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AI isn’t ready to replace human coders for debugging, researchers say

  • Microsoft Research found that AI models often fail at debugging tasks on SWE-bench Lite.
  • Researchers attribute the AI models' suboptimal debugging to a lack of decision-making data.
  • The study tested models from top AI labs, including OpenAI and Anthropic, on debugging.
  • Claude 3.7 Sonnet achieved a 48.4% success rate, while OpenAI's o1 reached only 30.2%.
  • The study suggests that fine-tuning can improve AI's interactive debugging, but human expertise remains crucial.
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TechCrunch broke the news in United States on Thursday, April 10, 2025.
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