According to a report by IDC, worldwide spending on artificial intelligence systems is forecast to reach $35.8 billion in 2019, an increase of 44.0% over the amount spent in 2018. The report also predicts that the retail sector will lead the spending, followed by the banking sector. Artificial intelligence is well-positioned to impact various sectors like retail, healthcare, banking, finance, discrete manufacturing, transportation, etc. According to a Gartner survey, 37% of organizations have implemented AI in some way. In the early stages, AI was based on rule-based systems, in which, the AI system depended on a knowledge base of rules to deliver business value.
Deep learning is a complicated process that's fairly simple to explain. A subset of machine learning, which is itself a subset of artificial intelligence, DL is one way of implementing machine learning (automated data analysis) via what are called artificial neural networks -- algorithms that effectively mimic the human brain's structure and function. And while it remains a work in progress, there is unfathomable potential. In this article, we'll briefly explain how deep learning works and introduce the best companies in 2020. Deep learning is a subcategory of machine learning methods powered by artificial intelligence technologies.
Just a few years ago, companies used innovation and digital transformation mostly to differentiate themselves and to stay competitive. The dramatic growth in digital technologies and cloud computing over the last couple of years has since changed this mindset. Today, organizations must be innovative and leverage the latest technologies simply to stay in business. Enterprises that implement online retail, banking, and other services aren't considering these channels as just another route to increase their revenue. They realize that online services are fast becoming their primary revenue channel.
In the finance sector, for instance, AI and ML can help firms improve everything from their retail banking experience to their trading algorithms, business analytics and fraud detection protocols. But there's a catch: the promise of AI and ML technologies may not be realised unless some key enabling technologies are put in place at the outset. First, firms need a network with fast, scalable, secure and rapidly deployable connectivity. Second, they need a way to coordinate big data as it flows between public and private clouds. This need for smart connectivity stems from the special demands of artificial intelligence.
In recent times the Artificial Intelligence (AI) is the breakthrough technology. We have started learning the ways to communicate with devices. We are successful in directing machines to perform certain tasks using their intelligence. Of late, machines are performing many smarter activities using cognitive intelligence in contrast to natural intelligence (NI) displayed by human and other animals. AI is being used in many sectors and it has opened the doors of implementation of AI in many other emerging sectors.