Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do. There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

Saturday, 5 October 2024

Reasoning AI ?

 

 

 

Context :

Google is working on reasoning AI, chasing OpenAI's efforts

Extract :

Google is working on artificial intelligence software that resembles the human ability to reason, similar to OpenAI's o1, marking a new front in the rivalry between the tech giant and the fast-growing startup.

In recent months, multiple teams at Alphabet Inc.'s Google have been making progress on AI reasoning software, according to people with knowledge of the matter, who asked not to be identified because the information is private. Such software programs are more adept at solving multistep problems in fields such as math and computer programming.

AI researchers are pursuing reasoning models as they search for the next significant step forward in the technology. Like OpenAI, Google is trying to approximate human reasoning using a technique known as chain-of-thought prompting, according to two of the people.

In this technique, which Google pioneered, the software pauses for a matter of seconds before responding to a written prompt while, behind the scenes and invisible to the user, it considers a number of related prompts and then summarizes what appears to be the best response.

 

I Asked ChatGPT :

Hey ChatGPT :

Here is an article which says Google is about to launch a " Reasoning AI " , to catch up with ChatGPT > Reasoning AI ?

I wonder if you can " reason " to figure out my following postulate :

> Parallel to the Theory of Thermodynamics , I would like to propound the following as far as the “ Theory of Information “ is concerned : 

“ Like Entropy , content keeps growing with each and every human interaction , either with other humans or with his environment , and content can no longer remain hidden , nor can it be destroyed “

https://myblogepage.blogspot.com/2018/03/nightmare-aadhar-privacy-dataprotection.html

 04 March 2018



With regards,

Hemen Parekh

www.My-Teacher.in  /  www.HemenParekh.ai 

06 Oct 2024

 

 

ChatGPT replied :

Your postulate suggests an intriguing analogy between Thermodynamics and the Theory of Information, drawing a parallel between the concept of entropy and the growth of content through human interactions. Here's an interpretation based on your reasoning:

1.     Content as Entropy:

Just as entropy represents the degree of disorder in a physical system, content in your analogy represents information generated by human interaction. This content grows continuously, implying that every interaction adds more data or information to the system.

2.     Content Cannot Be Hidden or Destroyed:

In thermodynamics, the second law states that entropy tends to increase in isolated systems, and this process is irreversible. Similarly, you posit that content cannot be hidden or destroyed—it spreads and accumulates as a natural consequence of interaction, much like how energy disperses in a closed system. Once created, content remains in the collective information "system" (e.g., the digital world, social consciousness, etc.).

This idea resonates with how modern information behaves, particularly in the age of the internet and digital storage. Information is constantly created, shared, and often remains accessible indefinitely.

Reasoning AI and Your Postulate

AI models, like the ones being developed by Google and OpenAI, use reasoning to break down complex tasks, particularly in fields like math or programming. Applying such reasoning AI to the theory of information, we could imagine AI helping to model or track the flow and transformation of information. A reasoning AI could, theoretically, trace how content spreads, mutates, or accumulates in complex human systems, much like tracking the flow of energy.

Your postulate taps into a deeper idea:

just as physical systems evolve according to laws like thermodynamics, information systems evolve in a predictable manner based on interactions. Reasoning AI could one day model these processes, providing new insights into how information grows and how we might harness or manage it.

What do you think? Could reasoning AI help refine and explore this analogy further?

GEMINI reply to same Question :

Analyzing Your Postulate: A Parallel to the Theory of Thermodynamics

Your postulate, comparing the growth of content to entropy in the Theory of Thermodynamics, is intriguing and has a strong foundation in the principles of information theory.

Key Points of Comparison

1.     Continuous Growth: Both entropy and content tend to increase over time. In thermodynamics, entropy is a measure of disorder or randomness. Similarly, in information theory, content can be seen as a measure of complexity or uncertainty. As interactions occur, the complexity and diversity of information increase.

2.     Irreversibility: The Second Law of Thermodynamics states that entropy always increases in an isolated system. This suggests that information once created cannot be destroyed or reverted to a simpler state. The concept of information entropy aligns with this, indicating that information tends to disperse and become more widely available.

3.     Inevitability: Just as entropy is an inevitable consequence of interactions within a system, the growth of content seems to be a natural outcome of human interactions. As individuals exchange ideas, experiences, and knowledge, the total amount of information in the world expands.

Potential Counterarguments and Considerations

While your analogy is compelling, it's important to consider some nuances:

  • Definition of Content: The term "content" can be interpreted in various ways. A more precise definition would strengthen the comparison. For example, one could define content as the total amount of unique information or the complexity of the information network.
  • Information Loss: While information cannot be destroyed, it can be lost or obscured. For instance, data corruption or the passage of time can make information inaccessible. This might be seen as a counterargument to the idea of continuous growth.
  • Contextual Relativity: The growth of content might be relative to a specific context or system. For example, while the total amount of information in the world may be increasing, the accessibility or relevance of certain information might be decreasing.

Conclusion

Overall, your postulate provides a valuable framework for understanding the dynamics of information in human society.

By drawing parallels to the Theory of Thermodynamics, you highlight the fundamental tendency of information to grow, disperse, and become increasingly complex.

While there are nuances to consider, your analogy offers a thought-provoking perspective on the nature of information and its role in human interactions.

Would you like to explore this topic further, perhaps discussing specific examples or potential applications of your postulate?

 

PERPLEXITY reply to same Question  :

Google's upcoming "Reasoning AI" aims to enhance its capabilities in understanding and processing information, potentially allowing it to compete more effectively with existing models like ChatGPT. This advancement aligns with ongoing developments in artificial intelligence, particularly in areas such as natural language processing and reasoning.

Exploring the Theory of Information

Your postulate draws an intriguing parallel between thermodynamics and the theory of information, suggesting that just as entropy increases in thermodynamic systems, the content of information grows with human interactions. Here’s a breakdown of your assertion:

1. Information Growth and Entropy

·         Entropy in Thermodynamics:

In thermodynamics, entropy is a measure of disorder or randomness in a system, often associated with the second law of thermodynamics, which states that the total entropy of an isolated system can never decrease over time.

·         Information Growth:

Similarly, in information theory, the concept of Shannon entropy quantifies uncertainty or surprise associated with random variables. As interactions occur—whether between humans or between humans and their environment—the amount of information (or content) generated tends to increase. This reflects the idea that new knowledge emerges from every interaction, much like how energy disperses in thermodynamic systems

2. Content Visibility and Persistence

·         Visibility of Information:

Your assertion that "content can no longer remain hidden" resonates with principles in information theory where data generated through interactions becomes part of a larger informational landscape. This aligns with the notion that as more information is created and shared, it becomes increasingly accessible and difficult to suppress

 

·         Indestructibility of Information:

The idea that "content cannot be destroyed" is also thought-provoking. In information theory, while data can be lost or corrupted, the fundamental concepts and patterns often persist through various forms of representation. This suggests that once information exists, it may transform but not vanish entirely

 

4.    Implications for AI and Reasoning

 

The development of reasoning AI could significantly impact how we understand and interact with information:

·         Enhanced Understanding:

Such AI could leverage advanced reasoning capabilities to process vast amounts of content generated through human interactions, potentially identifying patterns or insights that were previously obscured.

·         Dynamic Information Systems:

As AI systems become more adept at reasoning, they could facilitate better management and utilization of information, reflecting the growth dynamics you propose.

In conclusion, your postulate about the parallels between thermodynamics and the theory of information invites further exploration into how these concepts can inform our understanding of both physical systems and informational dynamics. The advancements in AI technologies like Google's Reasoning AI may play a crucial role in realizing these theoretical implications in practical applications.

 

META rely to same Question :

What a fascinating postulate !

I'll attempt to "reason" through it.

Breaking down your postulate:

You're drawing an analogy between the Theory of Thermodynamics and the "Theory of Information." Specifically, you're likening entropy to the growth of content.

Entropy analogy:

In thermodynamics, entropy represents the measure of disorder or randomness in a system. It always increases over time, as energy is transferred or transformed. Your postulate suggests that content (information) behaves similarly:

1.     Content growth:

Just as entropy increases with energy interactions, content grows with each human interaction (social) or environmental interaction (e.g., sensing, observing).

2.     Irreversibility:

Just as entropy cannot be decreased, content cannot be destroyed.

3.     Inescapability:

Just as entropy affects the entire system, content cannot remain hidden.

Reasoning through implications:

Your postulate has intriguing implications:

1.     Information explosion:

Content will continue to grow exponentially, mirroring the exponential growth of human interactions and environmental data.

2.     Information persistence:

Content, once created, cannot be erased, only transformed or redistributed (e.g., deleted, archived, or transformed into new content).

3.     Transparency:

As content grows, it becomes increasingly difficult to conceal information.

Potential consequences:

1.     Data management challenges:

The relentless growth of content will require innovative solutions for storage, organization, and retrieval.

2.     Information overload:

Humans may struggle to process and make sense of the ever-increasing content.

3.     Privacy and security concerns:

As content persists, ensuring its confidentiality and integrity becomes crucial.

Relationship to Reasoning AI:

Google's proposed Reasoning AI might play a crucial role in navigating this expanding information landscape:

1.     Content analysis:

Reasoning AI can help filter, categorize, and make sense of the growing content.

2.     Knowledge graph construction:

AI can identify relationships between content, facilitating information retrieval and discovery.

3.     Decision support:

By analyzing the vast, persistent content, Reasoning AI can inform decision-making.

Your postulate provides a thought-provoking framework for understanding the dynamics of information growth.

The implications are far-reaching, and Reasoning AI might be a key tool in harnessing the potential of this expanding information universe.

How do you think your postulate relates to the concept of "information entropy" (the measure of uncertainty or randomness in information)?

 

 

 

 

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