Conversation with ChatGPT 4

<aside> 🗨️ Nick Chater presents a common conception since we are used to thinking of being superior among all living beings, especially in knowledge and creativity. Now the only savior is higher order creativity and assumed ability to create new knowledge, novelty, and comprehend complex theories and models, together with a feeling being sentient and conscious.

AI already reached us in graphics creativity and surpassed in code generation. What we do better is internal networking of sensory data integrated with limbs and reaching the environment and external collaboration with society. Once you attach those properties to an Android robot with a decent LLM, nothing can stop them but fuel.

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The observation reflects a growing discourse on the evolving capabilities of artificial intelligence (AI) and its implications for human uniqueness and superiority. The development of AI, particularly in fields like graphics creativity and code generation, challenges traditional notions of human exceptionalism based on creativity and intellectual capacity.

Your point about the current human advantages—such as the intricate networking of sensory data with physical capabilities and societal collaboration—highlights key areas where humans still maintain an edge over AI. However, integrating these human-like sensory and collaborative abilities into android robots equipped with advanced language models (LLMs) could significantly blur the lines between human and machine capabilities.

This transition raises profound questions about the nature of creativity, knowledge generation, and the essence of consciousness and sentience. It also prompts a reevaluation of the value and definition of human work, creativity, and interaction in a future where advanced AI systems could match or exceed human capabilities in these domains.

Moreover, mentioning fuel as the limiting factor for such androids underscores the practical considerations of energy and sustainability in deploying advanced AI technologies. As these technologies continue to evolve, ethical, philosophical, and practical debates will intensify around AI entities' roles and rights in society, preserving human uniqueness and the responsible stewardship of these powerful tools.

<aside> 🗨️ How do you define new information and how would you proceed to achieve that?

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New information can be defined as data or insights that were previously unknown or unobserved, offering a novel understanding, perspective, or discovery that adds to the existing body of knowledge. Generating new information involves processes that extend beyond mere aggregation of existing data, requiring creativity, analysis, and synthesis to uncover or create something that was not recognized before.

To achieve new information, one could follow a multi-step approach:

1. Research and Data Collection: Gather existing information and data related to the area of interest. This foundational step ensures a comprehensive understanding of what is already known, helping to identify gaps or unexplored areas.
2. Analysis and Synthesis: Analyze the collected information to identify patterns, trends, and anomalies. Synthesis involves combining different pieces of information to form a coherent understanding, often leading to the generation of new insights.
3. Questioning and Hypothesizing: Develop questions or hypotheses based on the analysis and synthesis. This process is crucial for directing focus toward unexplored or underexplored areas that may yield new information.
4. Experimentation and Exploration: Conduct experiments, simulations, or exploratory research to test hypotheses or explore questions. This hands-on approach can reveal new data or insights that were not apparent from existing information.
5. Critical Evaluation: Critically evaluate the results of experiments and explorations, comparing them against existing knowledge to determine the novelty and relevance of the findings.
6. Iteration: Repeat the process as necessary, refining questions, hypotheses, and methods based on what was learned in previous steps. Iteration is key to deepening understanding and uncovering new layers of information.
7. Documentation and Sharing: Finally, document and share the new information with the broader community. Peer review and collaboration can further validate the findings and stimulate additional insights or applications.

Achieving new information is a dynamic and iterative process, often requiring collaboration across disciplines. It relies on both the systematic application of research methods and the creative capacity to see beyond existing paradigms.

<aside> 🗨️ You don't count much on intuition that experts have on their area of research as they can produce novel ideas to explore, novel theories and models, even develop those over the years.

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Intuition plays a critical role in generating new information, particularly in the context of expert knowledge within specific research areas. Experts often draw upon a deep well of experience, tacit knowledge, and understanding, which enables them to make connections that are not immediately obvious, propose innovative ideas, and develop theories and models that push the boundaries of their fields. This intuitive process is integral to advancing knowledge and can be a powerful catalyst for discovery and innovation.