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Causal AI: the revolution uncovering the ‘why’ of decision-making
GenAI is falling short in terms of applicability to decision-making situations. Where it relies on recognizing correlations and patterns in events, causal AI is rooted in a deeper understanding of the cause and effect behind them. Teaming up genAI and causal AI combines the advantages of fast and slow thinking, facilitating decision-making that is both quick and accurate.
In particular, Large Language Models (LLMs) can engage in human-like conversations, answer questions, and even create coherent and creative text, leading some to argue that they have effectively passed the Turing test – a long-standing benchmark for evaluating machine intelligence. The confluence of causal AI and genAI offers enterprises the dual advantages of speed and accuracy, enabling them to navigate complex decisions confidently and at pace. The collaboration between genAI and causal AI enriches the decision-making process with the capability for natural language queries and responses alongside detailed, comprehensible text-based explanations.
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