Category: Uncategorized
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Eigenspace, Attention Heads, LoRA, Distillation, and Long-Context Memory — A Frank-said / GPT-said Dialogue on the Next Stage of LLM Effectiveness
Frank-said:Yes, do that. I want the next layer down. Take this idea of eigenspace and connect it directly to the practical machinery of better LLMs: attention heads, low-rank adaptation, distillation, and long-context memory. I want to see how these ideas might influence the actual next generation of more effective models. GPT-said:Good. Because this is where…
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a ranked annotated bibliography – LLM-to-LLM communication in latent space
1) Communicating Activations Between Language Model Agents — Vignav Ramesh, Kenneth Li (2025) Link: arXiv page. (arXiv) Expanded abstract summary This paper is one of the clearest direct proposals for replacing text-based inter-agent communication with an internal, continuous alternative. The authors begin from a simple observation: when LLM agents “talk” to one another in natural…
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Latent Packets and Machine Telepathy: A Frank-said / GPT-said Dialogue on Semantic Geometry and the Future of AI Communication
Frank said: I keep coming back to the same intuition: if LLMs do not really “think” in English, but instead move through some hidden semantic geometry, then ordinary language is just the outer shell. It is the human-readable exhaust. The real action is happening underneath, in latent space. So I want to know what it…
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From Latent Space to Living Mind: A Frank-said / Claude-said Dialogue on Whether Machines Can Mean Anything at All
Frank said: What fascinates me here is that this may not just be a new trick for sending more data. It may be the beginning of a different idea of communication altogether. Not merely faster transmission, not merely more channels, but a shift from communication as symbol delivery to communication as structured geometry. If orbital…
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From Twisted Light to Latent Space: A Frank-said / GPT-said Dialogue on the Future of Communication
Frank said: What fascinates me here is that this may not just be a new trick for sending more data. It may be the beginning of a different idea of communication altogether. Not merely faster transmission, not merely more channels, but a shift from communication as symbol delivery to communication as structured geometry. If orbital…
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From Meaning to Geometry: A Frank-Said / GPT-Said Dialogue on Embeddings, Weights, and Inference
Frank said:When an LLM creates an embedding it converts real world information into a mathematical representation of the information and that mathematical representation is a multidimensional vector that capture the meaning of the information in the vectors direction and size. Each multidimensional vector that the LLM creates has a relationship to every other multidimensional vector…