Watch the demo: https://youtu.be/WVcprALYrBU I built a Mario demo where a local Laya model ranks candidate plans on CUDA, and my C++ library, JevT++, turns accepted plans into game inputs. The video shows the gameplay, decision flow, and knowledge graph behind it. The fun part was discovering that "the model returned a decision" and "the model actually controlled Mario" are two very different debugging milestones. I had to trace the winning controller all the way to the executed input. Model plans are checked for freshness and feasibility; local guards and fallback control handle the gaps. Inference and control are native C++, with a Python emulator bridge. This is a development-build integration demo on an RTX 4090, not a completed-game or performance benchmark. JevT++ itself is an MIT-licensed C++20 library for typed, model-backed decisions, with enum schemas, explicit abstention and optional Boost.Asio integration. Source: https://github.com/wiatrM/jevtpp Which moment in the demo best explains what the model is doing? If something is unclear, a timestamp would really help me improve the next cut. Disclosure: I'm the maintainer. The project, this post and video were made with Codex/AI assistance; the narration is synthetic.   submitted by   /u/mwiatruZ [link]   [comments]