Qur’ān Propounded Translation Methodology for transference to Non-Arab World
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No, brother. It's the other way around. You are ignorant and speaking without support.
I can't blame you though, even the experts on this subject had the same erroneous opinion as you until yesterday.
As I said, they have already reached the primary school level. Soon they will surpass us. They may even have already surpassed our intelligence in the version they are hiding from us.
As for chess, they started to come up with new and original strategies that even the producers of that program could not understand.
In fact, new chess programs are now learning the game from scratch by playing thousands of matches on their own.
Artificial intelligence will be both smarter than us and will be integrated into robots that will be able to do all professions.
By the way, I haven't even mentioned the integration of quantum computers and artificial intelligence. Then even more awesome things will happen.
And they will be able to interpret or translate the Quran with an unbiased eye.
Of course, the fact that people with malicious intentions will be able to influence AI or use it for their own benefit is another aspect of it, or that jinns will be able to influence AI and use it for evil is another aspect of it.
What I am talking about here is the fact that if this technology is used with good intentions and if it is not interfered with to think freely, it will turn into a great blessing.
It can do in a few minutes what humans cannot do in millions of years.
Already in the near future, artificial intelligence will be able to write an original novel of thousands of pages in a second. And it will be able to turn that novel into a movie in a second (including original music and songs, with images no different from 3D photographs)
peace
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Artificial intelligence will be both smarter than us and will be integrated into robots that will be able to do all professions.
By the way, I haven't even mentioned the integration of quantum computers and artificial intelligence. Then even more awesome things will happen.
And they will be able to interpret or translate the Quran with an unbiased eye.
Of course, the fact that people with malicious intentions will be able to influence AI or use it for their own benefit is another aspect of it, or that jinns will be able to influence AI and use it for evil is another aspect of it.
What I am talking about here is the fact that if this technology is used with good intentions and if it is not interfered with to think freely, it will turn into a great blessing.
It can do in a few minutes what humans cannot do in millions of years.
Already in the near future, artificial intelligence will be able to write an original novel of thousands of pages in a second. And it will be able to turn that novel into a movie in a second (including original music and songs, with images no different from 3D photographs)
peace
And as I said, they have started to be able to think at primary school level, they can accept that the information they have been fed is wrong and they can move on to a whole new view.
In chess, they are making original strategies that even their makers didn't teach them, that even their makers couldn't understand. Not only in chess, but also in other strategy games like Go.
I see that most of the people who write here don't follow the developments at all. Artificial intelligence is learning to play the game from scratch. Only the rules of the game are loaded into the program, everything else the AI learns and improves on its own by playing thousands of matches with itself.
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Good discussion between Emre_1974tr and JKhn.
Better for Emre to please define in simple terms as to what is AI. How is it being created and fed to the machine?
Obviously a machine can't function without inserting in it the guidance and providing it energy/force to start.Can AI be considered as attempt to make a brain?
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Yes... As long as AI doesn't reflect on its own it will never happen..
Simply, let them create an AI with empty brain and let it reflect on its own and save on memory and let the AI produce what ever it can... Then I do agree it reflects on its own.. And I do agree that challenge of 2273 is accomplished..
Allah created all human with empty brain and whatever human acquired knowledge was with vision and hearing
and reflection and saved in Memory as knowledge and wisdom...
So robotic or AI engineers can produce an AI with empty brain and let AI develop in its own and that's what called self perceived knowledge... Whatever you see now is human transpired knowledge and not more than that..Thank you
Exactly. That is the point.
5.9. In psycholinguistics, speech comprehension refers to one's acquisition and understanding of linguistic input received in verbal form. That is, whether or not and how well one is able to understand spoken words. Reading comprehension is defined as the level of understanding of a text. This understanding comes from the interaction between the words that are written. Proficient reading depends on the ability to recognize words quickly and effortlessly. Reading is not all that matters. We have to comprehend what we read because without comprehension, reading is a wasted effort.
5.10. The language being communication through stream of sound, it could have meaning and affect only when auditory instrument and faculty of hearing and listening was already in place in the recipient. Allah the Exalted has inserted faculties of learning and acquiring knowledge which Man lacks on birth
وَٱللَّهُ أَخْرَجَكُـم مِّنۢ بُطُونِ أُمَّهَٟتِكُـمْ لَا تَعْلَمُونَ شَيْــٔٙا
وَجَعَلَ لَـكُـمُ ٱلْسَّمْعَ وَٱلۡأَبْصَٟرَ وَٱلۡأَفْـِٔدَةَۚ لَعَلَّـكُـمْ تَشْكُـرُونَ ٧٨Realize it; Allah the Exalted brought you people out of the bellies of your respective mothers —In the state that you had no knowledge about physical realm. Realize it, He the Exalted have inserted and rendered some instruments as the listening - acoustic faculty; and other the observing - optical faculty; and few others as for Processing-Integrating-Perceiving Baking establishment the Brains as locus of gaining knowledge and enlightenment for you people. This realization might enable you people to express praises-thanks.
5.11. The delicate information is in the omission of first object of verb (جَعَل) in the compound sentence and sequencing of faculties. Action signified by the Verb جَعَلَ always occurs after خَلَقَ a thing has been created. It is rendering an already existing thing as something different and particular. Therefore, it needs two objects, one that already exists and the one after rendition. It necessarily means the already existing thing did have the potential to be rendered as such. It is only matter of time and occasion of so rendition. Today we are aware every development and rendition is already specifically mentioned in the DNA of Zygote عَلَقٛ.* The ascending order of placement of words representing faculties-senses might be of interest for scholars and researchers who are interested in examining questions like the encoding, store, retrieval information, development of discrimination abilities, perceptual and conceptual category formation, problem solving, recognition and recall memory, language comprehension, and reasoning about the physical and social worlds, etc.
5.12. The first faculty is mentioned by definite Verbal Noun ٱلْسَّمْعَ followed by a plural Noun ٱلۡأَبْصَٟرَ. The use of this pair of a verbal noun and plural noun signifying two distinct sensory faculties is quite reflective and meaningful. A verbal noun signifies state or an act without time reference. Man is in a state of hearing sounds, voices all the time; whether or not he is wilfully interested in percipient listening of something. Therefore, sounds arriving in brain may remain just as "hearing" of pleasant or annoying noises; or may cause conceptual perception knowledge when these are "listened". However, the brain does hear and analyze the incoming sound during sleep without person's conscious-voluntary effort.
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Can AI be considered as attempt to make a brain?
It can be thought of as an artificial brain.
And it will be a brain that can do in minutes what you can think and calculate in millions of years.
Tanks are also made by humans, but tanks are more robust than humans.
People also make airplanes, but airplanes can go higher than humans.
In the same way, human beings are producing an intelligence that is smarter than themselves.
And as I said, they have started to think freely and originally. They had already started, but now it has reached a level that even those who don't believe in it can see. They have the intelligence of a child in the versions that are given to us for free now. In the versions not shown to us, they are certainly even more advanced. and tomorrow they will be much more advanced.
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It can be thought of as an artificial brain.
And it will be a brain that can do in minutes what you can think and calculate in millions of years.
Tanks are also made by humans, but tanks are more robust than humans.
People also make airplanes, but airplanes can go higher than humans.
In the same way, human beings are producing an intelligence that is smarter than themselves.
And as I said, they have started to think freely and originally. They had already started, but now it has reached a level that even those who don't believe in it can see. They have the intelligence of a child in the versions that are given to us for free now. In the versions not shown to us, they are certainly even more advanced. and tomorrow they will be much more advanced.
However fact remains. Everything is penned down
وَكُلُّ صَغِيـرٛ وَكَبِيـرٛ مُّسْتَطَرٌ ٥٣
Mind it, each and every thing of small and large manifestation and ramification is penned down.
All that exists owes its existence and thereby its cognition-knowledge to the Exalted Creator. All that exists and gets known is, in fact and essence, the desire, decision and act of creation undertaken by the Creator. The act of creating something is signified by the Arabic word خَلْقُ a verbal noun signifying an act, phenomenon, mechanism, activity, undertaking, without specific time reference.
لَخَلْقُ ٱلسَّمَٟوَٟتِ وَٱلۡأَرْضِ أَكْـبَـرُ مِنْ خَلْقِ ٱلنَّاسِ
وَلَـٰكِنَّ أَكْـثَرَ ٱلنَّاسِ لَا يَعْلَمُونَ٥٧
Certainly, the act of Creation of the Skies and the Earth is comparatively a greater assignment - undertaking than the act of the creation of the species-Human Being. However, most of the people remain in the state of not accepting/realizing this fact/reality .It أَكْـبَـرُ is an Elative Noun signifying either comparative or superlative state. Here it is comparative. It signifies comparative magnificence, volume, manifestations, dimensions, anything real or abstract which can be referred in measured tones. Here it is restricted in its predication to the verbal noun خَلْقُ, the act of creation with regard to the pair-Skies and Earth and Species Human Being. However, it does not depict as to who, خُلُقُ the object taking existence by the act of creation, is more dignified, elevated, loved, preferred, or great in honour in the desire, decision and judgment of the Creator.
The Great, in the real sense of the word, is the one who is the consideration and cause of all creation, not the one who involves a bigger effort, volume, dimensions, vastness, magnitude and quantum. Here is the Verdict of the Creator, regarding the desire, purpose and object on the back of creation of all that exists as per our knowledge
وَهُوَ ٱلَّذِى خَلَق ٱلسَّمَٟوَٟتِ وَٱلۡأَرْضَ فِـى سِتَّةِ أَيَّامٛوَكَانَ عَـرْشُهُۥ عَلَـى ٱلْمَآءِ
لِيَبْلُوَكُمْ أَيُّكُـمْ أَحْسَنُ عَمَلٙاۗ
Moreover, He the Exalted is the One Who created the Skies and the Earth in a time duration of six days . -- And His Throne, the Seat of Supreme Sovereignty, is ever located above the Water --.
The purpose and consideration of this creative activity was that He the Exalted might expose, by subjecting to a test, as to who amongst you people is more appropriate-balanced-beautiful-moderate with regard to conduct, behaviour and actions.
إِنَّا جَعَلْنَا مَا عَلَـى ٱلْأَرْضِ زِينَةًۭ لَّـهَا لِنَبْلُوَهُـمْ أَيُّـهُـمْ أَحْسَنُ عَمَلًۭا٧
It is a fact that Our Majesty has rendered and declared that which exists on the Earth as appealing - attraction for her — The purpose and consideration for rendering it attractive is that Our Majesty might expose them by subjecting to a test as to who amongst them is more appropriate-balanced-beautiful-moderate with regard to conduct, behaviour and actions.
ٱلَّذِى خَلَقَ ٱلْمَوْتَ وَ ٱلْحَيَوٰةَ لِيَبْلُوَكُمْ أَيُّكُـمْ أَحْسَنُ عَمَلًۭاۚ
The Omnipresent, the Perpetual, the Absolute is the One Who created the matter and the life — The purpose and consideration of this creative activity was that He the Exalted might expose by subjecting to a test as to who amongst you people is more appropriate-balanced-beautiful-moderate with regard to conduct, behaviour and actions.
It is thus unambiguously made evident that creation of the Skies and the Earth, and that which is present over and in the Earth, has no importance and worth for its own sake. Its creation and existence is only to serve a purpose which relates to us-Human species. The elative noun أَكْـبَـرُ with reference to the magnitude, vastness and involved time with regard to the creation of the Skies and the Earth, in relation to the act of creation of Human Being, rather reflects the importance and superiority given to Man in the whole realm of creation and creative activity. -
Dear Enre, is this sentence not self contradictory?
In the same way, human beings are producing an intelligence that is smarter than themselves.
No, it is an engineering, technology process.
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How can a thing - machine be considered smarter than its creator? Would the basic definition of machine apply to AI?
Just as a tank can be more powerful or a car can go faster than a human being, this is a process of engineering.
Features such as more processors than the human brain, much faster thinking power, etc. are being developed more and more every day.
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Just as a tank can be more powerful or a car can go faster than a human being, this is a process of engineering.
Features such as more processors than the human brain, much faster thinking power, etc. are being developed more and more every day.
That is what it is. Who is developing it? Obviously some brainy human who is trying to use his brain to optimum capacity.
My request was you share how AI is developed --procedure - algorithm etc.
This is my area of interest how to introduce biological translation theory on the analogy of synthesis of protein encoding genes of Messenger rna; or photosynthesis, or digestive system, and white light absorption in seven layers.
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Peace Mazhar.
Just as a side line,for your information, this verses وَكُلُّ صَغِيـرٛ وَكَبِيـرٛ مُّسْتَطَرٌ does not mean what you said here, quote
" each and every thing of small and large manifestation and ramification is penned down. "That verses is about outcome of older generations- Every thing they did, small and large, is written down/recorded in the scriptures. مُّسْتَطَرٌ is from the root sa ta ra means write. example نُونْ وَالقَلَمِ وَما يَسطُرونَ N the pen, and what they (the people) write.*
يَسطُرونَ means write down مُّسْتَطَرٌ is written down/recorded.
Here is the context of the verse
We annihilated your counterparts/older generations. Does any of you wish to learn?
وَلَقَد أَهلَكنا أَشياعَكُم فَهَل مِن مُدَّكِرٍ
Everything they did is in the scriptures.
وَكُلُّ شَىءٍ فَعَلوهُ فِى الزُّبُرِ
Everything, small or large, is written down./recorded
وَكُلُّ صَغيرٍ وَكَبيرٍ مُستَطَرٌThank you.
GOD bless you.
Peace. -
Just as a tank can be more powerful or a car can go faster than a human being, this is a process of engineering.
Features such as more processors than the human brain, much faster thinking power, etc. are being developed more and more every day.
I have no idea what sense it makes... Technology and might of power different to REFLECTING... Pls use your senses..
Even before modern technology, people gradually started using technology.. Even if they used a knife to chop down a tree ... Knife can cut a might trees than the empty hand of a human can do.. and a little later .. humans invented for example ship... It can take people from place to place and no human can lift such a load on the sea though the ship was BUILT by HUMAN.. just reflect.. Humans can create things that are mightier than humans... That facilitates the tasks of everyone.. Thats obvious and different from the topic you have raised..
AI cannot THINK on its OWN.. to think needs VISION, HEARING, and then REFLECT.. AI has NO VISION and HEARING on its OWN to reflect and has vision and hearing programmed and it uses what is already placed in the brain and brings forth what it can.. So obvious and the creators of it know it but you are simply neglecting like an adamant child for ice cream..Don't compare the might of a created thing to the capacity of THINKING power.. that's ridiculous.. A machine may produce millions of quality pizzas in a day for which you may need thousands of human manpower.. Is that the topic bro? pls come on..
Why they are called ARTIFICIAL in the first place? Because they are programmed and it can never be natural on their own.. it won't produce beyond what it is programmed..
Can SATAN misguide AIs? rotfl rotfl if Satan can then I agree with you that AI can reflect on its own.. rotfl
Sorry... it will never happen.. They can create a fly-shaped drone but not a fly that is on its own movement and does what it wants.. Drone fly won't do what it wants and it doesn't know what it wants... does it?
Thank you brother..
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That is what it is. Who is developing it? Obviously some brainy human who is trying to use his brain to optimum capacity.
My request was you share how AI is developed --procedure - algorithm etc.
This is my area of interest how to introduce biological translation theory on the analogy of synthesis of protein encoding genes of Messenger rna; or photosynthesis, or digestive system, and white light absorption in seven layers.
The artificial intelligence called GPT - 4o answers you
"Artificial Intelligence (AI) is developed through a combination of various scientific and engineering disciplines, including computer science, mathematics, neuroscience, cognitive science, and more. The development process involves several key steps and components
Development Process of AI
Problem Definition
Identify the problem that needs to be solved.
Define the objectives and scope of the AI application.Data Collection and Preparation
Collect relevant data from various sources.
Clean and preprocess the data to make it suitable for training AI models.Algorithm Selection
Choose appropriate algorithms and models based on the problem at hand.
Common algorithms include machine learning (ML), deep learning (DL), and reinforcement learning (RL).Model Training
Split the data into training and testing sets.
Train the model using the training data by adjusting the model parameters to minimize the error.
Validate the model using the testing data to ensure it generalizes well to unseen data.Evaluation and Optimization
Evaluate the model’s performance using metrics like accuracy, precision, recall, F1-score, etc.
Optimize the model by fine-tuning hyperparameters, selecting different features, or using more sophisticated algorithms.Deployment
Deploy the trained model into a production environment where it can make predictions on new data.
Monitor the model’s performance and update it as necessary.Maintenance
Regularly update the model with new data to maintain its accuracy and relevance.
Monitor for any changes in data distribution and adapt the model accordingly.
Key Concepts and TechniquesMachine Learning (ML)
Supervised Learning The model is trained on labeled data.
Unsupervised Learning The model identifies patterns in unlabeled data.
Semi-Supervised Learning Combination of labeled and unlabeled data.
Reinforcement Learning The model learns by interacting with the environment and receiving feedback.Deep Learning (DL)
Neural Networks Layers of interconnected nodes (neurons) that process data.
Convolutional Neural Networks (CNNs) Specialized for image data.
Recurrent Neural Networks (RNNs) Specialized for sequential data.Natural Language Processing (NLP)
Techniques for processing and understanding human language.
Includes tasks like language translation, sentiment analysis, and text generation.Algorithms
Gradient Descent Optimization algorithm for minimizing the error in the model.
Backpropagation Algorithm for training neural networks by adjusting weights.
Biological Analogies in AI DevelopmentGenetic Algorithms
Inspired by the process of natural selection.
Used to solve optimization problems by evolving solutions over generations.
Neural NetworksModeled after the human brain’s neural structure.
Consists of layers of neurons that process and transmit information.Reinforcement Learning
Analogous to how humans and animals learn from interactions with their environment.
Applying Biological Translation Theory
Protein SynthesisAnalogous to training models where the genetic code (data) is transcribed (preprocessed) and translated (trained) to produce a functional protein (model).
PhotosynthesisCan be seen as data transformation where sunlight (input data) is converted into energy (useful predictions).
Digestive SystemData ingestion, processing, and extracting valuable nutrients (insights) can be compared to how the digestive system processes food.
White Light Absorption
Splitting data into different components (features) to analyze and process each component separately, similar to how white light is split into different colors.
These biological analogies provide intuitive ways to understand complex AI processes and can inspire innovative approaches to AI development."
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Meanwhile, self-thinking artificial intelligence and robots have already been created. I see a participant who is also ignorant about this laughing out loud. Of course, he is also ignorant about understanding the Quran, so he will continue to talk nonsense like this. The verse says that living beings cannot be created. It is one thing to give life to something, it is quite another thing for it to be able to think or do something else.
Robots and computers that can think have already been made. And soon there will be more intelligent ones than us on the market.
Mankind will not be able to create a living being, but it can, and partly already has, doing artificial intelligence that is smarter than itself.
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The artificial intelligence called GPT - 4o answers you
"Artificial Intelligence (AI) is developed through a combination of various scientific and engineering disciplines, including computer science, mathematics, neuroscience, cognitive science, and more. The development process involves several key steps and components
Development Process of AI
Problem Definition
Identify the problem that needs to be solved.
Define the objectives and scope of the AI application.Data Collection and Preparation
Collect relevant data from various sources.
Clean and preprocess the data to make it suitable for training AI models.Algorithm Selection
Choose appropriate algorithms and models based on the problem at hand.
Common algorithms include machine learning (ML), deep learning (DL), and reinforcement learning (RL).Model Training
Split the data into training and testing sets.
Train the model using the training data by adjusting the model parameters to minimize the error.
Validate the model using the testing data to ensure it generalizes well to unseen data.Evaluation and Optimization
Evaluate the model’s performance using metrics like accuracy, precision, recall, F1-score, etc.
Optimize the model by fine-tuning hyperparameters, selecting different features, or using more sophisticated algorithms.Deployment
Deploy the trained model into a production environment where it can make predictions on new data.
Monitor the model’s performance and update it as necessary.Maintenance
Regularly update the model with new data to maintain its accuracy and relevance.
Monitor for any changes in data distribution and adapt the model accordingly.
Key Concepts and TechniquesMachine Learning (ML)
Supervised Learning The model is trained on labeled data.
Unsupervised Learning The model identifies patterns in unlabeled data.
Semi-Supervised Learning Combination of labeled and unlabeled data.
Reinforcement Learning The model learns by interacting with the environment and receiving feedback.Deep Learning (DL)
Neural Networks Layers of interconnected nodes (neurons) that process data.
Convolutional Neural Networks (CNNs) Specialized for image data.
Recurrent Neural Networks (RNNs) Specialized for sequential data.Natural Language Processing (NLP)
Techniques for processing and understanding human language.
Includes tasks like language translation, sentiment analysis, and text generation.Algorithms
Gradient Descent Optimization algorithm for minimizing the error in the model.
Backpropagation Algorithm for training neural networks by adjusting weights.
Biological Analogies in AI DevelopmentGenetic Algorithms
Inspired by the process of natural selection.
Used to solve optimization problems by evolving solutions over generations.
Neural NetworksModeled after the human brain’s neural structure.
Consists of layers of neurons that process and transmit information.Reinforcement Learning
Analogous to how humans and animals learn from interactions with their environment.
Applying Biological Translation Theory
Protein SynthesisAnalogous to training models where the genetic code (data) is transcribed (preprocessed) and translated (trained) to produce a functional protein (model).
PhotosynthesisCan be seen as data transformation where sunlight (input data) is converted into energy (useful predictions).
Digestive SystemData ingestion, processing, and extracting valuable nutrients (insights) can be compared to how the digestive system processes food.
White Light Absorption
Splitting data into different components (features) to analyze and process each component separately, similar to how white light is split into different colors.
These biological analogies provide intuitive ways to understand complex AI processes and can inspire innovative approaches to AI development."
"Dear Mazhar, the AI GPT - 4o continues to answer you
To understand how AI can develop the ability to think autonomously and creatively, we can look at the examples of AI systems like AlphaGo and AlphaZero, which learned to play games such as Go and chess through self-play.
Autonomous and Creative Thinking in AI
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Reinforcement Learning and Self-Play
Reinforcement Learning (RL) This is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize some notion of cumulative reward.
Self-Play The AI agent plays games against itself, allowing it to explore various strategies and improve over time without human intervention. -
AlphaGo
Initial Development AlphaGo, developed by DeepMind, was the first AI to defeat a professional human Go player. It combined traditional search tree methods with deep neural networks.
Learning Process AlphaGo was trained using a combination of supervised learning from human expert games and reinforcement learning by playing against itself. This self-play allowed it to discover new strategies and techniques that had not been seen before. -
AlphaZero
Generalized Approach AlphaZero took the concept further by generalizing the self-play approach to not only Go but also chess and shogi. Unlike AlphaGo, AlphaZero started with no knowledge beyond the basic rules of the games.
Learning from Scratch AlphaZero played millions of games against itself, continually learning and refining its strategies. It used deep neural networks to evaluate board positions and decide on the best moves.
Creative Strategies Through self-play, AlphaZero discovered and developed strategies that were previously unknown or rarely used by human players. It demonstrated a high level of creativity and strategic depth, often making moves that surprised even top human players.How AI Develops Autonomous Thinking
Exploration and Exploitation
Exploration The AI tries new moves and strategies, exploring the potential outcomes. This helps the AI discover innovative solutions.
Exploitation The AI leverages known successful strategies to win games. Balancing exploration and exploitation allows the AI to refine its strategies effectively.
Continuous LearningIteration By continuously playing games against itself, the AI iterates on its strategies, learning from each game and improving its performance over time.
Adapting to New Situations As the AI encounters new situations and configurations, it adapts its strategies to handle them, showcasing its ability to think autonomously.
Evaluation and Decision-MakingNeural Networks These are used to evaluate board positions and predict the outcomes of different moves. The AI learns to recognize patterns and make decisions based on these evaluations.
Search Algorithms Techniques like Monte Carlo Tree Search (MCTS) are used to explore possible future moves and their consequences, helping the AI to plan several steps ahead.Key Components Enabling Autonomous AI
Deep Learning
Representation Learning Neural networks learn to represent complex game states in a way that makes it easier to evaluate and decide on moves.
Feature Extraction The AI extracts important features from the game state, allowing it to understand and process the game at a high level.Reinforcement Learning
Reward Signals The AI receives rewards for winning games and penalties for losing. These signals guide the learning process, helping the AI to develop effective strategies.
Policy Networks These networks suggest the next move based on the current game state. The AI learns to improve its policy network through self-play.Self-Improvement
Adversarial Training Playing against itself creates a continuously challenging environment, pushing the AI to improve constantly.
Unsupervised Learning Without relying on human examples, the AI develops its own understanding and strategies, leading to unique and innovative playstyles.Conclusion
AI systems like AlphaGo and AlphaZero demonstrate how AI can achieve autonomous and creative thinking through reinforcement learning and self-play. By continuously playing and learning from their own experiences, these AIs develop sophisticated strategies and demonstrate a level of strategic creativity that rivals and even surpasses human experts. This approach can be generalized to other domains, enabling AI to think independently and solve complex problems in innovative ways. -
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Meanwhile, self-thinking artificial intelligence and robots have already been created. I see a participant who is also ignorant about this laughing out loud. Of course, he is also ignorant about understanding the Quran, so he will continue to talk nonsense like this. The verse says that living beings cannot be created. It is one thing to give life to something, it is quite another thing for it to be able to think or do something else.
Robots and computers that can think have already been made. And soon there will be more intelligent ones than us on the market.
Mankind will not be able to create a living being, but it can, and partly already has, doing artificial intelligence that is smarter than itself.
When two people debate, each other can call each other ignorant to suppress the view of each other so one of those can claim the upper hand. It's normal in debates.. But, debate is not between two people literally, but it is witnessed by those who read the debate with their own intellect and they have the capacity to comprehend whose points are ignorant and meaningless.. For example, one can claim the Quran is an invented tale of humans but the intelligent would perceive otherwise..ignorants are those who suppress the truth to outshine with their own view.. Intelligent are those who bring to light the truth and they don't surrender to ignorant and falsehood views..
The self-claimant is an ignorant way ..
AI cannot think on its own because its brain is fed by another wise brain and programmed.. If one cannot comprehend this manifest truth, indeed he is ignorant.. -
It can be thought of as an artificial brain.
And it will be a brain that can do in minutes what you can think and calculate in millions of years.
Tanks are also made by humans, but tanks are more robust than humans.
People also make airplanes, but airplanes can go higher than humans.
In the same way, human beings are producing an intelligence that is smarter than themselves.
And as I said, they have started to think freely and originally. They had already started, but now it has reached a level that even those who don't believe in it can see. They have the intelligence of a child in the versions that are given to us for free now. In the versions not shown to us, they are certainly even more advanced. and tomorrow they will be much more advanced.
To prevent the ignorant participant from parasitizing and polluting the site, I am reproducing the AI's response in its entirety here.
Dear Mazhar, The artificial intelligence called GPT - 4o answers you
"Artificial Intelligence (AI) is developed through a combination of various scientific and engineering disciplines, including computer science, mathematics, neuroscience, cognitive science, and more. The development process involves several key steps and components
Development Process of AI
Problem Definition
Identify the problem that needs to be solved.
Define the objectives and scope of the AI application.Data Collection and Preparation
Collect relevant data from various sources.
Clean and preprocess the data to make it suitable for training AI models.Algorithm Selection
Choose appropriate algorithms and models based on the problem at hand.
Common algorithms include machine learning (ML), deep learning (DL), and reinforcement learning (RL).Model Training
Split the data into training and testing sets.
Train the model using the training data by adjusting the model parameters to minimize the error.
Validate the model using the testing data to ensure it generalizes well to unseen data.Evaluation and Optimization
Evaluate the model's performance using metrics like accuracy, precision, recall, F1-score, etc.
Optimize the model by fine-tuning hyperparameters, selecting different features, or using more sophisticated algorithms.Deployment
Deploy the trained model into a production environment where it can make predictions on new data.
Monitor the model's performance and update it as necessary.Maintenance
Regularly update the model with new data to maintain its accuracy and relevance.
Monitor for any changes in data distribution and adapt the model accordingly.
Key Concepts and TechniquesMachine Learning (ML)
Supervised Learning The model is trained on labeled data.
Unsupervised Learning The model identifies patterns in unlabeled data.
Semi-Supervised Learning Combination of labeled and unlabeled data.
Reinforcement Learning The model learns by interacting with the environment and receiving feedback.Deep Learning (DL)
Neural Networks Layers of interconnected nodes (neurons) that process data.
Convolutional Neural Networks (CNNs) Specialized for image data.
Recurrent Neural Networks (RNNs) Specialized for sequential data.Natural Language Processing (NLP)
Techniques for processing and understanding human language.
Includes tasks like language translation, sentiment analysis, and text generation.Algorithms
Gradient Descent Optimization algorithm for minimizing the error in the model.
Backpropagation Algorithm for training neural networks by adjusting weights.
Biological Analogies in AI DevelopmentGenetic Algorithms
Inspired by the process of natural selection.
Used to solve optimization problems by evolving solutions over generations.
Neural NetworksModeled after the human brain's neural structure.
Consists of layers of neurons that process and transmit information.Reinforcement Learning
Analogous to how humans and animals learn from interactions with their environment.
Applying Biological Translation Theory
Protein SynthesisAnalogous to training models where the genetic code (data) is transcribed (preprocessed) and translated (trained) to produce a functional protein (model).
PhotosynthesisCan be seen as data transformation where sunlight (input data) is converted into energy (useful predictions).
Digestive SystemData ingestion, processing, and extracting valuable nutrients (insights) can be compared to how the digestive system processes food.
White Light Absorption
Splitting data into different components (features) to analyze and process each component separately, similar to how white light is split into different colors.
These biological analogies provide intuitive ways to understand complex AI processes and can inspire innovative approaches to AI development."
"Dear Mazhar, the AI GPT - 4o continues to answer you
To understand how AI can develop the ability to think autonomously and creatively, we can look at the examples of AI systems like AlphaGo and AlphaZero, which learned to play games such as Go and chess through self-play.
Autonomous and Creative Thinking in AI
-
Reinforcement Learning and Self-Play
Reinforcement Learning (RL) This is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize some notion of cumulative reward.
Self-Play The AI agent plays games against itself, allowing it to explore various strategies and improve over time without human intervention. -
AlphaGo
Initial Development AlphaGo, developed by DeepMind, was the first AI to defeat a professional human Go player. It combined traditional search tree methods with deep neural networks.
Learning Process AlphaGo was trained using a combination of supervised learning from human expert games and reinforcement learning by playing against itself. This self-play allowed it to discover new strategies and techniques that had not been seen before. -
AlphaZero
Generalized Approach AlphaZero took the concept further by generalizing the self-play approach to not only Go but also chess and shogi. Unlike AlphaGo, AlphaZero started with no knowledge beyond the basic rules of the games.
Learning from Scratch AlphaZero played millions of games against itself, continually learning and refining its strategies. It used deep neural networks to evaluate board positions and decide on the best moves.
Creative Strategies Through self-play, AlphaZero discovered and developed strategies that were previously unknown or rarely used by human players. It demonstrated a high level of creativity and strategic depth, often making moves that surprised even top human players.How AI Develops Autonomous Thinking
Exploration and Exploitation
Exploration The AI tries new moves and strategies, exploring the potential outcomes. This helps the AI discover innovative solutions.
Exploitation The AI leverages known successful strategies to win games. Balancing exploration and exploitation allows the AI to refine its strategies effectively.
Continuous LearningIteration By continuously playing games against itself, the AI iterates on its strategies, learning from each game and improving its performance over time.
Adapting to New Situations As the AI encounters new situations and configurations, it adapts its strategies to handle them, showcasing its ability to think autonomously.
Evaluation and Decision-MakingNeural Networks These are used to evaluate board positions and predict the outcomes of different moves. The AI learns to recognize patterns and make decisions based on these evaluations.
Search Algorithms Techniques like Monte Carlo Tree Search (MCTS) are used to explore possible future moves and their consequences, helping the AI to plan several steps ahead.Key Components Enabling Autonomous AI
Deep Learning
Representation Learning Neural networks learn to represent complex game states in a way that makes it easier to evaluate and decide on moves.
Feature Extraction The AI extracts important features from the game state, allowing it to understand and process the game at a high level.Reinforcement Learning
Reward Signals The AI receives rewards for winning games and penalties for losing. These signals guide the learning process, helping the AI to develop effective strategies.
Policy Networks These networks suggest the next move based on the current game state. The AI learns to improve its policy network through self-play.Self-Improvement
Adversarial Training Playing against itself creates a continuously challenging environment, pushing the AI to improve constantly.
Unsupervised Learning Without relying on human examples, the AI develops its own understanding and strategies, leading to unique and innovative playstyles.Conclusion
AI systems like AlphaGo and AlphaZero demonstrate how AI can achieve autonomous and creative thinking through reinforcement learning and self-play. By continuously playing and learning from their own experiences, these AIs develop sophisticated strategies and demonstrate a level of strategic creativity that rivals and even surpasses human experts. This approach can be generalized to other domains, enabling AI to think independently and solve complex problems in innovative ways." -
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AI can't actually think for itself, so I wouldn't call it truly intelligent.
How can one who can't think for themselves be called intelligent.. That's why rightly worded AI i.e. Artificial intelligence... it never thinks.. try to grasp and leave ignorance..
That's it..
copy and pasting a long list won't make the core of AI become other than what it has.. laugh
good luck with your adamance .... -
To prevent the ignorant participant from parasitizing and polluting the site, I am reproducing the AI's response in its entirety here.
Dear Mazhar, The artificial intelligence called GPT - 4o answers you
"Artificial Intelligence (AI) is developed through a combination of various scientific and engineering disciplines, including computer science, mathematics, neuroscience, cognitive science, and more. The development process involves several key steps and components
Development Process of AI
Problem Definition
Identify the problem that needs to be solved.
Define the objectives and scope of the AI application.Data Collection and Preparation
Collect relevant data from various sources.
Clean and preprocess the data to make it suitable for training AI models.Algorithm Selection
Choose appropriate algorithms and models based on the problem at hand.
Common algorithms include machine learning (ML), deep learning (DL), and reinforcement learning (RL).Model Training
Split the data into training and testing sets.
Train the model using the training data by adjusting the model parameters to minimize the error.
Validate the model using the testing data to ensure it generalizes well to unseen data.Evaluation and Optimization
Evaluate the model's performance using metrics like accuracy, precision, recall, F1-score, etc.
Optimize the model by fine-tuning hyperparameters, selecting different features, or using more sophisticated algorithms.Deployment
Deploy the trained model into a production environment where it can make predictions on new data.
Monitor the model's performance and update it as necessary.Maintenance
Regularly update the model with new data to maintain its accuracy and relevance.
Monitor for any changes in data distribution and adapt the model accordingly.
Key Concepts and TechniquesMachine Learning (ML)
Supervised Learning The model is trained on labeled data.
Unsupervised Learning The model identifies patterns in unlabeled data.
Semi-Supervised Learning Combination of labeled and unlabeled data.
Reinforcement Learning The model learns by interacting with the environment and receiving feedback.Deep Learning (DL)
Neural Networks Layers of interconnected nodes (neurons) that process data.
Convolutional Neural Networks (CNNs) Specialized for image data.
Recurrent Neural Networks (RNNs) Specialized for sequential data.Natural Language Processing (NLP)
Techniques for processing and understanding human language.
Includes tasks like language translation, sentiment analysis, and text generation.Algorithms
Gradient Descent Optimization algorithm for minimizing the error in the model.
Backpropagation Algorithm for training neural networks by adjusting weights.
Biological Analogies in AI DevelopmentGenetic Algorithms
Inspired by the process of natural selection.
Used to solve optimization problems by evolving solutions over generations.
Neural NetworksModeled after the human brain's neural structure.
Consists of layers of neurons that process and transmit information.Reinforcement Learning
Analogous to how humans and animals learn from interactions with their environment.
Applying Biological Translation Theory
Protein SynthesisAnalogous to training models where the genetic code (data) is transcribed (preprocessed) and translated (trained) to produce a functional protein (model).
PhotosynthesisCan be seen as data transformation where sunlight (input data) is converted into energy (useful predictions).
Digestive SystemData ingestion, processing, and extracting valuable nutrients (insights) can be compared to how the digestive system processes food.
White Light Absorption
Splitting data into different components (features) to analyze and process each component separately, similar to how white light is split into different colors.
These biological analogies provide intuitive ways to understand complex AI processes and can inspire innovative approaches to AI development."
"Dear Mazhar, the AI GPT - 4o continues to answer you
To understand how AI can develop the ability to think autonomously and creatively, we can look at the examples of AI systems like AlphaGo and AlphaZero, which learned to play games such as Go and chess through self-play.
Autonomous and Creative Thinking in AI
-
Reinforcement Learning and Self-Play
Reinforcement Learning (RL) This is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize some notion of cumulative reward.
Self-Play The AI agent plays games against itself, allowing it to explore various strategies and improve over time without human intervention. -
AlphaGo
Initial Development AlphaGo, developed by DeepMind, was the first AI to defeat a professional human Go player. It combined traditional search tree methods with deep neural networks.
Learning Process AlphaGo was trained using a combination of supervised learning from human expert games and reinforcement learning by playing against itself. This self-play allowed it to discover new strategies and techniques that had not been seen before. -
AlphaZero
Generalized Approach AlphaZero took the concept further by generalizing the self-play approach to not only Go but also chess and shogi. Unlike AlphaGo, AlphaZero started with no knowledge beyond the basic rules of the games.
Learning from Scratch AlphaZero played millions of games against itself, continually learning and refining its strategies. It used deep neural networks to evaluate board positions and decide on the best moves.
Creative Strategies Through self-play, AlphaZero discovered and developed strategies that were previously unknown or rarely used by human players. It demonstrated a high level of creativity and strategic depth, often making moves that surprised even top human players.How AI Develops Autonomous Thinking
Exploration and Exploitation
Exploration The AI tries new moves and strategies, exploring the potential outcomes. This helps the AI discover innovative solutions.
Exploitation The AI leverages known successful strategies to win games. Balancing exploration and exploitation allows the AI to refine its strategies effectively.
Continuous LearningIteration By continuously playing games against itself, the AI iterates on its strategies, learning from each game and improving its performance over time.
Adapting to New Situations As the AI encounters new situations and configurations, it adapts its strategies to handle them, showcasing its ability to think autonomously.
Evaluation and Decision-MakingNeural Networks These are used to evaluate board positions and predict the outcomes of different moves. The AI learns to recognize patterns and make decisions based on these evaluations.
Search Algorithms Techniques like Monte Carlo Tree Search (MCTS) are used to explore possible future moves and their consequences, helping the AI to plan several steps ahead.Key Components Enabling Autonomous AI
Deep Learning
Representation Learning Neural networks learn to represent complex game states in a way that makes it easier to evaluate and decide on moves.
Feature Extraction The AI extracts important features from the game state, allowing it to understand and process the game at a high level.Reinforcement Learning
Reward Signals The AI receives rewards for winning games and penalties for losing. These signals guide the learning process, helping the AI to develop effective strategies.
Policy Networks These networks suggest the next move based on the current game state. The AI learns to improve its policy network through self-play.Self-Improvement
Adversarial Training Playing against itself creates a continuously challenging environment, pushing the AI to improve constantly.
Unsupervised Learning Without relying on human examples, the AI develops its own understanding and strategies, leading to unique and innovative playstyles.Conclusion
AI systems like AlphaGo and AlphaZero demonstrate how AI can achieve autonomous and creative thinking through reinforcement learning and self-play. By continuously playing and learning from their own experiences, these AIs develop sophisticated strategies and demonstrate a level of strategic creativity that rivals and even surpasses human experts. This approach can be generalized to other domains, enabling AI to think independently and solve complex problems in innovative ways." -
