Can You Build an Alternative to LLMs? 8 Months, ~200 Failed Experiments, One Wall. 2

Short summary

After 8 months and ~200 experiments building a CPU-only knowledge system, the author identified critical failures in different architectures but learned systems perform better by abstaining on unsupported cases. The core insight: knowledge requires full causal transitions (condition → action → consequence), not just preserved signals. This honest failure analysis reveals the gap between memory (storing events) and weights (changing behavior).

• •8-month research attempted to build a non-neural, experience-accumulating system as an LLM alternative
• •All tested carriers (memory, graphs, state, vectors) preserved individual aspects but failed at complete causal transitions
• •Key breakthrough: systems improve by abstaining on unsupported cases rather than forcing pattern matches

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