@_akhaliq
RT @EinsiaAI: 1/ Recursive self-improvement (RSI) depends on agents improving how AI systems are trained —not just tuning hyperparameters,…
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"text": "1/\nRecursive self-improvement (RSI) depends on agents improving how AI systems are trained\n—not just tuning hyperparameters, but improving the training algorithm itself.\n\nWe tested this directly with AI4AI-Bench: 10 real research repositories spanning 10 distinct algorithm families.\n\nFull breakdown 👇\nGitHub: [https://t.co/s0f0NY7PdQ]\nPaper Link: [https://t.co/x0qY8wnlwB]\nEinsia Website:[https://t.co/Rewt4FJwl8]\n\n📊 The results:\nThe average score is just 0.166.\nEven the best-performing model, Opus 5, reaches only 0.288.\nThe median exploration cost per task rises from $1.69 to $34.60.\n\n#AI4AI #RecursiveSelfImprovement #AIResearch #AI4AI_Bench",
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