Full text available for a fee. The main purpose of the research reported here is to show that a new and more powerful type of computer-assisted instruction (CAI), based on extensive application of artificial-intelligence (AI) techniques, is feasible, and to demonstrate some of its major capabilities. A set of computer programs was written and given the name SCHOLAR. Due to its complexity, only the conception and educational aspects of this system (including an actual on-line protocol) are presented in this paper. IEEE Transactions on Man-Machine Systems MMS-ll:190-202

Russian Mathematical Surveys, 25, 221-262

Artificial Intelligence and other smart technologies are used to empower businesses from every industry, regardless of location. Moreover, smart technologies help companies gain an advantage in front of their competitors, so they are changing the business landscape at an increasing speed. Therefore, today we'll have a look at some of the most innovative and useful AI-based products that help businesses stay competitive and get the lead in their niche. While the logistics industry benefits from a wide range of sensors and GPS-enabled devices, the product that brought the most improvements is the AI-based dash cam for trucks. This product is mounted on a truck's dashboard and has a wide range of features that allow fleet managers to monitor drivers and optimize routes. Due to these devices, trucks get in fewer traffic accidents, transport speed has improved, and costs have dropped.

Over the past few years, there has been a growing interest in statistics and machine learning. Today, machine learning can help us make smarter decisions, and big data controls everything in our lives. It influences how we work, shop and do business. Data even help the police determine when and where the next crime is likely to happen. But how is it all happening and how did it all start?

Nowadays, practically everything around us that comes from the realm of technology appears to have some aspect of artificial intelligence (AI). Artificial intelligence, in computer terminology, is the programming and development of computers and systems capable of utilising and processing information in a way analogous to human activity. In other terms, it is a technology that allows robots to accomplish jobs that would ordinarily need human-like reasoning. Artificial intelligence offers a wide range of potential applications, including transportation, healthcare, education, agriculture, cybersecurity, and so on. It has the potential to increase worker productivity, stimulate economic growth, and improve the lives of millions of people.

Some of the world's most advanced artificial intelligence (AI) systems, at least the ones the public hear about, are famous for beating human players at chess or poker. Other algorithms are known for their ability to learn how to recognize cats or their inability to recognize people with darker skin. But are current AI systems anything more than toys? Sure, their ability to play games or identify animals is impressive, but does this help toward creating useful AI systems? To answer this, we need to take a step back and question what the goals of AI are.

Through an enormous experimental effort the structures of around 100,000 unique proteins have been determined, but this represents a small fraction of the billions of known protein sequences. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence--the structure prediction component of the'protein folding problem'--has been an important open research problem for more than 50 years. Despite recent progress existing methods fall far short of atomic accuracy, especially when no homologous structure is available.

Like it or not – artificial intelligence is here, and it is going to stay. Researchers predict that by 2020, artificial intelligence technologies will be implemented in the majority of new software products and services, which will inevitably change the way we live, work, and do business. The machine learning technology is only in its infant stage, but it has already proven its efficiency in performing routine tasks in a broad array of industries, from retail, manufacturing, and healthcare to education and cybersecurity. However, while AI can be a huge help in detecting and fighting the latest cyber threats, experts are worried that artificial intelligence techniques could also bring more risks and even fuel cybercrime. "As AI capabilities become more powerful and widespread, we expect the growing use of AI systems to lead to the expansion of existing threats, the introduction of new threats and a change to the typical character of threats," a report warns. Researchers strongly suggest that before completely trusting the benefits of deep machine learning, it's crucial to take into consideration potential misuse of the artificial intelligence technology.

Artificial intelligence is ruling the market by introducing services that will change both the customer experience and the way we look at customers. The healthcare industry consists of medical instrument manufacturers, government and private sector hospitals, clinics, pathology labs etc. And includes diagnosis, medical care, illness prevention, and wellness. The industry is expected to reach 280 billion USD by the year 2020 and around 372 billion USD by the time we reach 2022. Which will be three times larger when compared to 2017.

Suddenly, deepfakes are questioning the integrity of automated identity verification, which undeniably is the way to go for securing trust and efficiency in our digitized world. With money laundering and identity theft at stake, sophisticated anti-spoofing measures are required. While liveness detection is a trusted mechanism to secure the real user's presence, deepfakes are now creating new attack vectors. What are deepfakes even and what can biometrics do against them? And are they the real challenge for identity verification?