Promise aside, candidates should still expect stiff competition as they reenter the now employer-driven job market. Many employers now looking to rehire want to increase the quality of the workforce with fewer recruiters. This requires new tools and innovative strategies. That's why many recruiters are turning to artificial intelligence to help assess their growing number of applicants. AI can play a major role in the virtual hiring process, from AI scheduling assistants to prehire candidate assessments to employee onboarding automation software.

The Coronavirus has drastically reshaped the economy and the labor force. Since its rapid spread around the globe, we have experienced titanic shifts in how we work, where we work, and the technologies we use to stay connected. Such massive change is escalating the importance of HR's role within organizations. Workers are turning to their managers and their HR leaders, in particular, for guidance on how to navigate their "new normal" -- research indicates that 73% of workers depend on their employer for support in preparing for the future of work. Just as CFOs have greatly increased their scope since the 2008 financial crisis, CHRO's now have that same opportunity to become central C-suite players.

We usually don't expect the image of a teacup to turn into a cat when we zoom out. But in the world of artificial intelligence research, strange things can happen. Researchers at Germany's Technische Universität Braunschweig have shown that carefully modifying the pixel values of digital photos can turn them into a completely different image when they are downscaled. What's concerning is the implications these modifications can have for AI algorithms. Malicious actors can use this image-scaling technique as a launchpad for adversarial attacks against machine learning models, the artificial intelligence algorithms used in computer vision tasks such as facial recognition and object detection.

Numbers can be multiplied, subtracted and squared in a vacuum, alone in a room. Books, too, on almost any subject, can be processed independently. Emotions, on the other hand, are typically experienced -- and learned -- in context, among people, in a social environment. That's why some California parents are concerned that virtual learning, mandated in areas that have seen a spike in coronavirus cases, might impede their school-age children's social and emotional learning. Experts agree it's not something to take lightly.

TensorFlow Extended (TFX), a TensorFlow based general-purpose machine learning platform provides orchestration of many components--a learner for generating models based on training data, modules for analyzing and validating both data as well as models, and finally infrastructure for serving models in production. The platform is particularly known for training, validation, visualization, and deployment of fresh newly trained models in production continuously relatively quickly. The individual components can share utilities that allow them to communicate and share assets.

The growth of the internet due to social networks such as facebook, twitter, Linkedin, instagram etc. has led to significant users interaction and has empowered users to express their opinions about products, services, events, their preferences among others. It has also provided opportunities to the users to share their wisdom and experiences with each other. The faster development of social networks is causing explosive growth of digital content. It has turned online opinions, blogs, tweets, and posts into a very valuable asset for the corporates to get insights from the data and plan their strategy. Business organizations need to process and study these sentiments to investigate data and to gain business insights(Yadav & Vishwakarma, 2020).

While everyone agrees on the name, there is less consensus on what predictive maintenance really means or how to implement it in industrial operations. But to truly unlock the potential of predictive and industrial maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML). Read this whitepaper to get the low down on this approach and its business value.

Developers of artificial intelligence ("AI") continue to push the technology to the next level; not a week goes by without a news story claiming that the next big thing has arrived. One popular recent example is OpenAI's latest machine learning system called GPT-3, which was trained on 45TB of text data and has been pounced upon by fellow developers and commentators alike. Its potential is vast but we are still in the early days of the AI revolution. However, as the AI available to be used grows more powerful, it becomes ever more important to consider the ethical and legal issues involved. In this context, the Information Commissioner's Office ("ICO"), the independent authority in the UK for enforcing data protection laws, has released its "Guidance on AI and Data Protection".

To help prisoners transitioning back to regular society, Purdue University Polytechnic Institute researchers are using artificial intelligence to uncover risky behaviors which could then help identify when early intervention opportunities could be beneficial. A U.S. Department of Justice study found that more than 80 percent of people in state prisons were arrested at least once in the nine years following their release from prison. Almost half of those arrests came in the first year following release. Marcus Rogers and Umit Karabiyik of Purdue Polytechnic's Department of Computer and Information Technology are leading an ongoing project focused on using AI-enabled tools and technology to reduce the recidivism rates for convicted criminals who have been released. Both are examining the forensic psychology aspect by identifying risky behaviors, stressful situations, and other behavioral and physiological factors connected to a risk of individuals returning to criminal behavior. Rogers is a professor and Karabiyik is an assistant professor in the fields of digital and cyber forensics.

The Maltese government launched its vision and strategy for AI less than a year ago, and by 2030, AI solutions will be a highly valued and trusted part of everyday life in Malta. The Malta Digital Innovation Authority (MDIA) is overseeing its implementation to build trust in how AI works and enhance the general readiness to adopt AI solutions in everyday lives. One of the key flagship projects to be launched shortly, in close cooperation with the University of Malta, is the development of Maltese language digital resources and tools. A 2013 report by Michael Rosner and Jan Joachimsen assessed the position of the Maltese language in digital media, particularly the extent to which it is used and, more importantly, the extent to which such use is supported by the deployment of tools and resources. The conclusions deduced from the results of this analysis were that the level of technological support for Maltese, compared with that for other European languages, is extremely low, giving rise to the threat of "digital extinction" for the language.