This presentation explores the evolving landscape of machine learning by comparing traditional ML techniques with modern Large Language Models (LLMs). It examines the challenges of maintaining and scaling each approach, their impact on decision-making and innovation, and the overall value they bring to businesses. In particular, we focus on applications within the context of specialized models versus a generic approach. By analyzing both the limitations and opportunities inherent in these methods, the discussion provides insights into whether the rise of LLMs signals the end of classic ML or represents a complementary evolution in the field.

In this session, you will get to know more about:

• Challenges in maintaining and scaling both traditional ML and LLMs
• Impact of each approach on business decision-making and innovation
• Comparative value of specialized ML models versus generic LLMs in business applications