The use of AI is becoming indispensable for promoting corporate DX and improving business productivity. However, there are many types of AI tools, and there are differences in what they can do, so there are many people who are wondering which tool to introduce.
Therefore, in this article, we will introduce 20 recommended AI tools by category. At the same time, we will also explain how to choose AI tools so that they do not fail, so please refer to those in charge of companies that are considering introducing AI tools.
What is AI (synthetic intelligence)?
In the first place, AI ( Artificial Intelligence ) means "artificial intelligence". It refers to a computer with intelligence close to the human brain, and its main feature is that it learns on its own without human beings giving orders or instructions.
The term AI was coined half a century ago. However, in recent years, due to the evolution of computer technology, AI-related technology has developed dramatically. Here, we will explain the basics of AI, from the historical background of its birth to its impact on modern society.
Historical background of AI
The first appearance of AI in the world dates back to 1956. It is said to have been proposed by computer scientist Professor John McCarthy at the Dartmouth Conference held in the United States. After that, AI research began to flourish, and the first artificial intelligence boom occurred from the late 1950s to the 1960s.
However, the technology at that time was not able to solve the complicated problems, so we entered the winter era.
After that, in the 1980s, the second artificial intelligence boom occurred. By giving computers knowledge, AI has been programmed to act like an expert in its field. However, at that time, computers could not collect information by themselves, and it was necessary to describe the contents so that humans could understand them. As a result, it did not spread due to problems such as the limited scope of its use, and the winter era came again from around 1995.
Since the beginning of the 2000s, there has been a third artificial intelligence boom. The impact of AI on society is increasing, such as deep learning, automatic collection of information by crawler bots, and presentation of answers to human questions by AI chat.
About the development of modern AI technology
As of 2023 when I wrote this article, we are in the midst of the third artificial intelligence boom. In particular, what sparked the boom was "machine learning," in which AI itself acquires knowledge from large amounts of data (big data). Advances in the practical application of machine learning in all business fields have brought dramatic improvements in business productivity.
From 2022 onwards, ``Image Generation AI'', in which AI generates new images, and ``ChatGPT,'' in which natural sentences are automatically generated in response to human questions, have appeared. In this way, AI technology is not only handled by experts, but is starting to spread to the point where anyone can use it in familiar life scenes.
What impact will the development of AI have on modern society?
In recent years, with the development of AI technology, AI is beginning to spread in our daily lives. Things that have been done manually by humans can now be automated through the use of AI, allowing humans to spend their time doing other things.
On the other hand, there are many people who are worried about future work and life, such as "Will human jobs disappear as AI develops?"
Certainly, there is a high possibility that AI will be able to replace "routine work" such as calculations and information collection and organization, which AI is good at. If it is a simple text entry or inquiry response, it is more efficient to leave it to AI without mistakes.
However, it is unlikely that AI will replace everything that humans do. Most of the AIs currently being developed are problem-solving specific, meaning they cannot define or handle problems on their own. Also, AI is not good at reading other people's feelings and reading between the lines.
Therefore, rather than worrying too much about losing jobs to AI, it will be necessary to identify what only humans can do and use AI to improve the accuracy of work.
In any case, there is no substitute for the importance of skillful use of AI. In recent years, AI tools that can easily handle AI even for those who do not have specialized knowledge have appeared one after another, so we will be in an era where it is even more necessary to master how to use AI tools.
Types of AI tools
There are various types of AI tools. Current AI tools can't do everything with one machine like "Doraemon". Each AI tool has its own model, and each corresponds to a different field.
Therefore, it is necessary to select an appropriate AI tool according to the issues and objectives of the company. Here, I will briefly explain what you can do with AI tools.
machine learning
Machine learning is a technology that allows computers to learn on their own without human intervention. For example, if you give it a picture of a dog or a cat, it will automatically classify them. By giving a lot of data, the computer will automatically find patterns and learn the rules.
Machine learning extracts rules from large amounts of data without human intervention. This technology is used in various fields such as autonomous driving, voice recognition, and image recognition. However, it requires accurate data and can be slow to train in order to get correct results.
deep learning
Deep learning is a type of machine learning, and is a technology that can solve problems with high accuracy by processing large amounts of data. It is used in fields such as image recognition, speech recognition, and natural language processing.
Although it makes data preprocessing easier than traditional techniques, it requires large amounts of data and high computational power, and can be costly to implement.
natural language processing
Natural Language Processing (NLP) is a technology that allows computers to process human language. It understands meaning from text and is used for automatic translation, sentence generation, sentiment analysis, information retrieval, speech recognition, etc. NLP is done using techniques such as machine learning and deep learning. Today, it is used in fields such as business, medicine, law, government, and education.
But words are ambiguous and cannot be fully automated. Also, using NLP requires a large amount of data and advanced computational processing power.
image recognition
Image recognition is a technology that allows a computer to look at a photo or video and determine what is in it. Using technologies such as machine learning and deep learning, it automatically learns the patterns and features in photos and videos, and can identify even unknown objects with high accuracy.
Currently, it is used in surveillance cameras, self-driving cars, medical inspections, product inspections, face recognition, and other scenes. However, recognition may be difficult due to resolution, lighting conditions, angles, and hidden areas. Therefore, in order to improve accuracy, ensemble learning that combines multiple methods and learning using many photographs and videos are necessary.
Other AI tools
There are various types of AI tools besides machine learning, deep learning, natural language processing, and image recognition.
For example, a robot framework for controlling robotics, a speech synthesis engine for realizing speech synthesis technology, a sensor data processing tool for analyzing sensor data of an autonomous vehicle, or a customer for predicting customer behavior. analytic tools, etc.
Since these tools are specialized in their respective fields, they have different functions and features. For example, the robot framework specializes in robot motion control and sensing, and the sensor data processing tool specializes in real-time sensor data processing. In addition, customer analytics tools have the ability to visualize business data and support business decision making.
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