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Rich Data vs. Quantity of Data in Code Generation AI: A Paradigm Shift for Healthcare
In high-stakes sectors like healthcare, not all data is created equal. This groundbreaking paper by Prof Muthu Ramachandran and Steven
Fouracre challenges the conventional wisdom of “more is better” — showing how rich, curated datasets outperform sheer data volume in Code Gen AI.
Key takeaways:
- Rich data yields more accurate, auditable, and privacy-compliant code
- Code Gen AI trained on massive unfiltered data increases errors and
tech debt
- Best practices for deploying Gen AI in regulated industries
- Case study: Self-Evolving Software (SES) proves the power of data curation
Essential reading for anyone in healthtech, AI, LLMs, software
engineering, and digital health policy.
Read the full paper at https://doi.org/10.30953/bhty.v8.396
