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LLMs as Explainable AITools One of the standout features of LLMs is their ability to use in-context learning (ICL). Researchers are using this ability to turn LLMs into explainable AItools. Theyre making AI explanations accessible to everyone, not just tech professionals. Take the model x-[plAIn] , for example.
Similarly, what if a drug diagnosis algorithm recommends the wrong medication for a patient and they suffer a negative side effect? At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “blackbox” logic, meaning no one can see how the algorithm makes decisions.
{This article was written without the assistance or use of AItools, providing authentic and insightful views on A.I.} By Tushar-Aggarwal.com (Author) Unforeseen Threats: A New AI Revolution However, here’s the concerning reality: AI doesn’t actually require consciousness or physical prowess to pose a threat to human civilization.
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