US intelligence community’s virus origins report is artificial, political flavoring, not science: Pakistani scholar

Illustration: Liu Rui

Editor’s Note:

Ninety days have passed since US President Joe Biden ordered for a report probing into the origins of the still ravaging novel coronavirus. On Tuesday, Biden reportedly received a classified report from the US intelligence community that was inconclusive about the origins of the novel coronavirus. It included information about whether or not the virus jumped from an animal to a human, or escaped from a lab in Wuhan. What are the US’ intentions behind its origins-tracing maneuver? Global Times (GT) reporter Wang Wenwen talked to Yasir Habib Khan (Khan), founder and president of the Institute of International Relations and Media Research in Pakistan, on these issues.

GT:  What do you think are the US’ intentions behind its origins-tracing maneuver? Why could a scientific investigation become so politicized? 

Khan: Every intension has its deep-rooted history that gives foundation to spillover action.

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Swish Data Closes Five Year, $43 Million Contract to Provide the U.S. Department of Veteran’s Affairs With Artificial Intelligence Operations Solution

MCLEAN, Va.–(BUSINESS WIRE)–Today, Swish Data Corporation (Swish), a trusted Service-Disabled Veteran-Owned and HUBZone-certified small business provider of technology solutions and engineering services to the U.S. federal government, announced that the company has been awarded a five-year, $43 million contract to provide the Department of Veterans Affairs (VA) with an artificial intelligence operations (AIOps) solution, professional services and training.

The VA required a solution to monitor the operating status of all Veteran’s Affairs Enterprise Cloud (VAEC) cloud services, containers, virtual machines and physical infrastructure and automate IT operations. In pursuit of this contract, Swish partnered with ScienceLogic to deliver their market leading, context-infused, AIOps platform.

“VA needed real-time monitoring and automation to discover, monitor, diagnose and fix infrastructure issues in the VAEC,” stated Dave Catanoso, director of the Enterprise Cloud Solutions Office at VA. “ScienceLogic has a great solution to deliver these advanced capabilities.”

ScienceLogic also has the advantage

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Artificial Intelligence, Smart Education and Learning & Learning Management System Gaining Momentum

Dublin, May 12, 2021 (GLOBE NEWSWIRE) — The “The US Postsecondary Online Education Market: Size, Trends and Forecasts (2021-2025 Edition)” report has been added to ResearchAndMarkets.com’s offering.

“The US Postsecondary Online Education Market: Size, Trends and Forecasts (2021-2025 Edition)”, provides an in depth analysis of the postsecondary online education market of the US by value and by volume. The report provides a detailed analysis of the US postsecondary online education market by institution type.

The postsecondary online education market can be segmented into undergraduate and graduate postsecondary education. Undergraduate postsecondary education is the formal education undertaken after completing the secondary school, while graduate postsecondary education generally known as post-graduation are the professional or research studies in various disciplines.

Further, the US postsecondary online education market operates with the help of three types of institutions, namely, public not-for-profit, private not-for-profit and private for-profit institutions.

The US postsecondary online education market has

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Applying artificial intelligence to science education

A new review published in the Journal of Research in Science Teaching highlights the potential of machine learning–a subset of artificial intelligence–in science education. Although the authors initiated their review before the COVID-19 outbreak, the pandemic highlights the need to examine cutting-edge digital technologies as we re-think the future of teaching and learning.

Based on a review of 47 studies, investigators developed a framework to conceptualize machine learning applications in science assessment. The article aims to examine how machine learning has revolutionized the capacity of science assessment in terms of tapping into complex constructs, improving assessment functionality, and facilitating scoring automaticity.

Based on their investigation, the researchers identified various ways in which machine learning has transformed traditional science assessment, as well as anticipated impacts that it will likely have in the future (such as providing personalized science learning and changing the process of educational decision-making).

“Machine learning is increasingly

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