Einsia(@EinsiaAI):1/ Recursive self-improvement (RSI) depends on agents improving how AI systems are trained —not just tuning hyperparameters, but improving the training algorithm itself. We tested this directly with AI4AI-Bench: 10 real research repositories spanning 10 distinct algorithm families. Full breakdown 👇 GitHub: [https://t.co/s0f0NY7PdQ] Paper Link: [https://t.co/x0qY8wnlwB] Einsia Website:[https://t.co/Rewt4FJwl8] 📊 The results: The average score is just 0.166. Even the best-performing model, Opus 5, reaches only 0.288. The median exploration cost per task rises from $1.69 to $34.60. #AI4AI #RecursiveSelfImprovement #AIResearch #AI4AI

2026.08.21 17:33

1/ Recursive self-improvement (RSI) depends on agents improving how AI systems are trained —not just tuning hyperparameters, but improving the training algorithm itself. We tested this directly with AI4AI-Bench: 10 real research repositories spanning 10 distinct algorithm families. Full breakdown 👇 GitHub: [ Paper Link: [ Einsia Website:[ 📊 The results: The average score is just 0.166. Even the best-performing model, Opus 5, reaches only 0.288. The median exploration cost per task rises from $1.69 to $34.60. #AI4AI# #RecursiveSelfImprovement# #AIResearch# #AI4AI_Bench#

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