Qur’ān Propounded Translation Methodology for transference to Non-Arab World
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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." -
-
Peace everyone….
Now, let’s go back in time… tempt
Let’s compare Adam with AI !
Since normal human beings are born and seek from childhood, let’s take the example of Adam in particular… Allah created Adam and made him known everything but left him free to think and reflect on his own wherewith a DECISION is generated.. That’s why Allah punishes humans in Hell because of the decision humans took neglecting the truth and opting for falsehood..
On the other hand, AI is fed with all possible decisions (unlike Adam) that it can make through which it is programmed.. Had Allah also done the same with Adam, Allah can never punish the children of Adam because Allah knows that’s what the human being would in the future bring forth since Allah has programmed it in that manner and it would not go beyond how it is programmed… You can take examples from animals.. They are programmed by Allah in their own nature and it won’t go beyond it and whatever they do is as they were programmed i.e. within that frame… But not human and Jinn… We are not programmed and thus not controlled by Allah in our thought process and we don’t know what we will do throughout our life..
AI won't think on its own... nope nope nope
thank you, everyone.. -
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." -
-
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.That is fine. Perhaps same is what I tried to render the content.
24.20. The original text of Qur’ān is stated as inscribed on (لَوْحٛ) a wide and thin, gleamed and glistened plate which is all time safe (مَّحْفُوظِۭ). Both the books, Mother/Principal Book and Qur’ān, share the qualitative attribute of explicitly explicative—conveyor of information in succinct, individuated, distinct and crystallized manner, functioning like an exegete. It reveals it has distinct chapters which in itself constitute a book of distinct concept. The biographies of different type of peoples are assigned distinct name and how are they penned is disclosed which further confirms that the Principal Book is in the language resembling the code language of the Computer
كَلَّآ إِنَّ كِتَٟبَ ٱلْفُجَّارِ لَفِى سِجِّيـنٛ ٧وَمَآ أَدْرَىٰكَ مَا سِجِّيـنٚ ٨كِتَٟبٚ مَّرْقُومٚ ٩
Nay, that will not avail; the fact is that the Book/biography of fearless transgressors/wicked is detailed in that given the title Sijjeen — And what is that which could give you the perception as to what is Sijjeen — That is a book which has the characteristic of written with dots.
24.21. As against the Book of the people who will be imprisoned in the Hell-Prison, the biographies of those destined to Paradise is in separate Book recorded in the same manner
كَلَّآ إِنَّ كِتَٟبَ ٱلْأَبْرَارِ لَفِى عِلِّيِّيـنَ١٨وَمَآ أَدْرَىٰكَ مَا عِلِّيُّونَ ١٩كِتَٟبٚ مَّرْقُومٚ ٢٠
Nay, indeed the Book/biography of the pious is certainly incorporated in Illiyin — And what is that which could give you the perception as to what is Illiyun — That is a book (record of elevated/honoured people) which has the characteristic of written with dots —24.22. The last elliptical sentence (كِتَٟبٚ مَّرْقُوم) with subject elided described how those books are penned/inscribed. Passive participle as adjective is descriptive term for the said book from Root ر ق م which embeds the perception of streak, calligraphy, penmanship and writing and that which resembles it; writing with dots or points.
وَكُلَّ إِنْسَانٛ أَلْزَمْنَٟهُ طَـٟٓئِرَهُۥ فِـى عُنُقِهِۦۖ وَنُخْرِجُ لَهُۥ يَوْمَ ٱلْقِيَٟمَةِ كِتَٟبٙا يَلْقَىٰهُ مَنْشُورٙا ١٣
ٱقْرَأْ كِتَٟبَكَ كَفَىٰ بِنَفْسِكَ ٱلْيَوْمَ عَلَيْكَ حَسِيبٙا ١٤
Every human of free-will is bound by his deeds. Our Majesty has permanently tied in his neck all hollow deeds of ill result as accusation/ charge sheet —And Our Majesty will bring it out in writing-print out for him on the Day of Rising which he would see openly —; He will be asked; "You read your book - biography — Today, you suffice to take account for yourself as accountability judge."24.23. Man's fate - augury is what will happen to him ultimately, which will depend upon his ledger of deeds. It is account of voluntary action and not involuntary actions. Forebrain is responsible for voluntary action, hindbrain is responsible for involuntary action. This ayah explains that man's ledger is scrolled in his neck. Voluntary actions are done by commands given by motor signals which pass through the descending tracts of the central nervous system starting from brain to spinal cord. Motor signals have to pass through the neck.
وَوُضِعَ ٱلْـكِـتَٟبُ فَـتَـرَى ٱلْمُجْرِمِيـنَ مُشْفِقِيـنَ مِمَّا فِيهِ
وَيَقُولُونَ يَٟوَيْلَتَنَا مَالِ هَـٰذَا ٱلْـكِـتَٟبِ لَا يُغَادِرُ صَغِيـرَةٙ وَلَا كَبِيـرَةٙ إِلَّآ أَحْصَىٰـهَاۚ
وَوَجَدُوا۟ مَا عَمِلُوا۟ حَاضِرٙاۗ وَلَا يَظْلِمُ رَبُّكَ أَحَدٙا ٤٩
And the written biography/Book of record is laid open —Thereby, you will see the criminals in ashamed and embarrassed condition by reading what is written therein. And they will say, "Woe is for us; what sort of Book is this —Neither it leaves mention of a minor thing nor of a major one except that it has enumerated it." And having perused the Book they visualized from memory as present what they had done. And the Sustainer Lord of you the Messenger will not do any injustice to any individual.24.24. Everything done either innovatively for the first time or repeatedly whether of little and great ramification is honestly and truthfully inscribed on aligned lines
وَلَقَدْ أَهْلَـكْنَآ أَشْيَاعَكُـمْ فَـهَلْ مِن مُّدَّكِـرٛ ٥١
وَكُلُّ شَـىْءٛ فَعَلُوهُ فِـى ٱلزُّبُرِ ٥٢وَكُلُّ صَغِيـرٛ وَكَبِيـرٛ مُّسْتَطَرٌ ٥٣
And indeed Our Majesty did cause the annihilation of peoples of your species/class — Thereat, is there one who consciously and purposely saves it in memory, comprehends and recalls to mention-takes lesson and admonition?
Beware,every thing they innovatively did is recorded in the Documents. Mind it, each and every thing of small and large manifestation and ramification is penned down.نٓ ۚ وَٱلْقَلَمِ وَمَا يَسْطُرُونَ١
Noon, the ink pot and swearing is by the Pen; And by the record which they (the Angels) keep recording in black and white honestly and truthfully.
0
24.25. It نٓ is the twenty sixth consonant of Arabic Alphabet with a sound stretching glyph above it. It has no vowel. However, its original pronunciation sound has built in vowel-sound in it. Individually also, it sounds like a syllable-نُونْ comprising sound of CVC-Consonant-Vowel-Consonant. Its shape is like an ink-pot, with a dot which emerges the moment tip of the pen touches the ink. It is just the dot from where everything expands. The word نُونْ signifies Whale, a mammal perhaps with the largest brain mass. Interestingly, the following words have also the linkage with the ink-pot and brain. Next is a prepositional phrase relating to the elided verb signifying, what follows is being stated under oath. It is common perception that the objective of stating something on oath is to emphasize the certainty and let the listener pay focused attention to realize the importance of recognizing that which is going to be stated.24.26. Not only all physical activities go into the written record but also every uttered word is penned down as told earlier
وَلَقَدْ خَلَقْنَا ٱلْإِنسَٟنَ وَنَعْلَمُ مَا تُوَسْوِسُ بِهِۦ نَفْسُهُۥۖ
وَنَـحْنُ أَقْرَبُ إِلَيْهِ مِنْ حَبْلِ ٱلْوَرِيدِ ١٦إِذْ يَتَلَقَّى ٱلْمُتَلَقِّيَانِ عَنِ ٱلْيَـمِيـنِ وَعَنِ ٱلشِّمَالِ قَعِيدٚ ١٧
مَّا يَلْفِظُ مِن قَوْلٛ إِلَّا لَدَيْهِ رَقِيبٌ عَتِيدٚ ١٨
Be mindful; Our Majesty have created the Man. And be cautious; Our Majesty fully know that thought - desire-lust which his inner-self keeps sub-vocally inspiring-alluring him.
And Our Majesty are even at that point in time nearer to that thought than the Communicating-Transmitting Cord (vocal cord)— When the two peculiar Efficient Receptors continuously keep efficiently receiving-confronting-acquiring this thought regularly—While located/ seated symmetrically; regularly confronting that coming from the right side and from the left side.
He (Man) emits not a segment of an expression - syllables of a word in the open air but a smartly ever alert and present guard is nearby him to record it in writing.24.27. The word يَلْفِظُ is the solitary word made from Root "ل ف ظ " that occurs in the Qur’ān. It seems indicative that once we utter a word from mouth it attains permanence in existence. It goes in air to stay permanently; the speaker cannot take it back. Hence, we should think twice before uttering a word. The spoken word instantly goes in record in writing
وَٱللَّهُ يَكْتُبُ مَا يُبَيِّتُونَۖ
Be mindful; Allah the Exalted records in writing all that they secretively discuss during night.
أَمْ يَحْسَبُونَ أَنَّا لَا نَسْمَعُ سِرَّهُـمْ وَنَجْوَىٰـهُـمۚ بَلَـىٰ وَرُسُلُنَا لَدَيْـهِـمْ يَكْتُبُونَ ٨٠
Or do they think that Our Majesty listen not their secret whispers and counsels in isolation —Their perception is false; what to say of listening, the deputed angels by Our Majesty are by their sides who are recording everything in writing.I hope it clarifies.
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Many thanks, Emre.
I am trying to grasp it.
Few years back Dr. Kais consulted me about Ontology and asked how many questions can I answer by quoting from Qur'an. I told him any question relevant to human conduct, psyche and information needed for salvation can be answered.
Your this para is interesting
//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."//On the very first page of Quran-Corpus of my website
https//haqeeqat.pk/Quran.Corpus-1.htmit is mentioned and linked
معنی اور مفہوم اور مصنف کے نقطہ نظر تک پہنچنے کے لئے سات منزلیں۔ قرءان مجید کے باہم مربوط سات مدار /محورجن میں متن گردش کرتا ہے۔Qur’ān isٱلنُّورَ; the White Light; Source of Enlightenment - how to absorb its seven colours
http//haqeeqat.pk/TranslationOfQuranSevenLayeredAnalysis.htm -
In a few years, artificial intelligence will be able to provide the best and most unbiased translation of the Quran.
No, AI is simply parroting what's on the internet and what it was trained on. If AI is so smart, why not ask it how much a wife and parents inherit according to the Qur'an?
According to what you posted many times, the wife gets 1/4, while each parent gets nothing, and 3/4 goes to nobody.
STANFORD SCIENTISTS FIND THAT YES, CHATGPT IS GETTING STUPIDER
https//futurism.com/the-byte/stanford-chatgpt-getting-dumberLikewise, it's clueless especially on simple math, example
ChatGPT
I'm pretty good with basic math! What do you need help with?How many letters in Bismillah?
ChatGPT
The phrase "Bismillah" (بسم الله) consists of 8 letters in the Arabic script.Ask AI the same question above a few times to see if it's as dumb as a rock.
