The use of artificial intelligence in business is showing signs of acceleration. Nearly three-quarters of companies are now using AI (31%) or are exploring the use of AI (43%), according to IBM's "2021 Global AI Adoption Index." IT professionals responding to the IBM survey cited changing business needs in the wake of the pandemic as a driving factor in the adoption of AI at their companies. Indeed, 43% said their companies have accelerated AI rollouts as a result of the pandemic. Advances in AI tools have made artificial intelligence more accessible for companies, according to survey respondents.

At the beginning of the year, I have a feeling that Graph Neural Nets (GNNs) became a buzzword. As a researcher in this field, I feel a little bit proud (at least not ashamed) to say that I work on this. It was not always the case: three years ago when I was talking to my peers, who got busy working on GANs and Transformers, the general impression that they got on me was that I was working on exotic niche problems. Well, the field has matured substantially and here I propose to have a look at the top applications of GNNs that we have recently had. If this in-depth educational content on graph neural networks is useful for you, you can subscribe to our AI research mailing list to be alerted when we release new material.

This article explores some new and emerging applications of text analytics and NLP in healthcare. Each application demonstrates how HCPs and others use natural language processing to mine unstructured text-based healthcare data and then do something with the results. Healthcare databases are growing exponentially, and text analytics and natural language processing (NLP) systems turn this data into value. Healthcare providers, pharmaceutical companies and biotechnology firms all use text analytics and NLP to improve patient outcomes, streamline operations, and manage regulatory compliance. In fact, 26 million people have already added their genetic information to commercial databases through take-home kits.

Isn't it equal to a miracle that your upcoming actions are being predicted by computers and software? And the charm of this miracle is being spread by one of the thrilling technology that is "Machine learning". Machine learning technology does not need to be introduced as it has already made its place in the hearts of the people. But still, for the sake of the beginners, we would like to give a brief introduction to it. Machine learning is the application of Artificial Intelligence which makes the computers to predict the outcomes automatically without the intervention of human beings. In Supervised Machine learning, you are having both input and output variable and then the algorithm is used there in order to predict the output variable.

In 2017, the global software system market size for artificial intelligence (AI) was $2.65 billion. By the end of 2025, however, a new report from QY Research found that it is expected to skyrocket to $78 billion. The market concentration of AI software systems is high, and is expected to stay that way, according to the report. SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research) The US currently holds the leader position for AI consumption globally, according to a press release, and is expected to keep that title for the next few years. In 2017, the US held 35.88% of the global market, according to the report.