Add LLM Proxy Babylon — inference-time optimization for low-resource …

[tverney]

Adds LLM Proxy Babylon to the Software section.

LLMs allocate ~93% of training tokens to English, leaving low-resource languages with degraded reasoning, higher token costs, and weaker safety alignment. This proxy bridges that gap at inference time by selectively pre-translating prompts to English before sending to the LLM.

Real benchmarks show quality scores jumping from 0.456 to 0.949 for Thai, with 70% fewer input tokens. Research by Deng et al. (2023) shows low-resource languages have 3x the likelihood of harmful content — the translate-to-English path routes prompts through the model's strongest safety guardrails.

This complements dataset creation and model training efforts by providing an immediate, deployable solution for any existing LLM.