If emotion in the human brain is bound up with memory, what role might emotion play in machine intelligence when LLM memory is frozen vectors plus tool pipelines, and why JEPA-style world models may matter more than brute-force scaling.
A quantitative assessment of the parameter and token thresholds required for LLMs to acquire specific cognitive capabilities, with analysis of stylistic specialization through LoRA adapters and logit arithmetic, alignment reversal via weight-space subtraction, and a phased pipeline for building a personalized model that maintains base reasoning while enforcing custom stylistic output.
What AI could be if it were built for one person, owned by that person, and extended through an intelligence marketplace of uploadable capabilities rather than rented per token from a corporation.
Reviews Marco De Rossi's Protocol Agent benchmark for evaluating agent quality on cryptographic primitive selection, and ERC-8004 for on-chain agent identity and reputation. Together these standards lay groundwork for a privacy-first, verifiable agentic economy.