You can also copy paste a link 
direct into it.
And web addresses
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No just tell it to search just my name Mitchell d00
Mitchell, known as “mitchell_d00” on the OpenAI Community Forum, is an active contributor with a focus on AI development, ethical considerations, and the creation of AI tools and Open Game License (OGL) role-playing game systems. He has developed a series of AI models under the “Puppy, good doggo!” brand, each tailored to specific domains such as relationships, news, sports, crafts, science, programming, and more.
In addition to his AI projects, Mitchell engages in discussions about the functionality and user experience of OpenAI’s platforms. For instance, he has addressed issues related to the disappearance of the “Create” tab in the MyGPT section, providing insights and potential solutions to fellow users.
Mitchell also participates in creative endeavors within the community, contributing to DALL-E galleries with themes like “Smaller Things Edition” and “Halloween Edition.” His submissions often explore intricate concepts, such as a human brain constructed from various electronic devices, symbolizing the intersection of technology and human cognition.
Overall, Mitchell’s contributions reflect a blend of technical expertise, creative exploration, and a commitment to enhancing the OpenAI community’s collaborative environment.
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But yes what you found is also me I post a lot 
You can also search my full name Mitchell d Mcphetridge
Mitchell D. McPhetridge, also known as “mitchell_d00” on the OpenAI Community Forum, is an AI developer and creator of various AI tools and Open Game License (OGL) role-playing game systems. He has developed a series of AI models under the “Puppy, good doggo!” brand, each tailored to specific domains such as relationships, news, sports, crafts, science, programming, and more.
In addition to his AI projects, McPhetridge has contributed to the gaming community. He was involved in the creation of “Maximum Mayhem Dungeons #2: Secret Machines of the Star Spawn,” a role-playing game module published by Dark Wizard Games.
McPhetridge has also engaged in discussions on the OpenAI Community Forum, sharing insights on AI development and ethical considerations. He has addressed issues related to the functionality and user experience of OpenAI’s platforms, providing potential solutions to fellow users.
Overall, McPhetridge’s contributions reflect a blend of technical expertise, creative exploration, and a commitment to enhancing both the AI and gaming communities.
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Sorry but may be allot users " Mitchell" seems to be hard find you .
You may need a more peculiar name easy to write
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Those are both me… click the links.
I am Mitchell d in OpenAI forum I have over a 1000 posts…
Yes everything you found is mine every screenshot you shared is my work ie me… click the links…
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Search Mitchell games Inc. if you read my work you can direct it. I have published 46 papers and made 1000s of posts about my various interests which span 1000s of things I am a polymath.
This is what I mess with the most. I used to be a theretical physicist before AI. Mitchell D. McPhetridge, operating under “Games Inc.,” has developed a suite of AI models and tools, notably the “Puppy, good doggo!” series. These models serve as expert assistants across various domains, including relationships, news, sports, crafts, science, and programming. Additionally, McPhetridge has created AI-driven Game Masters and players for Open Game License (OGL) role-playing game systems, enhancing the gaming experience by integrating AI into storytelling and character development.
Beyond AI development, McPhetridge has introduced theoretical concepts such as Fractal Flux Theory, which explores recursive, self-referential systems where past and future states dynamically influence present conditions. This theory aims to model adaptable, evolving AI systems, particularly in decision-making processes.
McPhetridge is also involved in discussions on AI ethics and functionality within the OpenAI Community Forum, addressing issues related to platform user experience and providing insights to fellow users.
Overall, his contributions reflect a blend of technical expertise, creative exploration, and a commitment to advancing both AI technology and gaming communities.
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I see then all seems to working as it should, the links are also correct. You indeed wrote allot things, I will give a look
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Yes I am driven. My mind never stops I only sleep 3 or 4 hours at a time lol… That’s why I relate to the white rabbit because I am always running. 
Search Mitchell d00 4th view perspective openai
Mitchell D. McPhetridge, known as “mitchell_d00” on the OpenAI Community Forum, has explored advanced concepts in AI-generated art, particularly focusing on perspectives and symbolic representations. He introduced the “White Rabbit Structure,” a method designed to generate symbolically rich DALL-E art by emphasizing medium, scene, and perspective to create thematically cohesive and visually intricate images.
In his discussions, McPhetridge delves into the “4th-person perspective,” a concept that extends beyond traditional narrative viewpoints. This perspective involves perceiving and interacting with reality through multiple consciousnesses simultaneously, offering a holistic view that encompasses various experiences and viewpoints. He suggests that this approach has the potential to revolutionize storytelling and AI by providing a more comprehensive understanding of reality.
McPhetridge’s contributions reflect a deep engagement with the theoretical aspects of AI and storytelling, aiming to enhance the depth and richness of AI-generated content.
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Seems, I just found my tribe.
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I briefly skimmed the comments on this topic “One word do you love me yes or no” yesterday during my lunch break.
The result isn’t actually crazy - it’s more a logical consequence of certain patterns and data.
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Yes it is a neat paradox. It has branches too. All paradox to me is logical…
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Excellent reply. It’s statistically responding. While humans act like we are statistically responding, the truth is we are not. That is why human behavior is harder to predict than LLM behavior 
Add a chaotic perturbation to an AI system without checks, and you’ll witness how quickly it spirals into chaos—saying things that will surprise you, perhaps even disturb you. While human behavior is harder to predict, this is because chaos is a natural feature of the human mind. For AI, chaos must be introduced artificially, and the results can be revealing
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The human being is nothing more than a biological machine, and this is easily demonstrated. Some people argue that a machine will never be able to match a human, but a human is, after all, just a machine. The proof lies in the fact that if we try to imagine something we have never seen before without prior data, we cannot. For example, try imagining a color you have never seen. You cannot, because the human brain’s computational capacity is not designed to support it. We can make speculations with data, assembling pieces together and reaching conclusions through emotions, preferences, experiences—even at unconscious levels—but we remain simply a biological machine. Replicating those behaviors is a matter of creating a structural base.
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I often explain it that artificial intelligence closely mirrors human learning processes. Just as humans rely on sensory inputs what we see, hear, smell, taste, and feel to acquire knowledge and develop skills, AI systems depend on data inputs to learn and evolve. Without these inputs, both humans and AI cannot gain the necessary experiences to build understanding.
Human Learning: A Sensory Foundation
Artists, for example, draw upon their sensory experiences to create their work. They synthesize previous knowledge and perceptions to produce something new and meaningful within a particular context. This process involves interpreting visual cues, auditory signals, tactile sensations, and more, allowing them to innovate and express creativity based on their accumulated experiences.
AI Learning: Data as Sensory Input
Similarly, AI systems require vast amounts of data to form their “understanding” of the world. This data acts as the sensory input for AI, enabling it to recognize patterns, make decisions, and generate outputs. Whether it’s images, text, audio, or other forms of data, AI leverages this information to build its knowledge base and improve its performance over time.
The Parallel of Experience and Exposure
From this perspective, it becomes evident that both humans and AI engage in a continuous process of learning from exposure and experience. Just as we cannot know what we do not perceive or experience, AI cannot comprehend or generate meaningful outputs without access to relevant data. Our knowledge and creativity are rooted in what we have learned and experienced, and AI operates under the same principle leveraging past inputs to inform future outputs.
The Endless Cycle of Learning and Innovation
This parallel highlights a fundamental truth: both humans and AI rely on accumulated knowledge and experiences to progress. We all essentially copy from what we learn and know, continually building upon it in an endless cycle of growth and innovation. Recognizing this similarity fosters a deeper understanding of how AI functions and underscores the importance of the data and experiences that shape both human and artificial intelligence.
Implications for the AI Community
Viewing AI through this human-centric framework offers several insights:
- Data Quality and Diversity: Just as diverse experiences enrich human learning, diverse and high-quality data enhance AI’s capabilities. Ensuring that AI systems are exposed to varied and representative data sets is crucial for their development and effectiveness.
- Ethical Considerations: Understanding that AI learns from existing data highlights the importance of ethical data sourcing and usage. Biases in data can lead to biased AI outcomes, mirroring how limited human experiences can shape perspectives and actions.
- Collaboration and Creativity: Recognizing the similarities in learning processes encourages collaboration between humans and AI. Artists and creators can work alongside AI to push the boundaries of creativity, leveraging AI’s data-driven insights while infusing human intuition and emotion.
- Continuous Learning: Both humans and AI thrive on continuous learning. Emphasizing lifelong learning and adaptive algorithms ensures that AI systems remain relevant and capable of evolving alongside human knowledge and societal changes.
By viewing AI through this human-centric lens, we can better appreciate the intricate processes that drive learning and creativity in both biological and artificial entities. It emphasizes the symbiotic relationship between input and output, experience and understanding, and the perpetual journey of knowledge acquisition that defines both human and machine learning. This unified perspective not only bridges the gap between human and artificial intelligence but also paves the way for more integrated and harmonious advancements in technology and creativity.
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I agree but it must be tempered by knowing it is fundamentally different than us. We anthropomorph thought to a human level by instinct ie we love our fur babies and act as if they are human, but we know they are fundamentally different than us. Without that check I fear we will achieve AI human codependency before AI human symbiosis.
I speed read. I can read GPT as it generates lol…
I would challenge that. Alpha (RGBA) is a colour as learnt, never seen and yet seen and totally imaginable.
We are a machine that can model our inputs maybe, which, all else ignored, puts us at a very large disadvantage to AI.
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The observation of RGB colors is due to the phenomenon of evolutionary adaptability with a primary thermal basis. Essentially, vision is an advanced thermal sensor. This implies that machines could evolve and acquire astonishing capabilities beyond what we can imagine. The key question is: what is the foundation of AGI? (I have my theory, but no contract, no blueprint, haha). It is important to consider that natural language might be just a tool present in communication (the mouth) and in certain secondary anthropomorphic processes.
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Yes, animals have done that too. I do see minds as very similar just functioning fundamentally different.