Java and Building AI Applications with Kevin Dubois
Software Huddle
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Adapting Software Engineering for AI and ML
This chapter explores the challenges and adaptations required for traditional software engineering in the context of machine learning and AI applications. It highlights the complexity of integrating AI into enterprise systems, discusses the evolution of development tools, and stresses the importance of continuous education for developers. The conversation addresses trade-offs in model selection and emphasizes the need for flexible solutions that cater to varying accuracy standards and business requirements.
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