Show HN: Era – A deterministic, non-neural AI that runs on CPU (github.com)

Era, a newly unveiled AI architecture, offers a deterministic approach to cognitive processing, setting itself apart from traditional neural networks and large language models (LLMs). By utilizing eight mathematical engines based on principles from physics, chaos theory, and graph mathematics, Era achieves a 0% hallucination rate while providing verified and contextually relevant responses. Unlike LLMs, which often produce output with some degree of inaccuracy or rely heavily on probabilistic learning, Era's cyclic system allows its engines to continuously interact and refine information, improving accuracy and efficiency. For instance, while a typical LLM may take over 2 seconds to respond, Era does so in approximately 400 milliseconds, all while running offline and maintaining full explainability. This development is significant for the AI and machine learning community as it challenges conventional methodologies and highlights the potential for deterministic cognitive architectures. Each engine in Era serves unique functions, such as a Mood Attractor that incorporates chaos theory to affect AI responsiveness, and a Physics Verifier that treats information sources with varying levels of credibility. As a result, Era could enhance applications in fields like fact-checking, explainable AI, and personalized interactions by providing accurate, human-like responses grounded in verifiable data. The architecture's modularity and focus on real-time knowledge retrieval present a promising shift toward more reliable and transparent AI systems.