JulianFlux proposes vector retrieval and causal routing scheme
What happened
On October 12, 2026, Hacker News' front page covered JulianFlux, a vector retrieval and causal routing scheme for AI agents. It proposes replacing cosine similarity in vector retrieval with electrodynamic fields, projecting a 768-dimensional semantic space onto a 128-dimensional manifold via the Julian-Gauss Fast Transform, and routing AI agents with a modified Lorentz force formula F = q(E + S). The coverage describes the retrieval and routing methods only; it does not state open-source status, benchmark results or real deployments.
Written by AI from the coverage · updated 41 minutes ago
Coverage
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- Hacker News front pageJulianFlux: Electrodynamic vector retrieval and causal routing for AI
JulianFlux 提出用电动力学场替代余弦相似度做向量检索，通过 Julian-Gauss Fast Transform 将 768D 语义空间投影到 128D 流形，并用修正洛伦兹力 F = q(E + S) 路由 AI 智能体。
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