If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
"Will AI Take Control of Jobs in the Future?" you might wonder. When you ask a group of people for their thoughts, you will certainly get a range of responses. Some might argue that "no, AI will make our jobs easier," while others might argue that "yes, we will undoubtedly lose our jobs." It's a controversial issue that's been a mystery for a long time. However, since the release of COVID-19, a lot has changed in our lifestyles, businesses, and economy as a whole. AI is no exception, and it is educating us about its importance.
Today we see our working routine very different from what it was at least 10 years ago. Due to technology advancement and access to the Internet we are able to telecommute. And for many of us it has become the only alternative because of the pandemic of Covid-19. Nevertheless, even remote workers need to be supervised for sake of productivity. Here are some practical advices how to make it happen.
An expansive compound of buildings covering the equivalent of 46 football pitches was recently erected on the outskirts of Guangzhou, China's bustling southern metropolis. The sprawling complex of three-storey buildings contains some 5,000 rooms and is the first of what is expected to be a chain of quarantine centres built by the Chinese government to house people arriving from overseas as it forges ahead with its zero-tolerance approach to COVID. The compound is equipped with "5G communication technology and artificial intelligence" infrastructure, and each room, which can host only one person at a time, has cameras at its door and a robot delivery system to "minimise human contact and the risk of cross-infection", according to the introduction to the centre put out by the Guangzhou government. It took the construction team less than three months to finish the project – in an echo of the Huoshenshan and Leishenshan temporary hospitals that were built in record time in the central city of Wuhan as COVID-19 took hold in early 2020. But while those hospitals were greeted with relief, the appearance of the quarantine centre nearly two years after the trauma of Wuhan has left some wondering why China is not relaxing its virus strategy now that the vast majority of its one billion people have been fully vaccinated. They're building more facilities but there is no indication the authorities plan to ease the restrictions that have effectively ended international travel for people in China.
GRC traditionally used to be siloed, and the technology underpinning it, monolithic. How is the nature of varied risks encountered by organizations and financial institutions shifting in the changed circumstances? Post the global financial crisis of 2008, risk management as a function has evolved in shape and form, becoming a business imperative. Fast forward to 2021, and our world is going through a series of dramatic changes, as the ripple effect of unprecedented and potentially catastrophic events, like the COVID-19 pandemic. As a consequence, the global landscape of Governance, Risk, and Compliance (GRC) is becoming increasingly complex.
Covid-19 has shined a spotlight on many of the world's networks, from the internet to international air travel. But the supply chains that crisscross the world--the ships and trucks and trains that link factories to ports and warehouses, bringing almost everything we buy many thousands of miles from where it's produced to where it's consumed--are facing more scrutiny than they ever have. "It's fair to say that whatever you're selling, you've got a problem right now," says Jason Boyce, founder and CEO of Avenue7Media, a consulting firm that advises top Amazon sellers. Boyce says he has clients who would be turning over tens of millions of dollars a year if they could stay in stock. "We're having talks with clients every day where they're just crying," he says.
Researchers have mapped the web of connections underpinning coronavirus conspiracy theories, opening a new way of understanding and challenging them. Using Danish witchcraft folklore as a model, the researchers from UCLA and Berkeley analysed thousands of social media posts with an artificial intelligence tool and extracted the key people, things and relationships. The tool enabled them to piece together the underlying stories in coronavirus conspiracy theories from fragments in online posts. One discovery from the research identifies Bill Gates as the reason why conspiracy theorists connect 5G with the virus. With Gates' background in computer technology and vaccination programmes, he served as a shortcut for these storytellers to link the two.
In a school canteen in Gateshead, cameras scan the faces of children, taking payment automatically after identifying them with facial recognition. More than 200 miles away in North London, staff at a care home recently took part in a trial that used facial data to verify their Covid-19 vaccine status. And in convenience stores around the country, staff are alerted to potential shoplifters by a smart CCTV system that taps into a database of individuals deemed suspect. In each case, biometric data has been harnessed to try to save time and money. But the growing use of our bodies to unlock areas of the public and private sphere has raised questions about everything from privacy to data security and racial bias.
With 2021 just around the corner and all of us wondering what's in store for auto insurance, here are some of the trends that I believe are likely to take hold of the sector in the year to come. The aftereffects of COVID-19 will continue to shake up the insurance industry. Customers will not only favor flexible service providers, but "modular" services - meaning those that they can pick and choose features from based on their needs or even their current financial standing. For auto insurers, this could translate into policies based on the actual mileage driven as opposed to the number of drivers, or even discounts for drivers that participate in ridesharing programs. Personalization will become the new normal for insurance. Relatively, the insurance industry is pretty far behind the pack in terms of the scope of applications to intelligently process or integrate real-time data.
Coronaviruses can be isolated from bats, civets, pangolins, birds and other wild animals. As an animal-origin pathogen, coronavirus can cross species barrier and cause pandemic in humans. In this study, a deep learning model for early prediction of pandemic risk was proposed based on the sequences of viral genomes. A total of 3257 genomes were downloaded from the Coronavirus Genome Resource Library. We present a deep learning model of cross-species coronavirus infection that combines a bidirectional gated recurrent unit network with a one-dimensional convolution. The genome sequence of animal-origin coronavirus was directly input to extract features and predict pandemic risk. The best performances were explored with the use of pre-trained DNA vector and attention mechanism. The area under the receiver operating characteristic curve (AUROC) and the area under precision-recall curve (AUPR) were used to evaluate the predictive models. The six specific models achieved good performances for the corresponding virus groups (1 for AUROC and 1 for AUPR). The general model with pre-training vector and attention mechanism provided excellent predictions for all virus groups (1 for AUROC and 1 for AUPR) while those without pre-training vector or attention mechanism had obviously reduction of performance (about 5–25%). Re-training experiments showed that the general model has good capabilities of transfer learning (average for six groups: 0.968 for AUROC and 0.942 for AUPR) and should give reasonable prediction for potential pathogen of next pandemic. The artificial negative data with the replacement of the coding region of the spike protein were also predicted correctly (100% accuracy). With the application of the Python programming language, an easy-to-use tool was created to implements our predictor. Robust deep learning model with pre-training vector and attention mechanism mastered the features from the whole genomes of animal-origin coronaviruses and could predict the risk of cross-species infection for early warning of next pandemic.
FREMONT, CA: The COVID-19 epidemic ushered in a time of tremendous acceleration in the industrial sector's digital transformation endeavors. What ordinarily takes years to develop and implement took only a few months. This transition has been aided by technologies that were already available but whose adoption has been accelerated. As a result, flexible manufacturing augmented reality, predictive maintenance, edge computing, and digital thread are more widely adopted in 2021. The rate at which manufacturers respond to market changes is known as flexible manufacturing.