Bellman-Ford Algorithm
Shortest Paths with Negative Edge Weights & Negative Cycle Detection
#Graph Theory#Dynamic Programming#Arbitrage#Financial Networks
Choose Presentation Mode:
STAGE 1 / 7— Anti-Pattern
Section 1: The LLM Anti-Pattern vs Right-Sized Model
The Naive Generative LLM Approach:
Prompting an LLM to scan a currency exchange FX table to detect triangular arbitrage opportunities.
Why It Fails in Production:
LLMs cannot perform precision floating-point arithmetic or multiply sequence probabilities without rounding errors and hallucinations.
Targeted Algorithm (Bellman-Ford Algorithm)
Latency:1.2ms
Cost / 1M Ops:$0.00
Determinism:100% Exact Arbitrage Proof
Generative LLM Alternative
Latency:3,800ms
Cost / 1M Ops:$15,000
Determinism:Math Hallucinations