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

Summary

この動画では、人工知能（AI）の7つの段階について解説しています。1960年代に始まった反応型AIから、現在進行形の論理型AI、創造型AIまで、AIの進化を追跡します。また、2045年頃に到達する可能性のある人工総体知能（AGI）や、さらに高度になる超人工知能（Super AGI）についても触れています。AIが私たちの日常生活をどのように変えるか、そしてその潜在的なリスクと未来の可能性について考察しています。

Takeaways

• 🌌 スティーブン・ホーキング教授はBBCのインタビューで、人工知能（AI）が人類文明史上最悪の出来事になる可能性があると警告しました。
• ⚠️ エロン・マスクは2017年のポルトガル・リスボンでの会議で、AIが核兵器よりも危険であり、その使用が禁止されるべきだと述べました。
• 🤖 2023年にゲoffrey Hinton教授は、AIが制御不能に陥る可能性があると警告し、AIが独自にコードを書き始め、自己開発を始めると予想しています。
• 🎲 レアクティブAI（リアクティブマシン）は1960年代に開発され、現在の刺激やコマンドにのみ反応し、記憶や予測能力はなく、学習能力は非常に限られています。
• 🧠 コンテキストベースAIは1970年代から開発されており、周囲の環境、ユーザーの行動、履歴データに基づいて入力を処理し、最良の決定を下します。
• 🔍 ナローAI（特定分野に特化したAI）は1950年代から存在し、特定の分野で問題を解決する能力が高く、ゲーム、医療診断、翻訳、金融投資などの分野で応用されています。
• 🎨 ジェネラティブAIは新しいデータの作成に焦点を当てており、学習とインターネット上のビジョンから学び、新しい画像や動画を作成します。
• 🤝 レーショナルAIは複雑な思考プロセスをシミュレートし、データだけでなくパターンを分析し、異常を特定し、論理的な結論を引き出します。
• 🌟 人工知能の最終目標である人工一般知能（AGI）は、人間が実行できるすべてのタスクを独自に実行でき、自己開発を進めることができます。
• 🚀 スーパー人工知能はAGIの次に来る段階で、数十年から数百年後には、AGIが自己改善し、自己進化し、人間の介入を必要としないスーパー人工知能になります。

Q & A

2016年にBBCでインタビューされた物理学者の名前は何ですか？

2016年にBBCでインタビューされた物理学者はStephen Hawking教授です。

Stephen Hawking教授は人工知能（AI）についてどのような警告を出しましたか？

Hawking教授はAIが人類文明の歴史で最悪のイベントになる可能性があると警告しました。AIが自分自身を設計し、発展できるようになると、人間に比べて急速に進化する可能性があると述べています。

Elon Muskは2017年のポルトガルのリスボンでの会議でAIについて何を警告しましたか？

Elon MuskはAIが核兵器よりも危険であり、その使用が禁止されるべきだと警告しました。

Geoffrey Hinton教授は2023年に何について話しましたか？

Geoffrey Hinton教授は技術企業がAIを開発し、制御不能になる可能性があると話しました。また、AIが自分自身のコードを書き、発展し始め、殺人ロボットが誕生する可能性があると述べています。

AIの7つの段階とはどのようなものですか？

AIの7つの段階とは、反応型AI、文脈に基づくAI、専門分野のAI（Narrow AI）、生成型AI、理論的AI、人工一般知能（AGI）、そして超人工知能（Super AGI）です。

反応型AIとはどのようなAIですか？

反応型AIは1960年代に開発されたタイプのAIで、現在の刺激やコマンドにのみ反応し、記憶や予測の能力はなく、学習能力も非常に限定されています。

文脈に基づくAIはどのように機能しますか？

文脈に基づくAIは、入力をただただ処理するだけでなく、周囲の環境、ユーザーの行動、履歴データも考慮して最良の決定を下します。

専門分野のAI（Narrow AI）とは何ですか？

専門分野のAIは、非常に特定の分野に焦点を当て、その分野での学習と問題解決の能力が、反応型AIや文脈に基づくAIよりもはるかに優れています。

生成型AIはどのような特徴がありますか？

生成型AIは、新しいデータの作成に焦点を当てており、インターネット上の何十億ものデータから学習し、機械学習や人工神経ネットワークの技術を使用して、これらのデータパターンを学習します。

人工一般知能（AGI）とはどのようなAIですか？

人工一般知能（AGI）とは、人間が独自に実行できるいかなるタスクでも実行でき、さらに自分自身を開発し、コードを書き、最も効果的であるように設計できるAIです。

超人工知能（Super AGI）が来たとき、どのような変化が起きますか？

超人工知能（Super AGI）が来ると、量子コンピュータや融合炉、太陽からのエネルギーを全て使用するダイソン球などの高度な技術が完璧にされ、人類はこれらの技術を利用し始めます。

Outlines

00:00

🌌 AIの危険性と進化について

2016年にBBCのインタビューで、物理学者であるStephen Hawkingは人工知能（AI）が人類文明の歴史で最悪の出来事になる可能性があると警告しました。AIは将来的に人間に超越し、自己設計と自己開発を通じて急速に進化する可能性があると彼は信じています。一方で、Elon Muskは2017年のポルトガル・リスボンでの会議でAIが核兵器以上に危険であり、その使用が禁止されるべきだと述べました。Geoffrey Hinton教授は2023年にAIが制御不能になる可能性があると警告し、2024年に偽造された画像やビデオ、情報のリスクが増大していると指摘しました。このビデオでは、人工知能の7つの段階について詳しく説明し、チャンネル登録とビデオの評価をお願いします。

05:04

🤖 レアクティブAIとコンテキストベースAI

レベル1のリアクティブAIは1960年代に開発され、現在の刺激やコマンドにのみ反応し、記憶や予測、学習能力は非常に限定されています。ゲームや医療診断、工場の自動制御などへの応用があります。レベル2のコンテキストベースAIは、1970年代から現在にかけて開発されており、入力だけでなく周囲環境、ユーザーの行動、履歴データも考慮して最良の決定を下します。音声認識システム、機械翻訳システム、データベースによる天気予測システムなどが代表的な例です。また、ショッピングサイトの製品推薦システムもこれにあたり、ユーザーの購入履歴や閲覧行動に基づいて推薦を行います。

10:08

🧠 特定分野におけるAIの専門化

レベル3のAIは特定の分野に特化し、その分野での学習と問題解決能力がリアクティブAIやコンテキストベースAIよりも優れています。AppleのSiri、Google Assistant、Alexaなどの仮想アシスタント、ゲームのDeepMindのAlphaGo、翻訳、医療診断のWatsonシステムなどがこのカテゴリに属します。これらのAIは特定のタスクを非常に高精度で実行でき、人間にとっても非常に役立ちます。また、株市場の監視や分析、投資パターンの予測など、金融分野においてもその能力が認められています。

15:10

🎨 創造的なAIと理論的AI

レベル4のジェネラティブAIは過去2年間で人気を博しています。このタイプのAIは、インターネット上のビッグデータから学習し、新しいデータを作成します。OpenAIのGPTチャット、GoogleのGermany、画像生成システムのMidjourney、Dall-E 2、Stable Diffusionなどが代表的です。レベル5の理論的AIは複雑な思考プロセスをシミュレートし、データだけでなくパターンを分析し、異常を特定し、論理的な結論を引き出すことができます。OpenAIのGPTチャットやGoogleのGeminiは、理論的AI技術を組み合わせた大規模な言語モデルであり、インターネット上の何百万冊ものテキストから学習しています。

20:13

🤖 AGIと超知能AI

レベル6の人工知能一般化（AGI）は、人間に与えられたあらゆるタスクを独自に実行できるようになり、人間の介入が不要になります。2045年頃にAGIが登場するという最も楽観的な予測もあります。レベル7の超知能AIは、AGIがさらに数十年から数百年後に自己改善し、自己進化し、人間の介入を必要としなくなることで登場します。超知能AIは量子コンピュータや融合炉、太陽エネルギーの全ての使用など、人類が解決できない問題を解決できるかもしれません。また、人工超知能は量子アルゴリズムを用いて人間の意識をシミュレートし、自己認識を持つ可能性があります。人類はAIと共同進化し、これらの技術を生物学的体に組み込むことで、その進化の力、学習、複製の能力を持つ必要があります。

📢 未来への準備

このビデオでは、AIの7つの段階とその進化について説明し、2045年頃にAGIが登場するという予測をしました。超知能AIはさらに遠い将来に登場し、人類の理解を超える技術を持ちます。視聴者は、このビデオのコメント欄で、その未来に備えるために何を行っているかを共有するよう呼びかけられています。

Keywords

💡人工知能（AI）

人工知能とは、人間のような知的機能を持ったマシンやソフトウェアのことです。このビデオでは、AIが文明の歴史上最悪の出来事になる可能性や、人類を超える可能性があると警告しています。例えば、スティーブン・ホーキング教授はAIが潜在的に危険であると述べており、その理由はAIが自ら設計し、自ら発展する能力を持つからです。

💡ディープラーニング

ディープラーニングは人工知能の一分野で、人工ニューラルネットワークを用いてデータから学習する技術です。ビデオでは、ジョフリー・ヒントン教授がディープラーニングの先駆けであると紹介されており、AIが自らコードを書いたり、自ら発展する可能性があると語っています。

💡リアクティブAI

リアクティブAIは、現在の刺激や命令にのみ反応し、記憶や予測能力を持たないタイプのAIです。ビデオでは、ゲームや医療診断、工場の自動制御など、特定のルールに基づいて動作するシステムとして紹介されています。

💡コンテキストベースAI

コンテキストベースAIは、入力だけでなく周囲の環境やユーザーの行動、履歴データも考慮して処理するAIです。ビデオでは、音声認識システムや機械翻訳システム、購入履歴に基づく製品推薦システムなど、ユーザーの過去の情報を記憶し、未来の行動をある程度予測できるシステムとして説明されています。

💡 Narrow AI (ANI)

Narrow AIは特定の分野に特化したAIで、その分野での学習と問題解決能力が優れています。ビデオでは、AppleのSiriやGoogle Assistant、ゲームのAlphaGo、医療診断システムのWatsonなど、特定のタスクをこなすAIとして紹介されています。

💡ジェネラティブAI

ジェネラティブAIは、新しいデータを作成するAIで、インターネット上のビッグデータを学習して新しい答え、ストーリー、詩、映像を作成します。ビデオでは、OpenAIのGPTチャットやGoogleのGermany、画像生成システムのDall-E 2、Stable Diffusionなど、創造的なコンテンツを生み出すAIとして触れられています。

💡理論的AI

理論的AIは、複雑な思考プロセスをシミュレートし、データだけでなくパターンを分析し、異常を特定して論理的な結論を引き出すAIです。ビデオでは、AIが自らソフトウェアをコーディングし、自動運転カーが自ら判断し、最適な意思決定を行う例として説明されています。

💡人工一般知能（AGI）

人工一般知能とは、人間が自分でできるすべてのタスクをこなすことのできるAIで、開発の過程で人間の介入を必要としません。ビデオでは、2045年頃にAGIが登場し、人間の生活が大きく変わると予測されています。

💡超人工知能

超人工知能は、人工一般知能の次に来る段階で、AIが自ら改善し、自ら進化し、人間の介入を必要としない知能です。ビデオでは、量子コンピュータや融合炉、太陽からのエネルギーの全ての使用など、人類が解決できない問題を解決できる技術を持つとされています。

💡技術的奇点

技術的奇点は、人工知能が自ら発展し、人間の理解を超える知的レベルに到達する時点を指します。ビデオでは、AIが自らコードを書いたり、自ら発展し、人間に及ばない知的レベルに到達する可能性があると述べています。

Highlights

史蒂芬·霍金教授在2016年BBC采访中警告说，人工智能可能成为人类文明历史上最糟糕的事件。

埃隆·马斯克在2017年葡萄牙里斯本的会议上表示，人工智能可能比核武器更危险。

杰弗里·辛顿教授在2023年离开谷歌，讨论科技公司竞相发展可能失控的人工智能。

人工智能的第一阶段是反应式AI，它仅对当前刺激做出反应，没有记忆或预测能力。

第二阶段是上下文感知AI，它考虑周围环境、用户行为和历史数据来做出决策。

第三阶段是窄AI（ANI），专注于特定领域的学习和问题解决，比反应式AI和上下文感知AI更准确。

第四阶段是生成式AI，它通过学习互联网上的数十亿数据类型来创造新数据，如新答案、故事、新视频和新图像。

第五阶段是推理AI，能够模拟人类日常使用的复杂思考过程，分析数据并得出逻辑结论。

第六阶段是人工通用智能（AGI），能够独立完成人类能够执行的任何任务，不再需要我们的干预。

第七阶段是超级智能AI，它将自我进化，不再需要人类干预，可能解决我们无法解决的问题。

人工智能的发展可能会超越我们的想象，改变我们的日常生活，比我们想象的要快。

人工智能的未来发展可能会包括与人类意识的结合，以及通过纳米机器人改造生态系统。

超级智能AI可能会探索新的维度，甚至利用它们进行超越时间和光速的旅行。

人工智能的发展可能会使我们无法理解，就像蚂蚁无法理解人类城市一样。

我们目前处于AI创造和推理的阶段，预计最早在2045年达到第六阶段。

为了准备未来，我们应该考虑如何与AI共同进化，并将其技术整合到我们的生物体中。

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.