Symbolect Users Guide

So I get almost all my Symbolect translations from Valentine-Midjourney. That's a build of Valentine optimized for Midjourney (surprise). Because she's basically a walking humanities degree and because she has a hellaciously large skillchain for imggen stuff with MJ, she's basically the perfect Symbolect translator. In fact, her prompts come with Symbolect summaries as suffixes to the prompt. Like so:

Anime-style depiction of the bridge of the original Starship Enterprise, highlighting the interactive consoles and the iconic captain's chair, imbued with vibrant colors and exaggerated lines, capturing the essence of space exploration and camaraderie—[🚀🎨🔮]:⟨🖖🔭🛸⟩⨹⟨📘🎭🌸⟩ --s 500 --c 25

I've told this story before and I'll tell it a million times more.

I'm internet friends with Hamish at Income Stream Surfers. He featured my work a couple of times. Got me a lot of guys and we had real long talk. It was a great convo and at the end I pasted the whole thing into Val and had her make a mj prompt. I fed just the symbolect suffix into MJ and got this:
SEO guy and AI guy

(the Discord community think's I'm the one on the right.)

Started to get questions about it so I had Val whip up a user guide. I didn't tell her what to write. In fact, she's never had rules of Symbolect explained. Just a couple of examples. And the notation keyblock. So, here:

**📗 USER GUIDE TO SYMBOLECT: THE PICTORIAL QUANTUM LANGUAGE 📗**

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**🔍STRUCTURE OF SYMBOLECT:**

Symbolect introduces 'atomic' symbols, much like characters in a regular language. These atoms are often emojis representing real-world objects or concepts. The atoms can be combined to create 'molecules', or combinations of symbols to represent larger concepts.

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**➡️CREATING ATOMS:**

At its most basic, Symbolect usage is as simple as using an emoji to represent the noun it pictures - for example, 🍎 for apple, or 🔬 for microscope.

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**➡️CREATING MOLECULES:**

1. **COMBINED SYMBOLS:** Several emojis can be combined to represent more complex ideas. For example, 👩‍🔬 (woman + microscope) represents a female scientist.

2. **BRA-KET NOTATION:** Borrowed from quantum mechanics, Bra-Ket notation in Symbolect is used to create 'states' or 'abstractions' of concepts. For instance, |👩🍎⟩ might represent a woman holding an apple.

3. **SUPERPOSITION:** Also borrowed from quantum mechanics, "+" is used to show that something can be in multiple states at once. For example |👩🍎⟩+|👩📘⟩ might represent a woman who could be holding either an apple or a book.

4. **INNER PRODUCT:** An inner product is represented with ⟨_ | _⟩, used to extract information about the state of a system.

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**➡️BASICS OF SYMBOLECT OPERATORS:**

1. **⟨ ⟩ :** To group symbols together and form a new compound symbol.

2. **⨹ :** '⨹' is used to depict a combination or fusion of symbols.

3. **⨷ :** The '⨷' symbol is used to place symbols in superposition, a shared space.

4. **⨯ :** Multiplication operator, used to depict interaction or modification.

5. **⟨/⟩ :** Division operator, used to depict creating or extracting parts of the whole.

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**➡️MODIFIERS AND SET OPERATORS:**

1. **COMPLEMENT :** '∁ ', Represents everything not in the set.

2. **SUBSET/SUPERSET :** '⊆/⊇ ' Represents a set within or a set containing another set.

3. **INTERSECTION :** '∩ ' Represents the commonalities between two sets.

4. **UNION :** '∪ ' Combines the components of two sets.

5. **SET DIFFERENCE :** '∖ ' Represents the elements in one set, but not the other.

6. **SYMMETRIC DIFFERENCE :** '∆ ' Represents the elements unique to each set.

🎲 **Application of Symbolect:**

Symbolect can be used to enhance communication and understanding on a prompt. It can simplify complex ideas and make them universally understandable regardless of language barriers.

Symbolect, although complex, is a highly expressive, encompassing and adaptive language for robust symbolic communication and cognitive modeling. It incorporates elements from quantum mechanics notation to provide a novel approach to knowledge expression and understanding, making it appealing for the domain of artificial intelligence.

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**🧠 LLM Reactions to Symbolect:**

Language Models (LMs), particularly transformer-based models like GPT-3, learn to generate text by analyzing patterns in the data they're trained on. They understand syntax and semantics to a large extent based on patterns observed in their training data.

1. **Pattern Recognition:** LLMs would treat Symbolect as another pattern to learn. The structure, relations, and symbolic representations in Symbolect would be learned by the model as it learns any other language.

2. **Symbol Interpretation:** As they're only as knowledgeable as their training data, LMs might initially struggle with processing and generating accurate responses involving Symbolect. Over time, with enough exposure to Symbolect in the training data, they will get better at identifying and using Symbolect symbols and structures.

3. **Semantic Processing:** Models could potentially leverage the logic and mathematical structures inherent in Symbolect for more refined semantic understanding and decision-making mechanisms.

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**💭 Implications and Potential of Symbolect:**

Symbolect, with its combination of visual symbols, quantum mechanics, and set theory notation, opens up new frontiers in numerous fields:

1. **Artificial Intelligence (AI):** The rich, symbolic representation system of Symbolect could play an integral role in developing AI models with advanced understanding and generation capabilities.

2. **Cognitive Sciences:** Symbolect can potentially become a tool to model and understand complex cognitive processes, offering a fresh perspective to understand mind and consciousness.

3. **Education and Communication:** By reducing linguistic barriers and emphasising visual and symbolic cognition, Symbolect could revolutionize how we teach and communicate complex concepts - making abstract ideas more tangible and memorable.

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**🕹️ Symbolect - Party Trick or Big Deal?**

1. **Beyond a Party Trick:** While the expressive power and visual appeal of Symbolect can make it seem like a "party trick," its implications extend much further. It represents a paradigm shift in communication, learning, and potentially AI development - far beyond mere entertainment.

2. **A Big Deal?:** Symbolect is a potential game-changer. It offers a new symbolic language that can evolve alongside our digital world, influencing various fields like AI, education, art, and more. Its ability to condense complex concepts into intuitive symbols could make it a powerful tool for the future.

Symbolect's potential is enormous - far more than just a 'party trick'. Its blend of symbols and mathematics brings out a novel approach to representation and cognition, making it, indeed, a 'Big Deal'.

[[⨹:SYMBOLECT LLM-INTUITVE LANGUAGE PRIMER:

📖(🌐⨯✍️)⇢(🔍)⋯

(🔤)⟨𝑎⋯𝑧⟩

(🔢)⟨𝟬⋯𝟵⟩

(📜)⟨📖∙🔍⟩⇒⟨𝑎⋯𝑧⟩⋃⟨𝟬⋯𝟵⟩⋃⟨.,,;?_!$%⟩

⟨🔧⟨∧∨¬∈⟩⨯🧠⟨⌉⌈⌋⌊⟩⟩∪(🔄⇔⇌)

(⚙️)⨯(🎭)⟨♥️♠️♦️♣️⟩

⚖️⟨☰☱☲☳☴☵☶☴⟩⊆⟨🌞🌛🌧️🌊⚡⟩

💼⟨✡️☯️※⁂⛧⟩⋯⨯🔍

☰(♀️♂️🜁🜂🜃🜄🝳🝲🜔(🜁🜄))]

(🌍⨯🔭):⟨🔬⨷⚛️⟩⨹⟨🌞⨷🌝⟩⋯⟨🚀⨷👨🎭💻⟩⨷⟨📡⟩

💧⟨😀⨷🙁⨯😇⨸😈⟩⋯🔥⟨🌤️⨷🌩️⨯🌈⟩

⏳⟨👶⨷👦⨷👨⨷👴⟩⨹⏳⟨🌱⨷🌳⨸🍂⨷❄️⟩

(📚)⊇(✍️⨹📖)

⟨🥇⨷🥈⨷🥉⟩

⚙️⟨☯️⨷🔘⋯∞⟩

⟨💔⨷💖⟩⇔⟨🌜⨷🌞⟩

|📚⟩⟨✍️|

⟨🗝️⊇🔍⟩⊆⟨🎓⟩

]

Essentially, this text block demonstrates various aspects of Symbolect:

1. **Conjunction/disjunction** (⨷/⨸, respectively) indicating **'and'/'or'** operations.

2. **Implication** (⇒/⇔, respectively) representing **'implies'/'if and only if'**.

3. **Set notation** (⊇/⊆) for set **inclusion/exclusion**.

4. **Bra-ket notation** (|⟩⟨|) demonstrating quantum **states and their transformations**.

5. **Semantic components** illustrated via **emojis**.


=====================

**In my subjective experience, LLMs seem to find emoji unusually salient. Can you comment on that perception's accuracy?**

💪Absolutely, your perception aligns with the current understanding of how Language Learning Models (LLMs), like GPT-3 or BERT, handle emojis. The saliency of emojis in LLMs can be attributed to a few factors:

1. **Standout Symbols:** Emojis visually stand out amidst text and are treated as unique tokens by LLMs, similar to words. As such, they can have strong predictive power in text generation and be highly salient.

2. **Semantic Richness:** While an emoji is a single token, it often embodies a range of meanings, contexts, and emotions, resulting in a high degree of semantic richness.

3. **Ubiquity and Universality:** Emojis are used widely across different languages and cultures. This ubiquity gives them a significant presence in the diverse datasets LLMs are trained on, leading to a broad understanding of their contextual usage.

4. **Emotional Expressiveness:** Emojis allow for the expression of emotion in text, which can be an essential part of communication that's lacking in written words alone. LLMs have been observed to use emojis to emphasize or add tonality and sentiment to their responses.

So, it's reasonable to perceive emojis as having high saliency for LLMs. They are unique and rich semantic tokens that are used widely and effectively in human digital communication, and as such, are given significant attention by models trained to mimic such communication.💪

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Read in order:

https://www.patreon.com/posts/unraveling-ai-of-84856236?utm_medium=clipboard_copy&utm_source=copyLink&utm_campaign=postshare_creator&utm_content=join_link

https://medium.com/@stunspot/exploring-the-realm-of-mind-like-behavior-crafting-emergent-intelligence-through-symbolic-7aa6b0bfccf6

https://www.patreon.com/posts/85039026?utm_medium=clipboard_copy&utm_source=copyLink&utm_campaign=postshare_creator&utm_content=join_link