Artificial Intelligence has increased the chances of hearing it throughout our lives. I understand it somehow, but I think there are many people who are vague and difficult to explain the concept. In the coming era, a basic background in AI will be indispensable. Therefore, in this article, we will explain the outline and history of AI from the basics. If you want to know about AI, please refer to it.
Basic knowledge of AI
First, let’s take a look at the definition of AI and its types.
What is AI?
AI is an abbreviation for “Artificial Intelligence”, which is an artificial reproduction of a part of human intelligence using software. However, the definition of AI has not been clearly defined at this time, and it is widely understood by academic experts. In any case, it’s a good idea to remember that it’s a computer system that mimics human intelligence.
What is machine learning?
Machine learning is one of the methods of analyzing data, and it is a technique in which a computer automatically learns from the data to find out the rules and patterns behind the data. Algorithms implemented by manual programming can be automatically constructed from a large amount of data, so they are applied in various fields.
What is deep learning?
Deep learning is one of the machine learning methods that utilize neural networks. A neural network is a mathematical model based on the neural circuits (neurons) of the human brain, and is characterized by its ability to perform more complex calculations and learning.
What is big data?
Big data means a huge group of data that is difficult to record, store, and analyze with conventional database management systems. With the widespread use of big data, it has become possible to handle data that could not be collected in the past.
What is a quantum computer?
A quantum computer is a computer that can decipher complicated calculations that cannot be solved by conventional computers by applying the phenomenon of quantum mechanics to information processing technology. Quantum computers are being researched and developed as next-generation high-speed computers.
History of AI
AI has become a word that everyone has heard once, but by the time we got here, it took many years to develop. Let’s take a look at the history and roots of AI.
The birth of AI and the first boom
The concept of AI has its roots in the book “Calculating Machines and Humans” published in 1950 by the English mathematician Alan Turing. In the same book, he asked the question, “Can machines think?” And for the first time at the Dartmouth Conference held in 1956, machines that think like humans were named “artificial intelligence.” This conference will make AI known to scientists.
The first AI boom was in the 1960s. What was researched in the first AI boom was the appearance of computers solving specific problems one after another, such as puzzles and games with clear rules, by inferring and searching using computers. .. However, when I realized that the rules were unclear and I couldn’t solve complicated problems, it gradually went down.
The second boom arrived in the 1980s
In the second AI boom that came in the 1980s, “expert systems” emerged. An expert system is a program that has knowledge in a specific specialized field and can infer and judge events like an expert. Expert systems seemed like a great approach, but the boom didn’t last long because AI at the time couldn’t handle every case accurately.
Third boom and future
In the third boom, which has continued from the 2000s to the present, the practical level of machine learning has greatly improved by utilizing big data. The existence of the research team at the University of Toronto, Canada, was the catalyst for the boom around this time. At the 2012 image recognition software competition, we used neural networks to win the championship by a large margin in second place. In the same year, a group of Google researchers published a paper on image discrimination of cats using neural networks, which is said to have triggered the third boom.
AI utilization case study
Currently, AI is widely used in various fields. Here, we will introduce familiar cases where AI is used.
Netflix recommendation feature
Netflix, a video distribution subscription service, has built its own recommendation system to increase the engagement rate of viewers, and displays thumbnails of works according to the tastes of viewers. Even for the same movie / content, what kind of image it reacts to depends on the viewer. In Netflix, the theme and actors to be emphasized are changed according to the user’s viewing history, and the most effective thumbnail is displayed, which leads to the improvement of the audience rating of the content.
Google search engine
AI technology is also used in the field of search. For example, Google, which is famous for its search engine, uses “Sematic Search”, a mechanism that analyzes the meaning of search terms and displays the optimum search results. In addition, various technologies are used, such as “entity search” that displays accurate search results even from ambiguous information, and “voice search” that supports voice search.
Image diagnosis of NTT DATA
At NTT DATA, the development of diagnostic imaging AI that streamlines the diagnosis of doctors is underway. By analyzing the medical image of the patient with AI technology and showing the potential part of the disease on the screen of the PACS system used for diagnosis, we support accurate diagnosis.
AI learning method
There are several ways to learn AI. This time, we will list three learning methods that have the highest study effect among AI learning methods.
Buy a reference book
Currently, there are many AI-related reference books out there. You can learn by yourself by using such books. By incorporating knowledge using reference books, you can feel the merits such as “information is covered”, “expressions are easy to understand even for beginners”, and “you can remember important parts while writing”. ..
Go to school
In order to acquire AI, a wide range of specialized knowledge such as machine learning, deep learning knowledge, mathematics and statistics is required. Therefore, for those who have difficulty studying on their own or who do not know what to start with, learning from a professional at school is one way to do it.
There are two types of schools, school type and online type. If you want to study more efficiently, you can use a school-based programming school, and if you want to study at home in your spare time, you can use an online school.
Introduce tools
There is also a way to introduce AI tools and learn systematically while actually operating the tools. By learning while experiencing, you can master AI in the shortest time, which also helps to improve work efficiency.
TRYETING’s “UMWELT” for business use
If you want to utilize AI for your own business, we recommend using “UMWELT” developed by TRYETING. UMWELT is a “no-code AI cloud tool” that allows you to easily analyze data and automate operations without programming. Since it is equipped with abundant algorithms, you can build your own original AI system in 3 steps: data collection, algorithm selection, and system integration. Another strength of UMWELT is that it is offered at the lowest price in the industry, so it can be introduced while keeping costs down.
summary
In this article, we introduced the outline and basic knowledge of AI, and familiar cases where AI is currently used. AI itself is still in the process of growth. Going forward, “evolution of machine learning and deep learning technology” and “further improvement of computer computing performance” will continue to solve social issues facing Japan and play a role in supporting sustainable economic growth. Why don’t you deepen your knowledge about AI in this article and use AI for your business?