A few months ago, I asked the question: "Are Bots and Robots the Answer to Worker Shortages?" Here are a few more from recent months: PYMNTS.com: "Record Number of Robots Sold to Help Fill Jobs" "The labor shortage triggered by COVID-19 has been a boon to robot sales as businesses scramble to fill jobs amid increasing consumer demands for goods and services post-pandemic. "Orders for robotics January through October reached 29,000 units for a record $1.48 billion compared to last year's $1.09 billion, topping 2017's record for the same time period of $1.47 billion, the Association for Advancing Automation (A3) said in a press release." International Business Times: "Robots Filling Vacant Jobs Amid Ongoing'Great Resignation'" "The U.S. is struggling with a labor shortage that is hobbling its economic recovery, but companies are not sitting still as they work to keep production up and running.

A new artificial intelligence algorithm has discovered over 300 previously unknown exoplanets in data gathered by a now-defunct exoplanet-hunting telescope. The Kepler Space Telescope, NASA's first dedicated exoplanet hunter, has observed hundreds of thousands of stars in the search for potentially habitable worlds outside our solar system. The calatog of potential planets it had compiled continues generating new discoveries even after the telescope's demise. Human experts analyze the data for signs of exoplanets. But a new algorithm called ExoMiner can now mimic that procedure and scour the catalog faster and more efficiently.

Robotics is creating a hot buzz around the world in the field of cutting-edge technologies. Thousands of robots are getting deployed to work for multiple industries to help employees, customers, patients, tourists, and so on. Educational institutes have started offering professional degrees in robotics to highly interested students. Now, these robotics professionals are receiving a plethora of opportunities to work and develop robots in countries with an RPA facility or the best research and development labs. Let's explore some of the top ten countries for robotics professionals to continue the work with robotics.

Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But like it or not, AI technologies and intelligent systems will make huge advances in the next two decades--revolutionizing medicine, entertainment, and transport; transforming jobs and markets; enabling many new products and tools; and vastly increasing the amount of information that governments and companies have about individuals. Should we cherish and look forward to these developments, or fear them? There are reasons to be concerned. Current AI research is too narrowly focused on making advances in a limited set of domains and pays insufficient attention to its disruptive effects on the very fabric of society. If AI technology continues to develop along its current path, it is likely to create social upheaval for at least two reasons. For one, AI will affect the future of jobs. Our current trajectory automates work to an excessive degree while refusing to invest in human productivity; further advances will displace workers and fail to create new opportunities (and, in the process, miss out on AI's full potential to enhance productivity). For another, AI may undermine democracy and individual freedoms. Each of these directions is alarming, and the two together are ominous. Shared prosperity and democratic political participation do not just critically reinforce each other: they are the two backbones of our modern society. Worse still, the weakening of democracy makes formulating solutions to the adverse labor market and distributional effects of AI much more difficult. These dangers have only multiplied during the COVID-19 crisis. Lockdowns, social distancing, and workers' vulnerability to the virus have given an additional boost to the drive for automation, with the majority of U.S. businesses reporting plans for more automation.

In light of the April 2021 announcement of the world's first legislative framework for regulating Artificial Intelligence (AI), the European Artificial Intelligence Act (EU AIA), now is an opportune time for developers to revisit their strategies for testing AI applications. Incoming regulations mean that the group of stakeholders who care about your testing results just got bigger and more involved. The stakes are high, not least because companies that violate the terms of the legislation could face fines higher than those levied under the General Data Protection Act (GDPR). For the purpose of transparency, certain types of AI also have to make their accuracy metrics available to users, which adds to the pressure to get functional testing right. Following on from Applause's step-by-step guide to training and testing your AI algorithm, this article summarizes how developers should be testing AI applications in anticipation of the new era of AI regulations.

On 15 November 2021, the UK Department of Business, Energy, and Industrial Strategy published the Guide for Notifiable Acquisitions under the National Security and Investment Act ("Guide"), which will come into effect on 4 January 2022. The Guide emphasizes that the National Security and Investment Act requires organizations to notify the government about acquisitions of entities involved in seventeen areas of the economy which are deemed as "sensitive,". More specifically, the Guide defines and expands on specific considerations for each of these areas of the economy and the situations that necessitate notifying the government ("Mandatory Notification"). While the Guide observes that the research and usage of advanced materials are quickly expanding in both defense and civilian sectors, its relevance to assist in the transformation of key industrial sectors and supporting key areas of high-value manufacturing are emphasized. In addition, while highlighting the substantial benefits that advanced materials provide to military capabilities, it is argued that the national security risk it poses is obvious. According to the Guide, the intersectional and dual-use character of advanced materials would also mean that developing technologies based on advanced materials would have defense and security applications and ramifications independent of the application or industry that enables them to emerge.

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner How can #AI help government transform? The whole #AIGov topic is under study and development as, - egovernment, or digital government; - smart government or igovernment; - AI government; - Global AI Global World Government; Many governments have been already governed by i-government systems, evolving from digital E-Governments to Intelligent Governments. It makes a big share in the AI industry, involving big-tech and big consulting companies as, - Huawei, Digital Government; - Oracle, State and Local Government Solutions; - SAP, Intelligent Government; Moreover, there is the whole AI World Government forum to educate and inform public sector agencies on the strategic and tactical benefits of deploying AI and cognitive technologies and gathering leaders from across government, technology innovation, business and research to present the state of the practice and state of the technology to assist the public sector in leveraging advanced intelligent technologies to enhance government services. E-government transformation initiatives are happening worldwide. Trillions of dollars and millions of hours have been spent to fix government data collection systems, move to electronic forms, and establish Internet portals.

The U.N.'s Educational, Scientific, and Cultural Organization (UNESCO) this week approved a series of recommendations for AI ethics, which aim to recognize that AI can "be of great service" but also raise "fundamental … concerns." UNESCO's 193 member countries, including Russia and China, agreed to conduct AI impact assessments and place "strong enforcement mechanisms and remedial actions" to protect human rights. "The world needs rules for artificial intelligence to benefit humanity. The recommendation[s] on the ethics of AI is a major answer," UNESCO chief Audrey Azoulay said in a press release. "It sets the first global normative framework while giving States the responsibility to apply it at their level. UNESCO will support its … member states in its implementation and ask them to report regularly on their progress and practices."

As every aspect of modern life becomes more and more digitized, not just the economies of nations, but their sovereign influence will rely more and more on their command of technology, and especially the emerging technology of artificial intelligence (AI). In the 21st-century information technology revolution, whoever reaches a breakthrough in developing AI will come to dominate the world. "Artificial intelligence is a resource of colossal power," Russian President Vladimir Putin said at AI Journey 2019 conference, a major Eastern European forum on AI held in Moscow on Nov. 9, 2019. "Those who will own it will take the lead and will acquire a huge competitive edge." Putin expressed his concern about Russia's role in the artificial intelligence race in the forum--its two competitors, the United States and China, are far ahead of other countries in the AI race. "We must, and I am confident that we can become one of the global leaders in AI. This is a matter of our future, of Russia's place in the world," Putin added. Though the United States is still the world leader in terms of AI, China is quickly moving to take its place. On Oct. 16, Nicolas Chaillan, the former chief software officer of the U.S. Air Force, told The Epoch Times that the United States is set to lose the AI race against communist China if Washington doesn't act fast.

Land surface temperature (LST) is a key parameter when monitoring land surface processes. However, cloud contamination and the tradeoff between the spatial and temporal resolutions greatly impede the access to high-quality thermal infrared (TIR) remote sensing data. Despite the massive efforts made to solve these dilemmas, it is still difficult to generate LST estimates with concurrent spatial completeness and a high spatio-temporal resolution. Land surface models (LSMs) can be used to simulate gapless LST with a high temporal resolution, but this usually comes with a low spatial resolution. In this paper, we present an integrated temperature fusion framework for satellite-observed and LSM-simulated LST data to map gapless LST at a 60-m spatial resolution and half-hourly temporal resolution. The global linear model (GloLM) model and the diurnal land surface temperature cycle (DTC) model are respectively performed as preprocessing steps for sensor and temporal normalization between the different LST data. The Landsat LST, Moderate Resolution Imaging Spectroradiometer (MODIS) LST, and Community Land Model Version 5.0 (CLM 5.0)-simulated LST are then fused using a filter-based spatio-temporal integrated fusion model. Evaluations were implemented in an urban-dominated region (the city of Wuhan in China) and a natural-dominated region (the Heihe River Basin in China), in terms of accuracy, spatial variability, and diurnal temporal dynamics. Results indicate that the fused LST is highly consistent with actual Landsat LST data (in situ LST measurements), in terms of a Pearson correlation coefficient of 0.94 (0.97-0.99), a mean absolute error of 0.71-0.98 K (0.82-3.17 K), and a root-mean-square error of 0.97-1.26 K (1.09-3.97 K).