The role of data scientists is evolving with the rise of large language models, shifting from direct model training to a focus on the "harness" that guides AI systems. While foundation model APIs reduce the need for traditional predictive modeling, crucial tasks like setting up experiments, debugging complex systems, and designing effective metrics remain vital. The author argues that these essential functions are inherently data science work, requiring deep understanding of data and custom evaluation rather than relying on generic, off-the-shelf metrics. AI
RANK_REASON This is an opinion piece by an individual discussing the evolving role of data scientists in the context of LLMs.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
