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Latest Technologies in Computer Science in 2021 - Great Learning

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The twenty-first century has seen a technological revolution. Several highly commercial and widely used technologies from the early 2000s have completely vanished, and other ones have replaced them. In 2021, many latest technologies will emerge, particularly in the fields of computer science and engineering. These latest technologies are only going to get better in 2021, and they may even make it into the hands of the average individual. These are the key trends or latest technologies to look at whether you're a recent computer science graduate or a seasoned IT professional.


How to Start a Career in Artificial Intelligence - ITChronicles

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As Frank Newport, senior scientist at Gallup, expressed it: "Whether they know it or not, AI has moved into a big percentage of Americans' lives in one way or another already." Newport made the comment in light of the results of a 2018 Gallup consumer survey. It found almost nine of ten (85%) US adults use at least one service regularly that features some element of artificial intelligence. Almost half (47%) said they used smartphone personal assistants while 32% use ride-sharing apps, such as Uber and Lyft. Twenty-two percent have home personal assistants, such as Alexa and Google Home, and 20% use smart home devices, such as smart lights or smart thermostats.


What Is Artificial Intelligence Engineering? Prospects, Opportunities, and Career Outlooks - ITChronicles

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Research conducted by Gartner suggests that artificial intelligence or AI will create a business value of US $3.9 trillion by 2022. What's more, artificial intelligence is expected to be the most disruptive technology category for the next decade, due to advances in computing power, capacity, speed, and data diversity, along with the further evolution of deep neural networks (DNN). This growth is fueling a demand for talent in a number of related disciplines, including that of artificial intelligence engineering. But what is artificial intelligence engineering? Before answering that question, it's worth stepping back a little, to look at the evolution of artificial intelligence itself, and how it is enabling new ways of doing things that new require new skill sets to implement.


Vacancy Alert: Top Machine Learning Jobs to Apply in January 2022

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This is a vacancy alert for working professionals who have specialization in machine learning and its mechanisms who are looking for a vacancy in machine learning. Multiple tech companies have created plethora of jobs in machine learning in these recent years. There are different kinds of machine learning roles to get recruited and earn a hefty salary per annum. Thus, let's explore some of the top machine learning jobs to apply for in January 2022 with the necessary skills and qualifications. Responsibilities: The machine learning engineer needs to solve a variety of technical challenges and mentor other engineers while translating business and functional requirements into concrete deliverables.


🇺🇸 Machine learning job: Director of AI/ML Engineering at Armis Industries (work from anywhere in US!)

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Director of AI/ML Engineering at Armis Industries Remote › 100% remote position (in the US) (Posted Mar 6 2022) About the company Armis Industries is a Saint Louis-based, deep technology startup developing next generation Artificial Intelligence/Machine Learning-enhanced, autonomous and unmanned vehicle systems and related data analytics technology for both government and commercial applications. Job description Armis Industries is a St. Louis-based deep technology startup focused on developing the next generation of unmanned and fully autonomous vehicle systems for aerospace, defense and industrial applications. We develop full-stack autonomous systems, with in-house physical vehicle design, command and control development, and mission information analytics and decision making. Machine Learning is the foundation of our command & control, autonomous decision making, as well as sensor data analytics capabilities. We are building machine learning systems that can operate reliably in complex, real-world environments and that can be easily adapted to new locations and missions.