Until recently, Artificial Intelligence (AI) has been confined largely to machine learning tasks. But as algorithms and hardware continue to improve, AI will become more widely implemented in everyday life. Indeed, it appears 2018 is the year that AI moves from hype to reality, allowing businesses to profit from this technology. A recent Boston Consulting Group and MIT Sloan Management Review study of 3000 business leaders found that 83% of respondents believe that AI is a strategic priority for their businesses today, and 75% say that AI will allow them to move into new businesses and ventures.

Today, AI employs neural networks to make even greater advancements. A neural network seeks to imitate the way in which the human brain learns. Such systems essentially teach themselves by considering examples, generally without task-specific programming by humans, and then use feedback to improve their performance.  The goal of these algorithms is to create more sophisticated software and machines that can help humans better live our daily lives.

In the past, the power of AI was often evaluated by how well it played games that require advanced strategy. The most famous example occurred 20 years ago when IBM’s Deep Blue beat chess champion Gary Kasparov in a six-game chess match. The ancient Chinese game of Go is even more complex, as the number of possible moves exceeds the number of atoms in the known universe. But in 2016, an AI computer program called AlphaGo, designed by Google’s AI group Deep Mind, beat the world’s No. 2 Go player in a five-game match. To accomplish this astounding feat, the program drew on hundreds of thousands of online Go games played between humans as data for a machine learning algorithm. Then, AlphaGo played the game against itself over and over, fine-tuning its strategies iteratively using a technique called reinforcement learning. As a result, a newer program, AlphaGo Zero, gained the ability to beat all previous versions of AlphaGo by learning completely from scratch, with no knowledge of how humans play the game.

Now AI is moving beyond playing games to find practical applications for these algorithms. Google’s AI group, DeepMind, is using the same techniques it used to master Go to solve more practical problems. For example, Google’s parent company Alphabet used DeepMind AI to control parts of its data centers in order to reduce power consumption. Now DeepMind is applying an algorithm based on AlphaGo Zero to other real-world applications, beginning with protein folding. Every kind of protein folds into a unique shape, and this structure specifies the function of the protein. The knowledge gained through this algorithm will help medical researchers to build drugs that better combat various viruses. This will have far-reaching implications for improving health care.

Researchers can now train neural networks within a few hours or days, opening up a staggering range of applications. Here are just a few examples:

Image recognition: In 2015, researchers discovered that machines were actually better at identifying objects in images than humans were. Google found that by using computer vision and machine learning, an algorithm could be used to automatically determine which cucumbers on a farm were ready for harvesting.

Speech recognition and natural language processing: As anyone who has used Siri or Alexa can attest, speech recognition has become highly effective at transforming human speech into a format that can be used by interactive voice response systems and mobile applications. Today, voice-driven software navigation is helping to automate tasks with simple commands. This will help dramatically decrease the time required for repetitive activities such as administrative input and medical transcription. And as machines learn how to put the right words in the right order to create clear, effective messages, natural language processing is increasingly being used in customer service to generate reports and market summaries.

Virtual assistants and chatbots: Virtual assistants or chatbots are better able to mimic human behavior than ever before. After being trained with high quality data, these algorithms can understand the nuances of language and written text. This technology is being used for customer service, eCommerce, and media delivery.

We are currently at the most exciting point in the AI revolution. The technology is no longer a lofty dream but a practical and scalable tool that every organization will be utilizing in the near future. The future is extremely bright for robotic technicians and experts who will be a key resource for companies to leverage AI advice from.