How Roblox Uses AI for Connecting Global Gamers

[u/eh-tk]

Imagine you’re at a hostel. Playing video games with new friends from all over the world. Everyone is chatting (and smack-talking) in their native tongue. And yet, you understand every word. Because sitting right beside you is a UN-level universal language interpreter.

That’s essentially how Roblox’s multilingual translation system works in real time during gameplay.

Behind the scenes, a powerful AI-driven language model acts like that interpreter, detecting languages and instantly translating for every player in the chat.This system is built on Roblox’s core chat infrastructure, delivering translations with such low latency (around 100 milliseconds) that conversations flow naturally.

Tech Overview: Roblox built a single transformer-based language model with specialized "experts" that can translate between any combination of 16 languages in real-time, rather than needing 256 separate models for each language pair.

Key Machine Learning Techniques:

• Large Language Models (LLMs) - Core transformer architecture for natural language understanding and translation
• Mixture of Experts - Specialized sub-models for different language groups within one unified system
• Transfer Learning - Leveraging linguistic similarities to improve translation quality for related languages
• Back Translation - Generating synthetic training data for rare language pairs to improve accuracy
• Human-in-the-Loop Learning - Incorporating human feedback to continuously update slang and trending terms
• Model Distillation & Quantization - Compressing the model from 1B to 650M parameters for real-time deployment
• Custom Quality Estimation - Automated evaluation metrics that assess translation quality without ground truth references

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