TREE NEWS reports: Physicists at George Washington University say a formula can estimate when an AI chatbot will flip from good answers to bad ones. Early tests on small models back the approach, the researchers said. The work points to a way of forecasting chatbot degradation before it shows up in outputs.
Physicists Say Formula Predicts When AI Chatbots Turn Bad
The significance here is less about any single chatbot and more about whether AI reliability can be treated as a measurable property rather than something discovered after deployment. If a formula can flag degradation before it reaches outputs, that has obvious implications for any RWA or crypto operation leaning on AI for compliance, monitoring or customer-facing tools, where a silent quality drop carries real cost. The open question is whether the approach holds on the large, production-scale models that matter, since the reported tests were on small ones.
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