Deux IA d'accord = une source : la règle qui m'a évité un pipeline bâti sur du vide
The article discusses the author's experience with using two AI models for peer review. Both models provided similar feedback and ratings, leading the author to question the reliability of their convergence. The author emphasizes the importance of understanding the limitations of AI models and their training data.
- ▪The author submitted their work to two AI models for review and received identical ratings.
- ▪Both AI models provided similar critiques, raising concerns about their reliability.
- ▪The author highlights that the convergence of AI feedback may reflect shared training data rather than objective truth.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3897818) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Michel Faure Posted on May 24 • Originally published at dev.to Deux IA d'accord = une source : la règle qui m'a évité un pipeline bâti sur du vide #claudecode #ai #webdev #productivity My ERP with Claude Code (33 Part Series) 1 How much are 91,000 lines produced with Claude Code actually worth? 2 Supabase RLS in production: four traps that silence your queries ... 29 more parts...
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