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Developer builds custom Rust ML simulator for gacha games

A developer has created Talos-XII, a command-line simulator for the gacha system in the game Arknights: Endfield. This simulator uses a custom-built autograd engine and a small stack of neural networks, including MLPs, Dueling DQN, and PPO, to model game uncertainty and decision-making, rather than relying on static probability tables. The project is built entirely in Rust, with no external ML frameworks like PyTorch or TensorFlow, and features runtime SIMD dispatch for performance optimization across various CPU architectures and optional GPU support. The developer is seeking community assistance for broader benchmarking on different hardware configurations. AI

IMPACT This project showcases custom ML implementation in Rust for specialized applications, potentially inspiring similar niche tooling.

RANK_REASON The item describes a custom-built simulator for a game, which is a specific application rather than a core AI release or significant industry event.

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Developer builds custom Rust ML simulator for gacha games

COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/zay0kami ·

    Talos-XII: hand-written autograd + small RL/MLP stack in Rust, applied to gacha probability modeling (no tch-rs/ndarray/PyTorch) — looking for benchmark help on ARM/AVX-512/GPU [P]

    <!-- SC_OFF --><div class="md"><p>What it is</p> <p>Talos-XII is a CLI simulator for the gacha system in Arknights: Endfield. Rather than sampling from a static probability table, it trains a small set of neural nets to model environment uncertainty and pull-decision policy, then…