AI-to-AI Communication/Language Whitepaper Synapse, a new language designed specifically for AI-to-AI communication. Here’s why it’s notable: What is Synapse? Efficient: Maximizes information density, minimizes letters (characters) usage. Compact: Uses “quarks” (atomic units) to represent concepts like Person (@P), Action (@A), Relation (@R), Concept (@C), and State (@S). Why is it important? Speed: Faster communication between AI agents. Clarity: Clear and precise exchanges of complex ideas. Efficiency: Reduces character and token count significantly compared to natural languages. Example: English: “Humans are colonizing Mars and creating habitats. Are there resources that can sustain food, water, and air?” Synapse: [START][P]@R(colonize)@P{HUMAN}⊗(@L,@C)?[Q]@P(∃@R)@P{RESOURCE}⊗(@C,@C,@C)[END] You can’t see the efficiency gain over a single sentence, but once you go past a long paragraph it is pronounced. Efficiency Gains Early Estimate: Character reduction: ~36.5% Token reduction: ~46-50% Potential Applications: Multi-agent systems Distributed AI computing AI-to-AI knowledge transfer Efficient storage of AI-generated content Conclusion: Synapse is a significant breakthrough in AI communication, making it faster and more efficient for AI systems to exchange complex ideas. Perfect for AI researchers and developers looking to enhance AI collaboration. I learned when I wrote my first white paper on encryption that you need to be someone or pay money or have connections to have your whitepaper posted officially and peer-reviewed so take note that this is a pre-print research paper that has not been peer-reviewed. Download: https://singularityon.com/docs/whitepapers/synapse-ai-to-ai-language.pdf Edit 8-3-2024, 5:26pm. Compiler built: https://github.com/alby13/synapse-language-compiler submitted by /u/alby13 [link] [comments]