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Refers to artificial intelligence systems that not only provide accurate predictions or decisions but also offer explanations for how and why they reached those conclusions in a human-like, understandable manner. XAI aims to increase transparency and trust in AI systems by enabling users to comprehend the reasoning behind AI-driven outcomes. Sounds familiar?

AI models that are capable of understanding and generating human-like text. These models have been trained on vast amounts of previously inputted text data and can perform a variety of tasks such as answering questions and generating creative content (like ChatGPT). However… LLMs can inadvertently learn and perpetuate biases present in the data they were trained on, leading to biased or unfair outputs, and often lack transparency and accountability.

AI that evolves and learns with each input, rather than being a pre-trained language model. This type of AI typically employs principles inspired by biological evolution and human behaviour. Over time, as the AI gathers more data and refines its understanding of how the user speaks and behaves, it becomes increasingly accurate in its predictions and responses.