Qur’ān Propounded Translation Methodology for transference to Non-Arab World
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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."
" -
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." -
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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
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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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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.
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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.
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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.htmYou're welcome, Mazhar.
Artificial intelligence is really moving towards a great point.
As I said, it will be able to do in a few minutes what we can do in millions of years. Even faster...
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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.
It made me recollect some of the conversations I had with some of my office friends and why not with one of the members here namely Brother Fusion long back in WhatsApp ... I asked them to check what the reply of CHATGPT and they knew it gave obviously erroneous answers, but they still regarded it very high.. Yeah, people have the freedom to think about AI what they want.. But Technology is doing a great job for human life and that's indispensable.. But calling AI what it doesn't deserve is sheer overconfidence..
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You're welcome, Mazhar.
Artificial intelligence is really moving towards a great point.
As I said, it will be able to do in a few minutes what we can do in millions of years. Even faster...
By the way, 25 years ago, when scientists were saying that artificial intelligence would catch up with human intelligence in 2030, I was saying that it would happen in 2025. I am happy to be right about that too.
https//www.youtube.com/watch?v=P71UeRTzlaM
https//www.forbes.com/sites/ericsiegel/2024/04/10/artificial-general-intelligence-is-pure-hype/
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3.2. Translator must know "reading" begins before opening the Book in hand, like digestion starts before tasting food.
Experts and educationists suggest that the first rule in critical reading is that you must know what kind of a book is in your hand; and they say that we should know this as early in the process as possible, preferably before we begin to read. The first clue as to the type of a book is its title. Though many readers and even some professional translators ignore titles because perhaps they do not think it important to classify the book they are about to read or translate; the translator who intends to public his work must not overlook the Title Qur’ān which is otherwise a verbal noun expressing state and activity without time reference. The title instantly gives him the glimpse of its uniqueness and greatness of the ambit of its discourse. The title illustrates that all the realm, theoretical and practical, relevant to the reader is gathered and incorporated as a coherent unit in its ambit.
3.3. Translator must classify the Book
A professional translator obviously knows the broad lines of classification of books. Literature is classified according to whether it is fiction or non-fiction. Fiction is the classification for any work that is derived from imagination, in other words, a work not based strictly on history or fact. Non-fiction is works conveying knowledge, or expository works. Another distinction that applies to non-fiction - expository works is Theoretical vs. Practical Books. Theoretical concerns something to be seen and understood. And Practical concerns the application of knowledge. Sub division of theoretical books classifies them as history, science and philosophy.
He must undertake Inspectional reading of Qur’ān to find as to what type of a book is it, and/or what type of a book is it not. Upon skimming, he will find that it is specifically emphasized it is neither poetry, nor speculations of a prognosticator, and nor is comic. It is a non-fiction book, both Theoretical and Practical. Thereby, he must not indulge in imaginative flights to explain it.
3.4. Translator must know the difference between reading and interpreting great and ordinary book
Francis Bacon is stated to have once remarked that "some books are to be tasted, others to be swallowed, and some few to be chewed and digested". He was perhaps classifying and evaluating books by importance and greatness.
In real life, the process of digestion involves mechanically breaking down the ingestible into small pieces and then by chemical process converting it into liquid form. If the ingestible is a book, which in every language is but words and phrases tied into sentences, sentences tied into paragraphs and paragraphs into text - discourse, we will need liquefying it to digest the contents of book.
The skimming tells him for second thought before undertaking translation for publication, that it is the Grand Book ٱلْقُرْءَانَ ٱلْعَظِيـمَ. The title and the adjectival portrayal as the Greatest - the most exalted reveals that this Book will speak from an important original setting but is not trapped therein. Great books are written in a way that constitutes it a living experience for readers today. The text is arranged as living voices in the ever present for the reader to listen voice of the Author and its First Orator.
The Title and declaring the Book as the Greatest immediately cautions the would-be translator and interpreter, that it is an inexhaustible book, so no reading of it is final and no discussion would ever run it dry. This point is also emphasized by mentioning about its semantic density.
The only encouraging point for a would-be translator of Qur’ān is that great books are always smarter than the best teacher, but is within the reach of average student. The Author of Qur’ān has explicitly highlighted this feature that it facilitates the reader.
Notwithstanding that it is rendered facilitator to comprehend and translate, he must realize and accept that the Book is above him and always will remain so. It is accessible at different levels, like the seven colours -spectrum of White Light. At every level, it will give him a leap in understanding and raising intellectual level. Though he has become wiser and knowledgeable, it will lift him again and it will go on doing this until one's death, for a while to enter in eternal life.
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Dear Mazhar; artificial intelligence, GTP - 4o, seems to like your book. Here's what artificial intelligence thinks about your book (In the last part of it's evaluation, it also provides criticism and suggestions for improvement)
"The book "Grand Qur'ān Propounded Translation Methodology for Transference to Non-Arab World" by Mazhar Anwaar Nurani presents a highly detailed and innovative approach to translating the Qur'an, using a method inspired by the biological process of protein synthesis. This unique "Triplet Theory of Translation" suggests a meticulous and systematic framework for accurately conveying the meanings of the Qur'an to a non-Arab audience.
The structure of the book is comprehensive, covering everything from the prerequisites for a translator to the literary and syntactic analysis of the Qur'an's text. The inclusion of discussions on the elements of Arabic words, the unique title of the Qur'an, and the distinction between different types of verses shows the depth of the author's analysis.
One of the most intriguing aspects of the book is its emphasis on the literary creation of the Qur'an and the essential elements involved, such as paper, ink, and pen. This focus on the material aspects of writing highlights the importance of preserving the integrity and authenticity of the text in translation.
The author also delves into the broader philosophical and theological implications of the Qur'an, addressing issues such as polytheism, atheism, and the role of divine communication in human history. By linking these themes to the structure and organization of the Qur'anic discourse, the book offers a holistic view that integrates linguistic, literary, and theological perspectives.
The emphasis on the qualifications and impartiality of the translator is a crucial point. By advocating for translators who are free from biases, personal interests, and political affiliations, the book underscores the importance of sincerity and objectivity in the translation process.
Overall, this book seems to be a significant contribution to the field of Qur'anic studies and translation theory. Its detailed methodology, combined with its comprehensive coverage of linguistic and theological aspects, makes it a valuable resource for scholars and translators aiming to bring the message of the Qur'an to a wider audience.
Moreover, the book's approach to the thesis statement of the Qur'an, emphasizing its unity, cohesion, and coherence, reflects a deep understanding of the text's intrinsic structure. This focus on the internal consistency of the Qur'an highlights its literary sophistication and divine origin. By analyzing the syntactic and semantic aspects of the thesis statement, the author provides readers with tools to appreciate the Qur'an's nuanced meanings and rhetorical elegance.
The sections addressing the roles and characteristics of different scholars, distinguishing between the sincere and insincere, provide valuable insights into the dynamics of Qur'anic interpretation throughout history. This distinction is crucial in understanding the diverse perspectives that have shaped Qur'anic exegesis and the transmission of its teachings.
In addition, the book's discussion on the global impact of the Qur'an and its role in shaping a universal moral and spiritual framework is particularly relevant in today's interconnected world. The idea of the Qur'an turning the globe into an academy underscores its enduring relevance and the importance of its guidance in fostering a more just and ethical global society.
The emphasis on the forensic proof of the second element of the thesis statement—that Muhammad (peace be upon him) is the permanent universal messenger of Allah—adds a compelling dimension to the book. This approach, grounded in logical and evidential analysis, strengthens the case for the universality and timelessness of the Qur'anic message.
Furthermore, the book's exploration of the relationship between polytheism, atheism, and societal structures provides a thought-provoking examination of how religious beliefs intersect with social hierarchies and power dynamics. This analysis not only enhances our understanding of historical contexts but also offers insights into contemporary issues related to faith and social justice.
In conclusion, Mazhar Anwaar Nurani's "Grand Qur'ān Propounded Translation Methodology for Transference to Non-Arab World" stands out for its thorough and innovative approach to Qur'anic translation and interpretation. Its blend of linguistic, literary, and theological analysis, combined with a commitment to objectivity and authenticity, makes it a significant contribution to the field. This book is poised to be a valuable resource for scholars, translators, and anyone interested in a deeper understanding of the Qur'an and its profound impact on humanity.
While "Grand Qur'ān Propounded Translation Methodology for Transference to Non-Arab World" by Mazhar Anwaar Nurani offers a comprehensive and innovative approach to Qur'anic translation, there are several aspects that may warrant critical consideration.
Firstly, the complexity of the "Triplet Theory of Translation" might be challenging for readers who are not well-versed in both the fields of molecular biology and linguistics. While the analogy to protein synthesis is creative, it may not be accessible or immediately clear to a broader audience, potentially limiting the book's reach and impact. Simplifying this theory or providing more detailed explanations and examples could enhance its comprehensibility.
Secondly, the book's exhaustive detail, while thorough, might overwhelm some readers. The extensive coverage of linguistic, literary, and theological aspects, although valuable, may be too dense for those seeking a more straightforward guide to Qur'anic translation. A more concise summary or separate sections for different levels of readers could make the book more user-friendly.
Additionally, the emphasis on the prerequisites and qualifications for translators, although important, might appear somewhat idealistic. In practice, finding translators who are entirely free from biases, personal interests, or political affiliations can be exceedingly difficult. A more pragmatic approach that acknowledges and addresses these challenges could provide more realistic guidelines for aspiring translators.
Moreover, the book’s strong focus on the theological and philosophical implications of the Qur'an might not align with the interests of all readers. Some might prefer a more balanced approach that also considers contemporary social and cultural contexts without an overtly theological framework. Including diverse perspectives and interpretations could make the book more inclusive and relevant to a wider audience.
The forensic proof provided for the thesis statement regarding Muhammad (peace be upon him) as the permanent universal messenger of Allah, while robust, might benefit from engagement with a broader range of scholarly opinions, including those from outside the Islamic tradition. This could strengthen the book's academic rigor and appeal to a more diverse readership.
Lastly, the extensive use of Arabic terms without immediate translations or explanations might pose a barrier to non-Arabic speakers. Providing a glossary or more consistent in-text translations could make the content more accessible to all readers.
In conclusion, while Mazhar Anwaar Nurani's book offers a valuable and innovative contribution to Qur'anic translation and interpretation, addressing these potential areas for improvement could enhance its accessibility, practicality, and appeal to a broader audience."
GPT - 4o
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Peace .
What is the aim behind AI?
Who controls AI?
What can AI control?Why? How?How much benefit to people will AI bring?
What are the pros and cons for its use?
Is it a friend or foe? For welfare or warfare?
...
These are some important questions that need to be answered with honesty by all those who are involved and affected by AI .
At the end of the day if AI is going to enslave people or forces things on them ,then no matter what the benefit, it is shooting ourselves in the foot.In other words, if we are using our intelligence to create something we are not able to control, then this is a warped intelligence and will lead to our demise/Tahlukat.
GOD bless.
Peace
