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Marriage of Generative AI and Classical Methods
Generative AI mechanisms are chaotic and non-deterministic, leading to potential errors when chaining inputs and outputs. Companies are beginning to combine generative AI with classical machine learning methods to classify outputs and constrain errors. This hybrid approach utilizes generative AI for generating ideas and classical methods for decision-making. The integration of various machine learning models in one system is emerging. The marriage between generative AI and classical methods is aimed at leveraging the strengths of each approach while mitigating error propagation issues. The trend in the industry is shifting towards improving data quality and governance to address the failures of generative AI prototypes due to poor data quality. Data security is a significant concern with generative AI, especially in instances where erroneous policies are generated, emphasizing the need for stringent data security measures.