Artificial Intelligence (AI) are two technologies that are often talked about in the same breath. However, while there is some overlap between RPA and AI, they are fundamentally different technologies with distinct use cases. Defining RPA and AI RPA refers to software bots that are programmed to automate repetitive, rules […]
RPA vs AI – What is the Difference? 2024 Read More »
The emerging field of quantum computing holds great promise for helping solve some of humanity’s biggest challenges, including building a more sustainable future. Quantum computers utilize the strange properties of quantum physics to perform calculations that are extraordinarily difficult or impossible for classical computers. This quantum advantage could allow us to model complex systems like
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Quantum computing is an emerging technology that leverages the strange properties of quantum mechanics to perform calculations exponentially faster than classical computers. As quantum computers become more advanced in the coming years, they are expected to revolutionize many industries and technologies. But which technologies stand to be impacted the most by quantum computing advancements? Financial
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Defining Artificial Intelligence Artificial intelligence (AI) refers to computer systems that are designed to perform tasks that would otherwise require human intelligence. AI encompasses a wide range of capabilities from basic pattern recognition to more advanced functions like language processing and strategic planning. AI systems today are considered to be “narrow” AI, meaning they are
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Business intelligence (BI) and big data are two of the most talked about technologies in the data landscape today. On the surface, they may seem similar after all, they both involve analyzing data to drive business decisions. However, there are some fundamental differences between the two that are important to understand. Defining Business Intelligence Business
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Automated testing tools have grown in importance over the last several years. Software development cycles continue to get shorter as companies emphasize releasing software faster. Manual testing alone struggles to keep up with this quicker pace of releases. However, test automation helps ensure new features and code changes don’t break existing functionality. As a result,
