Artificial intelligence (AI) has been changing our lives for decades, but never has it felt more ubiquitous than now.
It is a branch of computer science that aims to create intelligent machines, and is fast becoming an essential part of the technology industry. It includes several sectors and branches, such as pattern recognition, data science, machine learning, computer vision and genetic programming.
Machine learning—a method of data analysis that automates analytical model building—is a key technology in the AI sphere. Using advanced algorithms that repeatedly learn from data, machine learning allows computers to find hidden insights without being explicitly programmed about where to look.
Powering many of our daily activities are the smart recommendation systems on e-commerce platforms, image recognition systems, email spam filtering and speech recognition, to name a few.
Now that the IT world faces marked growth in computing power, there is an increased interest in machine learning. Around four years ago, a new field of research was introduced called deep learning, and it is enjoying massive success in several areas.
It is based on the use of several layers of artificial neural networks (ANN), a group of algorithms that are closely based on the understanding of human brains. Deep learning combines advanced computing power and special types of neural networks to learn complicated operations using a large amount of data. This allows systems to identify—automatically—objects in images, or words in sounds. The commercial applications for this area are only starting to be discovered.
A project that combines several fields of machine learning—as well as AI—is the driverless vehicle. This arena is a clear focus for several firms in Japan ahead of the Tokyo 2020 Olympic and Paralympic Games.
Mainly based on sensors and software to drive, the cars will be taking visitors around the city by the summer of 2020. They rely heavily on such aspects of AI as machine learning, pattern recognition and computer vision.
For instance, computer vision techniques can generate a sophisticated learning algorithm, fed with many images containing objects that will allow a car to read and understand different images. This enables it to know the kind of obstacle with which it is faced—for example, a person, another car, or a bicycle.
The cars will also rely on language processing algorithms, such as sound recognition and real-time speech translation. Thus, those in the cars can give orders to the vehicle about destinations, or can inquire about their surroundings.
These are just a few examples of the large use of machine learning and AI. In the near future, robots and machines will be able to independently carry out several tasks and complicated operations. We will also have many smart devices and IT systems available to us in all industries due to the continuous advancement of AI and machine learning.
Although AI in popular media is not always painted in the best light—whether that is via the dystopias of Hollywood, the warnings of thought leaders such as Stephen Hawking CH CBE, or the words of inventor Ray Kurzweil in his book, The Singularity is Near—the reality is that many firms are adding elements of AI to their product suites to improve our lives.
The market in Tokyo is, therefore, as vibrant an incubator for the application of AI as are other global cities. This is leading to a wide variety of exciting new career opportunities here. From automotive to telecommunications to robotics, the demand for experienced professionals with backgrounds and interests in AI is on the rise, and not set to slow down any time soon.
