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What Is Artificial Intelligence?

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2023 was a year of the Artificial Intelligence or AI in short. Most of the leading tech companies made their AIs, the most common names are ChatGPT (OpenAI), Bard (Google), Bing (Microsoft) and so on. Facebook’s and Elon Musk’s AI is still on the way. They are reaching popularity and more and more people uses them to help their work or just learn by them. But do we know really what is Artificial Intelligence? In this article we try to dive deep in this topic and introduce AI deeply.

What Is Artificial Intelligence?

Artificial Intelligence, or AI, represents a significant advent in technology, marking a new era of automation and advanced computer systems. It’s about making machines smart so they can do things on their own, like understanding what we say by speech recognition. Experts in data science and computer programs work hard to teach machines to learn and make smart choices using a vast amount of data.

There are two main kinds of AI: strong AI and weak AI. Strong AI, also called Artificial General Intelligence (AGI), tries to make machines that can do anything a person can do with their brain. Weak AI is different. It’s made to be really good at certain things, but it doesn’t really think or know things on its own. So strong AI is much closer to the human intelligence.

The big goal in making AI is to reach AGI. This means AI could do any brain work that a person can, including tough problems that usually need a person’s help. AGI would know how to learn and understand lots of different things, just like a human brain.

AI technology shows up in different ways in our lives. For example, there’s machine learning, a key component of generative AI, utilizing complex algorithms. This is where computers get better at something by learning from information. Then there’s Natural Language Processing (NLP), which helps AI understand and make sentences like a human. This is important for things like Siri or Alexa, our talking phone helpers.

what is artificial intelligence?

Another important part is computer vision. This breakthrough in computer vision has led to significant advancements in fields such as image recognition and automation. This is where AI can understand what it sees, like pictures or real-world scenes. In 2023, this is really big in AI and helps with things like self-driving cars and face recognition.

AI is also really good at recognizing images. It’s getting better at understanding pictures. Deep learning is a special kind of machine learning. It’s more complex and works kind of like how our brains think and make decisions. This technology is in many things we use today, like voice assistants, self-driving cars, and even advanced health tools.

As AI improves, it’s exciting but also makes us a bit worried. It’s great for health care, education, money stuff, and transportation, helping to make things better and solve big problems. But we also have to think about how it might change jobs, keep our personal information safe, and make sure it’s used the right way, especially in making decisions that are usually made by people. AI’s growth relies heavily on the compute power and large data sets available, which are essential for advanced AI algorithms.

What are the 4 types of artificial intelligence?

We call all the “thinking machines” AI, however they can be separated by its types. Let’s figure out what are the four types of AI exist.

Reactive Machines

One of the four types Reactive Machines are the simplest form of AI. A notable application of this AI type is in expert systems, where they provide specific, tailored responses to certain situations. They works based on the current data or inputs they receive, without any ability to use past experiences to inform future decisions.

A classic example is IBM’s Deep Blue, the chess-playing computer that defeated Garri Kasparov, a world chess champion in 1997. Deep Blue analyzed the chessboard in real-time and determined the best possible move from that specific situation. It didn’t learn from past games or plan for future moves. This type of AI is highly specialized and efficient at the task it’s designed for but lacks the ability to go beyond its programming.

Limited Memory

Limited Memory AI is a smarter kind of AI that can remember recent things for a short while. This AI type is crucial in fields like robotics, where it helps machines react adaptively to their environments. It uses recent info to make quick choices. For example, IBM Watson uses this type of AI in various AI applications like healthcare diagnostics and business analytics.

An other example is self-driving cars. They constantly check things like how far away they are from other cars, how fast they’re going, and which way they’re moving. They use this info right away to decide how to drive. But these cars don’t hold onto these memories for a long time. They can’t use old information to guess what might happen in the future.

Theory of Mind

Theory of Mind AI is a big idea that we’re still just thinking about, not something we have in real life yet. A smart English guy named Alan Turing, who was a great mathematician and computer scientist, came up with a test called the Turing test. It checks if a machine can act so smart that it seems like a human.

The goal is to make AI that really understands how people feel and think. This isn’t just about hearing words. It’s also about getting things like facial expressions and body language. We hope that AI can one day chat with people by really getting their feelings and responding in a way that shows it understands, just like how we talk to each other.

What is Artificial Intelligence - Alan Turing
Picture: Alan Turing (1912-1954) | Source: Wikipedia

Self-aware AI

Self-aware AI is the most fancy and imagined kind of AI. This idea comes from a big meeting called the Dartmouth Conference, where people first started talking about ‘Artificial Intelligence.’ This kind of AI would know it exists and even have feelings. It would understand its own emotions, think about itself, and know what it’s feeling inside. These AI systems would have their own wants and personalities. But right now, this is more like something you’d read in a sci-fi book. It’s way smarter and more complicated than anything we can make today.

What are the applications of AI in today’s world?

Let’s explore how Artificial Intelligence (AI) is changing things in many areas of our lives. AI is like a smart helper, making things easier and better in different ways:

Customer Support: AI is a big help in customer service. It uses chatbots and virtual helpers to answer people’s questions quickly and 24/7. These AI tools get better as they talk to more people, giving better answers each time. They make things faster for customers and easier for the people working in support.

Healthcare: In hospitals and clinics, AI is like a super smart doctor’s assistant. It helps find diseases quickly and suggests the best treatments. AI looks at health records and can spot things that might be missed. It helps in check-ups, making medicines, and even in operations, making sure patients get really good care. Interestingly here blockchain technology connects with AI as all the sensitive data could be stored and managed on a blockchain. This can help to improve patient privacy and security.

AI in Business: Businesses use AI to stay ahead. AI employs advanced problem-solving strategies to analyze market trends and customer preferences, making it invaluable in business analytics. It can do routine jobs, predict sales, and make ads that speak directly to what customers want. This helps businesses work better, save money, and sell more.

Smart Cars: In the world of cars, AI is behind the wheel of smart cars, including those that drive themselves. It uses information from all around to make safe driving choices. AI in cars is not just about driving on its own, but also about making the whole driving experience better, like reminding you when your car needs fixing. Or even automated driving that doesn’t require human intervention.

Homes: In our homes, AI is in smart devices that learn what we like. It can turn lights on and off, change the temperature, and keep our homes safe, all by itself. It knows what we need and helps make our homes more comfortable and energy-saving.

Art and Creativity: AI is also getting creative. It helps artists and designers make new kinds of music, paintings, and even stories. AI can come up with its own artworks, adding a fresh twist to creativity. It’s not taking the place of artists but giving them new ways to create.

AI Keeping Us Safe: For safety and watching over places, AI is really useful. It can look at video feeds and spot anything unusual, recognize faces, and track objects. This makes public places safer. AI is also used in keeping computers safe, finding and stopping security threats faster than before.

In all these ways, AI is like a super smart helper, making life easier and better in many areas. As AI keeps growing, it’s likely to become an even bigger part of our everyday lives.

The History of AI? – From 1957 To Present

The story of AI goes way back, even to ancient times when people wondered about thinking and being aware. Around the 3rd century BC, a Chinese thinker named Xunzi talked about making machines that could act like humans. In the 17th century, a French thinker, René Descartes, imagined a machine that could think and reason.

The first phase is the golden age of AI (1957-1974). This time was really good for AI. People were hopeful and made big steps forward. Computer experts were busy creating programs that could solve math problems and start to understand simple human talk. It was an exciting time, and many thought smart machines were just around the corner. Governments and businesses gave a lot of support and money for AI projects. AI grew fast, and everyone thought it would soon do even more amazing things.

But then the AI winter came (1974-1980s), when AI hit a rough patch known as the AI Winter. The excitement cooled down as AI couldn’t meet everyone’s high expectations. It struggled with tougher problems, and the computers back then just weren’t strong enough. Because of these issues, money for AI research got scarce, and interest in AI dropped a lot.

In the 1980s, things got better for AI. Researchers started focusing on more realistic goals. They used AI to help find information fast and to figure out health problems. Computers were also improving – they were quicker and held more data. This helped AI bounce back. AI began to be used more, like in making cars and planning the best ways to deliver goods and services.

Then, in the 1990s, a part of AI called machine learning really started to shine. It was all about teaching computers to learn from tons of data. The internet was a big help for AI because it gave so much information for AI to learn from. AI got better at understanding speech and recognizing things in pictures. Big companies invested a lot in AI. This led to some cool things we see today, like voice helpers on our phones and movie suggestions on streaming sites. AI wasn’t just a dream anymore; it became a big part of our everyday digital life.

What’s Next for AI?

Looking forward, AI has a lot of exciting and tricky roads ahead. It could change the way we work and live in huge ways. There are big hopes, like AI making our health care really personal and helping fix big problems with the environment. But we also have to think about keeping people’s information private, what happens to jobs, and making sure AI is fair and safe. The next steps in AI are about making the most of its power while also being careful to use it in a way that’s good for everybody.

What is ChatGPT and its relationship to artificial intelligence?

ChatGPT is a cool example of conversational AI that shows how AI can work with languages, like how we talk and write. It’s a type of AI model called GPT (Generative Pre-trained Transformer), made by a group named OpenAI. ChatGPT is special because it can write text that seems like it’s written by a person.

ChatGPT talks to the readers
Image: ChatGPT connects to the readers

Understanding ChatGPT

ChatGPT is made by OpenAI and is a type of GPT model. It stands out because it’s really good at making text that sounds human-like.

It has a large language model, kind of like a huge word library, a core aspect of neural network based AI technology. It learned from lots of text and uses deep learning (a smart way to teach computers) to make sentences that make sense and sound natural when we talk.

ChatGPT is awesome at chatting. It’s built to understand different questions and answer in a way that’s like talking to a human. It gets better by learning what word should come next in a sentence.

ChatGPT can do things like answer questions, explain stuff, help with creative writing, translate languages, and just have a friendly chat.

ChatGPT’s Relationship to AI

ChatGPT is a practical use of AI, showcasing the advent of virtual assistants powered by sophisticated machine learning. It uses ideas from machine learning and language processing to make something easy and useful for everyday life.

Making ChatGPT was a big deal in AI. It shows how machines can understand and copy human language well. It’s part of AI areas called natural language understanding (NLU) and natural language generation (NLG). These areas focus on making machines get and make language like humans.

ChatGPT brings up important talks about ethics and its effect on society. Issues like spreading wrong information, privacy worries, and the chance of misuse are part of these talks. It also makes us think about how humans and AI will interact in the future and how smart machines can be.

The Future of ChatGPT and AI

ChatGPT is always getting better. It’s improving at understanding situations, handling more complex talks, and being less biased. Future versions will likely be even smarter in how they interact and understand.

The progress and popularity of ChatGPT show a big leap in AI. It sets a standard for future tech, especially in making human-computer interactions better.

AI: Friend or Enemy?

According to the Hungarian László Mérő (former artificial intelligence researcher), the basic algorithms have not changed much, but the data and computing power available to computers have. As a result, developments that failed at the beginning of AI’s history are now present in many areas of our lives. From personal assistants to cybersecurity to military technology.

In 2023, there was huge hype around this technology, mainly thanks to ChatGPT and other generative AI. It is now widely used. However, alongside the benefits, it also poses problems for the future. Just think what would happen if AI could find its place in basic jobs such as cleaning, cooking, but also in more creative jobs such as programming or even writing.

Of course, this would not necessarily contribute to the elimination of these jobs, but there is a good chance that one AI-controlled machine could replace the work of several people. In any case, it would create the social problem of unemployment. Of course, positions may change and new types of jobs may emerge, but overall it is unlikely that humans will be able to keep up with machines in the long terrm.

Another aspect of the potential problems is political. Current imaging and voice AIs are capable of creating disinformation that could lead to serious diplomatic disputes. But if we discuss this in a narrower context, we are still talking about a dangerous thing, as it could greatly help today’s social isolationist processes.

The questions and dilemmas are numerous, but this is enough to show that it is certainly worth being critical and cautious about this technology. Of course, we are still a long way from The Terminator’s Skynet, written and directed by James Cameron, but it is already clear that the question is not where and to what we use artificial intelligence, but who can and will want to use it and for what purposes (with what resources available).


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