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Thats why explainability is such a key issue. People want to know how AI systems work, why they make certain decisions, and what data they use. The more we can explainAI, the easier it is to trust and use it. Large Language Models (LLMs) are changing how we interact with AI. Lets dive into how theyre doing this.
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. BlackboxAI lack transparency, leading to risks like logic bias , discrimination and inaccurate results.
It excels in performing logic-based problems, processing multiple steps of information, and offering solutions that are typically difficult for traditional models to manage. This success, however, has come at a cost, one that could have serious implications for the future of AI development.
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