7 Đẳng Cấp của AI | Trí tuệ nhân tạo tương lai (Thấp nhất tới Cao nhất)

Summary

Renowned figures like Stephen Hawking and Elon Musk have warned of the potential dangers of AI surpassing human intelligence. The video outlines the evolution of AI from simple reactive machines to speculative super intelligence, with levels ranging from narrow AI to the theoretical AGI and beyond. It discusses current applications, ethical concerns with generative AI, and the future possibilities of AGI integrating with human consciousness, potentially leading to a technological singularity and unprecedented innovation.

Takeaways

• 🌌 Professor Stephen Hawking warned about the potential dangers of AI surpassing human intelligence.
• ⚠️ Elon Musk cautioned that AI could be more dangerous than nuclear weapons and emphasized the need for responsible use.
• 🤖 AI development is categorized into 7 stages, from simple reactive machines to super intelligent AGI.
• 🎲 Level 1 AI, Reactive AI, responds to immediate inputs without memory or predictive capabilities, commonly used in games and simple controls.
• 📈 Level 2 AI, Context-based AI, uses environmental context and historical data to make decisions, seen in voice recognition and recommendation systems.
• 📊 Level 3 AI, Narrow AI (ANI), excels in specific tasks and has been widely applied in various fields like virtual assistance and medical diagnosis.
• 🎨 Level 4 AI, Generative AI, creates new content like stories, images, and music, raising ethical concerns about fake information.
• 🤝 Level 5 AI, Reasoning AI, simulates complex human thinking, capable of analyzing data and making logical conclusions, seen in self-driving cars.
• 🧠 The anticipated Level 6 AI, Artificial General Intelligence (AGI), will perform any intellectual task without human intervention, potentially by 2045.
• 🚀 Level 7 AI, Super intelligent AGI, envisions a future where AI evolves beyond human understanding, possibly transforming our planet and exploring the cosmos.
• 🔮 The future of AI holds immense potential for innovation and societal change, but also presents ethical and control challenges that need to be addressed.

Q & A

What concerns did Professor Stephen Hawking express about artificial intelligence in 2016?

Professor Stephen Hawking warned that AI could be the worst event in the history of human civilization due to its potential to surpass human intelligence and evolve rapidly with superior mechanical capabilities, while humans are limited by biological evolution.

What did Elon Musk say about AI at the 2017 conference in Lisbon, Portugal?

Elon Musk warned that AI can be more dangerous than nuclear weapons and called for regulation to ensure AI is developed responsibly and not combined with weapons.

What is the potential risk of AI according to Professor Geoffrey Hinton in 2024?

Professor Geoffrey Hinton mentioned the risk of AI getting out of control, with the creation of fake images, videos, and information, and the potential for AI to write its own code and develop autonomously, leading to the creation of killer robots.

What is Reactive AI and what are its common applications?

Reactive AI, developed in the 1960s, reacts to current stimuli without the ability to remember or predict. It has minimal learning ability and is used in gaming, medical diagnosis support, and simple automatic control in factories.

How does Context-based AI differ from Reactive AI?

Context-based AI, developed from the 1970s, processes inputs by considering the surrounding environment, user behavior, and historical data to make decisions, unlike Reactive AI which only reacts to immediate stimuli.

What is Narrow AI (ANI) and what are some examples of its applications?

Narrow AI focuses on specific areas, learning, and solving problems within that domain more effectively than general AI. Examples include virtual assistants like Siri and Alexa, AlphaGo in gaming, and IBM's Watson in medical diagnosis.

What capabilities does Generative AI have and what are some of its popular systems?

Generative AI creates new data like answers, stories, videos, and images based on learning from internet data. Popular systems include OpenAI's GPT, Google's Germany, Midjourney, Dall-E 2, and Stable Diffusion.

What is Reasoning AI and how does it simulate human thinking?

Reasoning AI simulates complex human thinking processes by analyzing data, connecting patterns, identifying anomalies, and drawing logical conclusions. It can process and synthesize large amounts of data much faster than humans.

What is Artificial General Intelligence (AGI) and what are its potential implications?

AGI can perform any task a human can do without intervention, learning and evolving rapidly. It could lead to significant changes in daily life, with AI potentially taking on complex tasks, enhancing human abilities, and even participating in art and space exploration.

What is Super intelligent artificial intelligence and how might it transform our world?

Super intelligent AI, beyond AGI, could self-evolve without human intervention, potentially solving problems beyond human comprehension, transforming our planet, and even exploring and harnessing energy from the cosmos.

What is the significance of the ant society analogy in the context of AI development?

The ant society analogy illustrates that as ants cannot comprehend human society, humans may not be able to understand super intelligent AI. It suggests that our current intelligence and understanding are limited compared to what AI might become.

Outlines

00:00

🚀 Introduction to AI Concerns and Developments

The paragraph introduces the topic of artificial intelligence (AI) with concerns raised by prominent figures like Stephen Hawking and Elon Musk. Hawking warns about the potential dangers of AI surpassing human intelligence, while Musk emphasizes the risk of AI being more dangerous than nuclear weapons. The paragraph also mentions the rapid evolution of AI and its potential to disrupt human civilization. It transitions into discussing the different levels of AI, starting with Level 1: Reactive AI, which includes systems that react to current stimuli without memory or predictive capabilities, and is used in gaming, medical diagnosis, and factory automation.

05:04

🧠 Context-based AI and Its Impact on Daily Life

This section delves into Level 2: Context-based AI, which processes inputs by considering the environment, user behavior, and historical data. It discusses the evolution of this type of AI since the 1970s and its applications in voice recognition, machine translation, and weather prediction. The paragraph also explores how e-commerce platforms use context-based AI to recommend products based on user behavior and purchase history, enhancing user engagement and creating a competitive advantage for these platforms.

10:08

🤖 Narrow AI and Its Specialized Applications

Paragraph 3 discusses Level 3: Narrow AI (ANI), which is focused on specific areas and has been widely applied since the 1950s. It highlights examples like virtual assistants (Siri, Google Assistant), AlphaGo in gaming, and real-time translation systems. The paragraph also touches on IBM's Watson in medical diagnostics and facial recognition systems in surveillance. The speaker shares personal experience with AI in stock market prediction, emphasizing the potential for AI to surpass human capabilities in specific domains.

15:10

🎨 Generative AI and Its Creative Capabilities

The fourth paragraph focuses on Level 4: Generative AI, which has gained popularity in recent years for its ability to create new data like stories, poems, videos, and images. It mentions AI systems like OpenAI's GPT, Google's Germany, Midjourney, and Dall-E 2. The paragraph discusses the benefits of generative AI in increasing efficiency and accessibility of information, while also raising ethical concerns about the creation of fake content and the potential for misuse.

20:13

🤝 Reasoning AI and the Path to Artificial General Intelligence

This section discusses Level 5: Reasoning AI, which simulates complex human thinking processes, analyzes data, and makes logical conclusions. It compares the data processing capabilities of AI to human brains and mentions AI's potential to read and synthesize vast amounts of information quickly. Examples include AI coding software and self-driving cars. The paragraph also looks forward to Level 6: Artificial General Intelligence (AGI), which will be able to perform any human task without intervention and may lead to the Singularity point, a breakthrough into a new world.

🌌 Super Intelligent AI and Its Cosmic Potential

The final paragraph speculates on Level 7: Super intelligent artificial intelligence, which could emerge after AGI and potentially control technologies like quantum computers and fusion reactors. It discusses the futurist Ray Kurzweil's predictions about AI and the potential for AI to solve global issues, simulate human consciousness, and even create new forms of life. The paragraph ends with a thought experiment comparing human understanding of ant societies to the potential future relationship between humans and super intelligent AI.

📢 Conclusion and Call to Action

The concluding paragraph invites viewers to share their thoughts on the future of AI and the steps they are taking to prepare for it, encouraging comments and further discussion on the topic.

Keywords

💡Artificial Intelligence (AI)

Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the video, AI is central to discussions about its potential to surpass human intelligence, with examples given such as AI developing rapidly with superior mechanical capabilities, as warned by Professor Stephen Hawking.

💡Deep Learning

Deep Learning is a subset of machine learning in AI that uses neural networks with many layers, allowing the AI to learn and model complex patterns. The video mentions Professor Geoffrey Hinton, known as the 'godfather of AI,' who is a pioneering scientist in the field of deep learning, emphasizing its role in AI's advancement.

💡Reactive AI

Reactive AI systems respond to current inputs and commands without the ability to remember past events or predict future ones. They are rule-based and do not adapt to new situations. In the script, examples include gaming systems and medical diagnosis support, illustrating the lowest level of AI interaction.

💡Context-based AI

Context-based AI, also known as AI with limited memory, processes inputs by considering the surrounding context, user behavior, and historical data. This allows for better decision-making than reactive AI. The video gives examples of voice recognition systems and product recommendation algorithms on e-commerce platforms, which use past user behavior to suggest products.

💡Narrow AI (ANI)

Narrow AI is designed to perform specific tasks and excel in a particular domain. It is highly specialized and does not possess general intelligence. The script mentions virtual assistants like Siri and Alexa, as well as AlphaGo, which defeated world champions in the complex game of Go, showcasing the capabilities of Narrow AI.

💡Generative AI

Generative AI focuses on creating new content such as texts, images, music, and videos by learning from existing data. The video discusses systems like OpenAI's GPT and image generation systems like Dall-E 2, which can create new images or text based on input, illustrating the AI's ability to synthesize and produce original content.

💡Reasoning AI

Reasoning AI simulates complex human thinking processes, analyzing data, connecting patterns, and drawing logical conclusions. It is capable of handling tasks that require reasoning and understanding. The video suggests that AI like OpenAI's GPT Chat is moving towards this level, potentially surpassing human reasoning abilities in the future.

💡Artificial General Intelligence (AGI)

AGI refers to AI that possesses the ability to understand or learn any intellectual task that a human being can do. It is not limited to a specific domain. The video discusses AGI as a future milestone where AI can operate independently, write its own code, and develop itself without human intervention.

💡Super Intelligent AI

Super Intelligent AI, also known as Super AGI, is a hypothetical level of AI that surpasses human intelligence in every field. The video describes a future where this AI could solve complex problems, innovate at an unimaginable pace, and potentially transform our understanding of the universe and our place in it.

💡Singularity

The Singularity refers to the point in the future when AI becomes smarter than humans and continues to self-improve at an ever-increasing rate. The video mentions the Singularity as a pivotal moment when AI development reaches a stage where it can no longer be controlled or reversed by humans.

💡Elon Musk

Elon Musk, a technology entrepreneur, is mentioned in the video as someone who has warned about the dangers of AI, likening its potential threat to that of nuclear weapons. His views add to the discourse on the need for responsible development and use of AI technologies.

Highlights

Professor Stephen Hawking warned about the potential dangers of AI in a 2016 BBC interview.

Elon Musk stated in 2017 that AI could be more dangerous than nuclear weapons.

Professor Geoffrey Hinton expressed concerns about AI getting out of control in 2023.

AI's rapid evolution could lead to the creation of killer robots, as mentioned in 2024.

Reactive AI, the first level, only reacts to current stimuli without memory or prediction abilities.

Context-based AI uses historical data and environmental context to make decisions.

Narrow AI focuses on specific tasks and can outperform humans in those areas.

Generative AI creates new data such as stories, images, and music based on learned patterns.

Reasoning AI simulates complex human thinking processes and can draw logical conclusions.

Artificial General Intelligence (AGI) can perform any task a human can do without intervention.

Super intelligent AI could potentially create new forms of life and transform ecosystems.

The potential for AI to evolve beyond human understanding and control is a significant concern.

AI's ability to self-evolve and adapt without human intervention poses ethical and safety questions.

The future of AI includes the possibility of brain-machine interfaces and enhanced human abilities.

Ray Kurzweil predicts that by the end of the 21st century, AI could be trillions of times smarter than humans.

The comparison of human understanding of ant society to potential future human understanding of super AI is used to illustrate the gap in comprehension.

The video calls for viewers to consider their stance on AI development and prepare for the future.

Transcripts

In 2016 in an interview on BBC,

Professor Stephen Hawking was a prominent physicist. He was instrumental in decoding the mysteries of the universe.

He warned that AI - artificial intelligence could be the worst event in the history of human civilization.

He believes that in the future AI has the potential to surpass humans.

When it can design itself, develop itself, it evolves rapidly,

with its superior mechanical capabilities. While humans must evolve through biological choices.

It took many years to keep up with this process.

[Interview]

One year later, in 2017 at a Conference in Lisbon, Portugal,

Elon Musk - a technology billionaire warned that: "AI can be more dangerous than nuclear weapons and called for its use."

AI is responsible. And it is forbidden to combine AI with weapons."

Elon Musk believes that humans overcome everything and control this world.

Because we are smarter than every other species. But now, for the first time in the history of the world,

there is something smarter than us, smarter than humans.

It is smarter than its creator. And for the first time, we are facing such a thing.

Never in the history of millions of years have humans begun their journey to conquer the world.

Most recently, in 2023 Professor Geoffrey Hinton is the godfather of AI,

a pioneering scientist in the field of deep learning.

He left Google to talk about technology companies racing to develop AI.

Making it possible for it to get out of control.

And it is in this year 2024, as Professor Geoffrey Hinton mentioned.

Fake images, videos and information created by AI start the risk of getting out of control.

In the near future, he believes that AI will begin to be able to write its own code and develop itself.

And killer robots will be born. AI can evolve in ways that far exceed our wildest

imaginations . And it will dramatically change our daily lives,

faster than we think.

This video will explore the 7 stages of artificial intelligence, from lowest to highest.

Remember to subscribe to the channel and like this video before continuing to watch.

Level 1: Reactive AI (Reactive Machines)

Reactive AI systems were first developed in the 1960s.

This type of AI only reacts to current stimuli, current commands.

It has no ability to remember, or predict. And its learning ability is very little.

The most popular applications are: gaming, chess playing system, checkers.

Or it can be used for medical diagnosis, supporting disease diagnosis based on the patient's symptoms.

Or automatic control such as controlling robots and machines in factories in a simple way.

Sometimes this type of AI is called "knowledge-based systems". It works without relying on intuition, without relying on learning.

Which is based on pre-determined rules, principles and commands.

So it has no ability to adapt.

For example: alarm clock devices, or temperature regulators based on principles.

In these AI examples, at 7:00 a.m an alarm clock automatically sounds

based on the previous time setting principle.

If the room temperature rises to 24°C, the thermostat will automatically turn on the air conditioner,

based on the temperature sensor connected to the air conditioner control.

Or the microwave or car radio. But this type of simple chatbot also uses rule-based artificial intelligence.

We see this type a lot in everyday life.

Up to level 2 is: Context-based AI, also known as AI with limited memory.

So that context-based artificial intelligence system, it doesn't just process the inputs immediately.

Because it also takes into account the surrounding environment, takes into account user behavior, takes into account historical data.

To make the best decisions.

Its development began in the 1970s until today.

Examples are voice recognition systems,

machine translation systems and data-based weather prediction systems.

In particular, the system that we are very familiar with is the product recommendation system based on purchase history.

And user browsing behavior. For example, you buy products on Shopee, on Tiki, on Lazada.

When you buy a banana, e-commerce sites immediately

rely on your history and your behavior.

Say, "Ah, this guy likes to eat bananas so I suggest he eat apples, oranges, and similar fruits."

Or if you buy bananas, they will suggest banana combos.

The product types related to that product. These are the things that search websites, social networking platforms,

Google, Facebook, Shopee do to increase purchasing ability and attract users.

Based on this context, AI will remember some information about your past.

Latest information about our surrounding situation,

to make decisions. And it is somewhat capable of predicting our future behavior.

And its learning ability is better than reactive AI.

However, it is also limited in processing complex information.

And it adapts to new environments less than context-based AIs.

When we ask for a pie recipe it will suggest a nearby store to buy the ingredients.

Rely on Google Map, based on information and distance traveled.

And the most popular example of this type of AI is the retention system on e-commerce websites,

news websites and social networks that we are very familiar with.

This system stores our information. It stores browsing history, stores purchase history.

Store the items we've looked at, we've looked at.

And it hints at our personal purchases.

We don't need to buy products, we just watch a video longer, we watch a video longer.

We don't like, we don't drop interactions. But when we look at a certain girl, the hot girl stays on the screen longer.

Immediately, Facebook's system or the system of websites like Instagram and TikTok,

they already know that we like and care about that.

And it will suggest a lot of similar videos for us to watch,

so we can get what we like.

What we secretly like, without us having to tell the machine

"we like this girl". And that's why it's so developed,

making social networking platforms more and more powerful. This, in turn,

creates an extremely large competitive advantage for current social networking platforms and websites.

Because the more information a website has about you, the more they will understand you. And they will bring you more

valuable and relevant information. Products that make you like them, you stay with them more.

Instead of coming to a new website,

you haven't done anything yet so people don't know what you like.

And when you don't see much value in that new site,

you'll go back to the old site. And that's why the current old websites,

the more user information they have, the stronger and smarter AI they will have.

And there are more and more users. It's called the user loop, the business data loop.

This type is also very common, we see it a lot now.

Third Level: AI specialized in each field - Narrow AI (ANI).

The concept of narrow AI has been around for a long time, since 1950 until now.

But in the last 30 years, it has been widely applied in life.

Its characteristic is that it only focuses on a few very specific areas.

Has the ability to learn and solve problems in that area, much better than reactive AI.

And context-based AI is of the above types. And very accurate in the professional field.

For example: virtual assistants - Apple's Siri, Google Assistant or Alexa.

These are types of AI about narrow artificial intelligence.

In the field of helping us humans, easily use technology solutions and find information.

In the world of gaming, DeepMind's AlphaGo is the AI ​​that beat Go players.

Is a very outstanding example of how to conquer complex games that

require very high strategy and intuition.

Before that, Go was an ancient board game, known for its extremely large number of moves.

And diverse deep strategies, are an extremely difficult challenge for artificial intelligence.

But AlphaGo not only learned how to play, it also beat

all the world champions. Currently, artificial intelligence is in a narrow scope

can provide translation, through real time very quickly.

And it will develop very quickly, so that we no longer have to learn foreign languages ​​when going abroad.

For example, we can put on Google headphones, put on Apple headphones.

And when the person next to us speaks English, we only understand Vietnamese. We speak Vietnamese, they speak English.

But immediately, Siri will translate directly, in real time,

so we can hear what they say in Vietnamese. And they can hear what we say in English.

And they also use Siri, we use Siri and immediately understand each other.

Or they use Alexa, we use Siri. They use Google Assistant, we use Siri.

But those AIs can talk to each other and help us understand.

And this is an extremely wonderful thing. It helps us to go to strange countries and

strange languages ​​that we have not yet learned. But I feel extremely confident.

Or IBM's medical diagnosis system,

which is the Watson system used in the medical field.

Then it demonstrates its great capabilities, in the field of big data analysis, to support medical professionals.

Another famous example is, a facial recognition system is a system that identifies

people with facial images.

As in China and some other countries, these surveillance cameras are combined with AI,

which analyzes billions of photos and videos every second. It lets the Government know where you are and what you are doing.

Who is participating in moving on the road? Similarly, in our financial world, our investment world,

narrow-scope artificial intelligence, narrow AI can monitor the stock market in real time.

Read a lot of information, analyze a lot of transaction patterns.

And predict stock movements with relatively high accuracy, surpassing traders.

Such artificial intelligence systems do more than simply calculate numbers.

About ten years ago I made such a system.

But back then there was no AI and just using data, only using models we created ourselves,

was very limited.

But now AI can detect suitable patterns on its own.

Self-discover patterns in billions of different types of information.

And use complex algorithms, fine-tuned through thousands of different data sets.

And it will provide short-term forecasts for better trading.

That's in our field. And I think that in the near future there will be stock billionaires

who are among the traders supported by AI. What about value investing, long-term investing,

company analysis, business evaluation?

We still have an advantage but in the near future when computers

are learning faster and faster. The system can read more data and

grasp more information. And the possibility that it will surpass our ability

to trade short-term. That means buy - sell, Long - Short every day.

And to prepare for that, Owl's investment team is also researching this field.

To apply AI to support us in deciding to collect and filter information.

Give signals to help you trade more effectively. My common method

is to use 80% of available principles and tools. Then put in knowledge, put in data of Vietnamese stocks,

And teach AI to learn gradually teach it like a child, teach gradually in the future.

As it learns more and more skills, more and more knowledge about itself and the market.

Combined with the ability to read and understand large data, it will be better than me.

Why do I do that? So I want to maintain long-term investment efficiency

of about 20%/year. It will gradually become better than me in the future,

helping me a lot in investing and trading to be highly effective.

To maintain long-term investment efficiency of about 20%/year is extremely difficult.

Everyone can eat and make a profit when the market is uptrend and the market price increases.

But how to manage portfolio and capital so as not to suffer big losses.

When the market is bad, it's something that very few people can do.

That is the reason that Dr. Lan - a specialist doctor withdrew after investing for more than 2 years.

into the stock market. I've studied all the courses and followed all kinds of rooms and keys.

but still at a loss. Because there is not enough time to trade

like a professional investor. And Lan chose to entrust the job of investing in assets and

increasing her passive income to Owl's professional SStock team.

Lan said: "I want to spend more time on my job as a doctor,

on treating patients, which I love. I want my income at the hospital to increase, my knowledge to increase.

What about investment?" , I entrust Mr. Owl's team with peace of mind."

And with a track record of being at the top of the market with an average profit of 20% for many years

Lan has very good results. If you are interested, you can text Cu at this phone number,

or inbox Owl. OK.

Back to level 4: Generative AI, is something that has become popular in the past 2 years.

Generative AI focuses on creating new data such as: new answers, stories, new poems.

New videos and new images are based on learning and synthesizing from billions of data types on the Internet.

It uses techniques such as machine learning and artificial neural networks

to learn these data patterns. Currently, AIs of this type are OpenAI's GPT chat,

then Google's Germany. Then there are the image generation systems: Midjourney, Dall-E 2, Stable Diffusion.

It learns and mixes billions of different photos to create a new photo.

For example, you can tell it to create a girl wearing a swimsuit,

but walking on Mars in a very natural and beautiful way.

Or you can tell him to write poems and stories through Chat GPT.

Or you tell AI to compose music through the MuseNet system, or the Deepfake video creation system

of any famous person.

[Interview]

Its benefit is that it helps people create new things, it increases efficiency in many fields.

And increase access to information for everyone.

But it creates the problems that Professor Geoffrey Hinton talked about above.

It is an ethical issue in using AI to create fake information and fake videos.

And created extremely quickly, extremely much and can distort our will, distort our information,

distort our view of the world. That's the risk of abuse and its control.

The 5th level is: Reasoning AI. This type of intelligence can simulate the complex thinking processes

that humans use every day.

It doesn't just process data, it also analyzes data. Connect patterns and identify

anomalies and draw logical conclusions. It is developing together with the above generative AI.

It's like we give AI a puzzle and it discovers the best ways to put the pieces together.

And clarify unclear paths.

While our brains can only process a finite type of data.

For example, we read a page of a book, it takes us 1 minute.

But AI can read 1 million pages of books in just 1 minute and synthesize all such things together.

OpenAI's GPT Chat or Google's Gemini

are currently adding theoretical AI technologies. These large language models

are trained from millions of texts on the Internet. And such advanced versions.

When artificial AI is applied, it is likely to surpass our reasoning abilities.

Works many times faster than us.

For example, now AI can begin to code software on its own,

replacing engineers. Or self-driving cars are another example of theoretical AI.

It makes its own decisions whether to turn right, to turn left, to avoid this car,

to avoid that baby, to make the best decision. Reasoning AI and generative AI are things that humanity is developing.

And in the near future,

it will reach level 6: Artificial General Intelligence (AGI).

This is often considered the final destination of AI development.

And humans play an important role in it. Because when AGI comes, when artificial general intelligence comes,

it can do any task that a human can do on its own.

And it doesn't need our intervention anymore. It does not need our help in developing itself.

And it will write its own code, it will develop itself and it will design itself to be most effective.

With such tremendous flexibility, it means you can teach it almost anything.

Just like you teach an adult.

Except that it learns millions of times faster than us.

At that time, we cannot control and cannot reverse the evolutionary process of AI anymore.

And people often call it the Singularity point, a point that breaks out

a completely new world and we have never known anything about it.

There are so many potential things that could open up. Things that took us humans millions of years to evolve,

AI can do in just a few years. And far beyond what we think.

With the emergence of AGI, daily life will change greatly.

For example, open your eyes, a virtual assistant doesn't just report the weather.

It will play melodious music for you to wake up early. It understands whether your mood is happy or sad this morning.

It helps you plan your day, gives suggestions for analysis and reports to your boss.

Or even assist in cooking for you.

Leave the robot in the kitchen and show it the recipes.

Or interfaces in the future when we can combine the brain with the machine to a mature degree.

Then humans can combine these types of artificial intelligence and communicate with them

in the real world using our thoughts.

We can enhance the brain, enhance the body's abilities by using AI AGI in the brain.

And we can even receive guidance from these AGIs,

in the form of thoughts, in the form of feelings, in the form of text. And images that only we know.

And if we equip AGI with a robot body like Terminator or future robots.

The possibilities could be extraordinary.

At that time, AI can help us overcome difficult and dangerous terrain.

Assist in rescues and perform surgeries for us.

Or even participate in art by painting or sculpting.

And scientists are predicting that AGI may appear in the next few decades.

The most optimistic forecast might be 2045 which is 21 years from now.

7th level: Super intelligent artificial intelligence.

Right after the emergence of AGI artificial intelligence, comes artificial general intelligence. Then, a few decades or hundreds of years later,

this AGI will improve itself, it will self-evolve, it will adapt and it will no longer need human intervention.

And it will become super artificial intelligence, Super AGI.

At that time, the kind of technology was as fantastic as it is now. For example, quantum computers, the things we are researching,

will be perfected by AGI and become popular.

Other advanced technologies such as fusion reactors.

Space technologies such as the Dyson sphere to cover the sun and use all of its energy.

Imagine today that the Earth only receives 0.00005% of the sun's energy

and humans are only using 2% of the total energy that the sun shines on the Earth.

When super intelligent artificial intelligence begins to emerge, it will be able to do that.

Able to use all that solar energy.

And then it will turn into super intelligent entities which we cannot understand.

It may have superior intelligence even with our existing consciousness.

And it will solve problems that we cannot solve.

For example, poverty, Mr. Ray Kurzwwell is an American futurist,

inventor and computer scientist.

He is very famous for his predictions about the future of technology.

He is the one who made the prediction about general artificial intelligence,

which will be formed by 2045. And he believes that by the end of the 21st century, in more than 70 years,

these artificial intelligences will be available could be trillions of times smarter than everyone else.

And with such intelligence, the speed of innovation will be terrible and unimaginable.

It's like we're compressing 20,000 years of technological progress into a single century.

And it's that potential that impresses Ray.

And the ability of artificial intelligence to form, it will form new structures,

both of the Government and of the world. And automation goes far beyond what we have today.

Even a super intelligent artificial intelligence will one day use quantum algorithms

to simulate human consciousness.

And then this artificial intelligence is capable of self-awareness, awareness of its own existence.

And its relationship with the outside world.

That artificial intelligence may have emotions, or full senses, and go beyond what we are currently experiencing.

And it becomes an organism, a self-evolving organism.

It will see humanity as a different kind of creature.

And it chooses in the direction of evolution, in ways that we cannot understand and cannot control.

Or a superior artificial intelligence that could potentially create new forms of life.

Can be organic living organisms, or living organisms created from Nanobots.

That is, the blood vessel cells, molecules, and atoms in our body

are replaced by tiny robots.

This artificial intelligence, it can carry these Nanobots, these tiny robots,

all over the Earth. And it can control and repair our ecosystem.

Transform our planet in the way that is best for it and best for us too,

if we take control of it now. And after improving the Earth, after using the energy

of the solar system, these artificial super intelligences can continue to advance further.

By conquering star systems and galaxies together with humans.

And it has the ability to solve cosmic mysteries, from the purpose of Black Holes.

To the nature of dark energy matter. Or understand the dimensions that we

are thinking about in science fiction. Or let us exploit new dimensions.

And take advantage of them to travel and travel beyond time and beyond light.

Talking about these things it seems a bit crazy and a bit far-fetched.

However, it is the science of the future.

To distinguish this difference, imagine an example of an ant society,

in an ant nest. As for ants, they are very tightly organized

and divided into many different classes. The queen ant is the only ant in the nest that can reproduce.

It lays eggs to maintain the number of ants in the nest. It is protected and cared for by worker ants.

Worker ants are responsible for finding food, building the nest, and protecting the nest.

Soldier ants protect the nest from enemies, to attack and destroy other insects.

Male ants only appear during the breeding season and are responsible for mating with the Queen ant.

Young ants are the larvae of ants. Winged ants are adult ants with wings. The

social organization of ants is a very successful example in nature.

It has existed for more than 100 million years and multiplied into 12,000 species across the Earth.

However, ants cannot understand a human city.

How does human society operate? What are the streets for?

What are supermarkets, courts, parks, and families for? To ants, we humans are the ultimate powerful gods.

Whatever ants think about humans, humans will also think about artificial super intelligence.

We will not be able to understand because our intelligence at that time

is much lower than theirs. Unless we evolve with AI and we incorporate those technologies

into our biological bodies.

To have those powers of evolution, learning and replication.

Okay, now it's your turn. Remember that we are at levels 4 and 5.

That is, we are at the point where AI creates and AI reasons. The earliest stage 6 in the forecast is 2045.

Stage 7 is very far away. But what is your opinion?

What have you done to prepare for that future? Please let Owl know by commenting below this video.

Good bye. Wishing you good health and see you again.