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Tagged: reinforcement-learning

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9 min read

Unsloth vs Axolotl vs TRL vs LlamaFactory: Pick by Coupling, Not Throughput

These four are not four alternatives at one layer — TRL is the trainer API, Axolotl and LlamaFactory wrap it, and Unsloth rewrites its source at import time. That single fact predicts the thing you will actually feel: TRL shipped 1.9.2 in July while two of the others still pin the 0.x line. The famous speed table nobody can source is the wrong axis entirely.

11 min read

AI in the Trading Stack: What Hedge Funds Actually Run on the Decision

AI in trading is not one bot; it is a four-layer stack — signal, sizing, execution, risk — and each layer runs a different model with different failure modes. Map the layers and any "AI hedge fund" headline becomes legible in thirty seconds.

18 min read

FinRL vs TensorTrade vs ABIDES-Gym vs ElegantRL: Who Controls the Simulation Contract

Four RL-for-trading projects, four near-identical feature lists — Gymnasium env, OHLCV ingest, PPO/SAC/A2C/DQN, backtest evaluation. The thing that actually decides which survives a serious research-or-prod loop is invisible there: who controls the simulation contract.