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Sr. Data Engineer

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Role Description: The Rackspace FinOps group enables cloud users to align their cloud technology adoption with their business strategies. We advise many of the world's largest AWS, GCP, Azure, and other Cloud consumers on topics ranging from cloud architecture to organizational governance to cloud economics, driving efficient cloud adoption and usage for our clients. The FinOps Data Engineer role is an exciting opportunity to build solutions that will help us and our clients turn complex multi-cloud cost and performance datasets into actionable insights. This is an opportunity to make an impact on a fast-growing team. You'll be instrumental in creating new and better analytics and ML solutions, and generally innovate to drive new value for our clients.


NAVWAR Launches Second Project Overmatch Prize Challenge; Aimed at Identifying Artificial …

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When it comes to the future of AI, the National Security Commission on Artificial Intelligence Final Report issued in March 2021 year contends, "The best …


Interdisciplinary Centre For Artificial Intelligence

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The Interdisciplinary Centre for Artificial Intelligence was established in the year 2019 in the Faculty of Engineering and Technology after the approval by the Executive Council, Aligarh Muslim University. One of the major objectives of the establishment of this Centre is to promote interdisciplinary research and development activities in Artificial Intelligence and its allied fields including Machine learning, Data Analytics, Natural language processing, etc. The faculty members attached to this Centre are from different fields of Engineering and Science with international exposure and a good publication record. The Centre aims to conduct masters and doctoral research programmes in the area of Artificial Intelligence. The Centre is poised to prepare the students to demonstrate technical competence in their profession by applying knowledge of contemporary advances in AI for providing practical and innovative solutions.


What Google's AI-designed chip tells us about the nature of intelligence

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In a paper published in the peer-reviewed scientific journal Nature last week, scientists at Google Brain introduced a deep reinforcement learning technique for floorplanning, the process of arranging the placement of different components of computer chips. The researchers managed to use the reinforcement learning technique to design the next generation of Tensor Processing Units, Google's specialized artificial intelligence processors. The use of software in chip design is not new. But according to the Google researchers, the new reinforcement learning model "automatically generates chip floorplans that are superior or comparable to those produced by humans in all key metrics, including power consumption, performance and chip area." And it does it in a fraction of the time it would take a human to do so. The AI's superiority to human performance has drawn a lot of attention.



Infrastructure Site Surveying Gets a Boost From Artificial Intelligence

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EMerald Geomodelling seeks to speed the process by letting an A.I. use its machine-learning to predict the subsurface geology of the site and reduce …


A Conversation with Teckro's Newest Leadership Hires

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World-class talent makes a company not only successful on paper but also an exciting and energetic place to work. In the nearly six years I've been with Teckro, we continue to expand our leadership team and bring on many talented new hires across all disciplines – engineering and product, our services team, and many new faces on the commercial side. Today we introduce two of our newest "Teckronauts" – Malia Lewin and Silvina Baudino, both joining to scale our global market strategy. Malia: Right now, the life sciences industry is leveraging technology to change the game of scientific discovery. There are beautiful, sophisticated, amazing things happening in the lab, but these are often hampered from getting to market and saving the lives of patients because of old, slow, paper-based models.


How Will Artificial Intelligence and Cybersecurity Be Seen Moving Forward?

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While AI can effectively mitigate threats and prevent potential cyberattacks, criminals can also exploit the technology to their advantage – putting …


Online panel: Digital Twins Leverage the Power of IoT

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Digital Twins are a digital representation of physical assets that utilize IoT data, enabling use cases such as predictive maintenance. Juniper Research expects that total global spend on Digital Twins will reach $12.7 billion by 2021; an increase of 17% from $10.8 billion in 2019. Manufacturing will be the single biggest sector for Digital Twins deployment; accounting for 34% of total spend in 2021, followed by energy & utilities at 18%. Digital Twins are not standalone products, and so must be implemented as part of a wider Industrial IoT strategy. While IoT sensors generate enormous amounts of data in the industrial setting, interpreting this data and putting it into operation requires a collaborative approach based on open platforms.


Google Artificial Intelligence Team Draws From Critical Race Theory, Internal Document Shows

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Google's artificial intelligence (AI) work draws from Critical Race Theory, a philosophical framework that posits that nearly every interaction should be seen as a racial power struggle and seeks to "disrupt" American society which it views as immutably racist, according to a company document obtained by The Daily Wire. A screenshot of an internal company page, obtained by The Daily Wire, says under the header "Ethical AI": We focus on AI at the intersection of Machine Learning and society, developing projects that inform the general public; bringing the complexities of individual identity into the development of human-centric AI; and creating ways to measure different kinds of biases and stereotypes. Out [sic] work includes lessons from gender studies, critical race theory, computational linguistics, computer vision, engineering education, and beyond! Google's Ethical AI team appears intent on encoding far-left ideology into its algorithms even after previous leaders of the team plunged the section into chaos over their insistence on overlaying progressive politics onto mathematics. Until recently, the team was co-led by Timnit Gebru, who cofounded a "Black in AI" racial affinity group and in 2018 coauthored a paper saying facial recognition technology was less accurate at recognizing women and minorities.