The 4 Types of Artificial Intelligence That Are Revolutionizing the World

Artificial intelligence is all around us. We use it every day, from the computer, smartphone, or tablet we hold in our hands to the voice assistant on our phones. It’s also behind the vast majority of internet searches and self-driving cars. There are different types of AI that you might not have heard about before. Here, are some examples of AI that are revolutionizing the world

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is an innovative technology that has revolutionized the way of living in the society. It is a branch of computer science that focuses on the design of systems that are able to solve problems that would otherwise require the input of a human mind. Such tasks include learning, reasoning, problem solving, perception and language understanding.

The AI market is growing rapidly on the global level and is expected to reach $1,811.8 billion by 2030. This growth is due to the fact that AI is capable of processing large amounts of data in a short span of time and with high levels of accuracy thereby making it a useful tool in different fields.

Perhaps the most striking AI statistic is the projected 21% net boost to the United States GDP by 2030. This goes to illustrate the vast economic growth prospects that AI has for the global economy. Further, it is expected that AI will create as much as $15.7 trillion to the global economy by 2030.

Artificial intelligence is changing many fields. For instance, Watson of IBM is very efficient in natural language processing and knowledge acquisition. In the automotive industry, self-driving cars that have been manufactured by Tesla and Waymo are already in the market. In the domain of games, Google’s DeepMind AlphaGo stunned the world by beating human masters in the game of Go.

AI is also growing in the scientific field as well. Synbot is an artificial intelligence robotic chemist that synthesizes organic molecules. Another example is GNoME that identifies stable crystals for robotics and semiconductor production.

How Does Artificial Intelligence (AI) Work?

Artificial Intelligence, abbreviated as AI, is a section of computer science that allows computers to imitate human intelligence. It is an area that is rapidly evolving and one that is changing the face of the world as we know it with new developments being made almost on a daily basis.

AI is a process that involves the use of data to make decisions by analyzing the data and coming up with conclusions on the analysis. It is capable of solving problems that would otherwise be solved by human intelligence, including learning, reasoning, problem solving, perceiving and understanding language.

For example, AI is used in voice-controlled virtual personal assistants such as Siri and Alexa. It assists in determining which post is to be displayed to the user of the social media platform. It also allows Amazon to track the customers’ buying pattern so as to suggest what they are likely to buy next.

The fundamental technologies that drive AI are “machine learning” and “deep learning. ” Machine learning is the process by which computer systems are able to learn on their own and adapt. Machine learning, a subset of artificial intelligence, employs neural networks with multiple layers (the ‘deep’ in deep learning) to process data at multiple levels of abstraction.

Recommended reading: Are Alexa And Siri Considered AI?

The 4 Types of Artificial Intelligence Based on Functionality

Artificial intelligence (AI) is one of the most revolutionary technologies that has ever been developed. This section provides details about the four categories of AI depending on functionality. All of them have their own part in transforming different fields, including the sphere of medicine, banking, means of transport, and media.

FURTHER READING:

1. 8 Best AI Chatbot Smartest AI Chatbot in 2022

2. 8 Artificial Intelligence Companies That are Riding the Wave of AI

3. 5 Common Myths of Artificial Intelligence

1. Reactive Machines

Reactive machines are the least complex of artificial intelligence. These AI systems are developed to respond to changes in the environment in which they exist. They are specific in task, this is an input always gives a certain output.

For example, machine learning models are re-active machines because they take customer data like purchase or search history and use it to make recommendations to those customers. This kind of AI is reactive. It does “super” AI because the average person cannot process large datasets such as a customer’s history with Netflix and respond to feedback with recommendations.

A perfect example of reactive AI is when IBM’s chess-playing computer system, Deep Blue, defeated Garry Kasparov in the mid-1990s. Deep Blue was able to recognize its own and its opponent’s pieces on the chessboard to make its prediction but it lacked the memory to use its previous errors to guide its choices.

But, reactive machines have their drawbacks. They are unable to learn from past events or experiences and thus cannot use this in their reasoning. These systems are created in order to respond to certain stimuli in a specific manner according to the rules given to it and are not capable of learning.

2. Limited Memory Machines

Reactive machines are only a small part of the whole picture; Limited Memory Artificial Intelligence revolutionizes industries. In contrast to the other types of AI, these systems have the capability to retrieve, use, and even learn from past information. This capability is very useful in applications where the information from the immediately preceding time is used for predictive purposes.

Limited Memory AI can be defined as AI systems where the AI relies on past experiences or previous data to make decisions. This makes it different from the reactive machines that do not have the ability to use such data. Limited Memory AI can look into the past to observe certain objects or scenarios in the future, which gives it a learning feature that improves its decision-making.

It is important not to confuse ‘limited memory’ with the lack of storage space in these AI systems; they do not have such a problem. However, the ‘limited’ aspect here means that they can only store data for the duration of a particular task or in the course of making a particular decision. This balance between memory for learning and memory limitation for efficiency is one of the key aspects of the Limited Memory AI.

The manner in which Limited Memory AI acquires and forgets information after the task is complex. Such systems keep information for as long as it is relevant and then either refreshed or deleted. This balance between memory for learning and memory limitation for efficiency is one of the characteristics of the Limited Memory AI.

3. Theory of Mind Machines

The field of artificial intelligence is on the verge of a revolution with the introduction of Theory of Mind machines. This kind of artificial intelligence is at the moment recognized as the third level of AI and is rapidly changing how machines communicate with human beings and other intelligent systems.

Theory of Mind, or ToM, is a psychological concept that describes the capacity to understand that other people have thoughts and feelings. It is about the recognition of the fact that other people may possess beliefs, desires, intentions, emotions and thoughts which are different from ours. This is an ability that is inherent in human beings and which is now being incorporated in machines.

The inclusion of ToM in AI is not just about the enhancement of the intelligence of the machines. It is about making them more compassionate and able to foresee actions. For example, ToM AI that is installed in self-driving cars would understand the emotions and thoughts of other drivers and pedestrians, which would lower the risk of an accident.

The development of ToM AI involves two fundamental aspects: education and communication processes. The learning aspect is the usage of superior pattern recognition and knowledge from models to build intelligence with practical sense. The last aspect is the social interaction aspect. This encompasses the ability to understand human social behavior and ethics that can be applied in societies.

4. Self-aware Machines

The ultimate form of artificial intelligence is self-awareness, and it remains to be seen. Nevertheless, the process of getting to this incredible achievement is already under way. These machines when they will be invented will have consciousness and self-awareness which is a big step in the AI domain.

1. Examples of self-aware machines

The field of artificial intelligence is a broad and expanding one. One of the interesting features is the creation of machines that possess self-consciousness and can perceive themselves. Well, let’s look at some examples of each.

The best example of a self-aware machine is IBM’s Watson. This cognitive computing system does not only analyze data and give answers but also interact with humans and adapt its responses based on the response it received.

Another example of such models is GPT-4 and Midjourney among others. These models can imitate human dialogues, pass professional tests, and draw beautiful pictures using only a few words. However, the question remains: how do we make something become self-conscious? Or conscious of the fact that other things are conscious of it?

As much as self-aware AI is yet to be achieved, scientists and researchers are always striving for this great achievement. For example, there is a philosophical approach known as mechanism, which states that people are probably some sort of machine, and the fact that we are able to reason, to speak, and to understand the world around us is simply the working of some process of which we are not aware.

2. Turing test (in artificial intelligence)

The Turing Test, which was proposed in 1950, is one of the most well-known measures of a machine’s intelligence. This test was developed by a British mathematician and computer scientist Alan Turing. Specifically, it involves a human judge who is to interact through writing with both a man and a machine.

The judge’s job is to decide which of the two is a human based on the answers that they provide. If the judge cannot differentiate between the human and the machine, then the machine is said to have passed the Turing Test. This test has been used to gauge the advancement of artificial intelligence research.

However, critics have pointed out that the Turing Test is too much based on language. It does not take into account other facets of intelligence like perception, problem solving, decision making, etc. However, all these limitations do not prevent the Turing Test from being the basis for new ideas and developments in AI.

How Has Designveloper Incorporated Artificial Intelligence Into Our Work?

At Designveloper, we are always seeking for the best ways to use artificial intelligence.

How has AI been used for software development at Designveloper?

At Designveloper, we have been on the cutting edge of incorporating artificial intelligence into our software development. The members of our team have been employing the AI chat tools like ChatGPT, Gemini, and Microsoft Copilot. These tools have been used in the summarizing of documents, in the writing of specifications, in the interpretation of code. Additionally, they’re also helpful in the provision of knowledge and tools during the coding phase.

A concrete instance is the web operations team at Lumin. Our Lumin team have employed LLM to produce code for sitemap extraction, which has improved the SEO of our static pages. We have also recently begun to integrate GitHub Copilot to enhance our coding experience as well.

This is why the incorporation of AI into our work processes is something that we take very seriously. Being a leading software development companies in Vietnam, we are constantly searching for the ways to enhance and advance. With the help of artificial intelligence, we are not only increasing our productivity but also providing better quality.

Conclusion

In conclusion, artificial intelligence is not a mere trend; it is a tool that is revolutionalizing the world. While we keep on developing new and exciting applications of AI, it is imperative to confront the problems that it brings. The future of AI is bright and there is so much that can be done with it. But as with any powerful tool, it has to be used with a certain level of caution. The revolution is only now starting, and the future looks bright. So, let’s welcome this change and build the future where AI will be useful for all of us.