AI Papers to Read in 2025
Reading recommendations to stay current with both foundational and recent achievements in AI and Data Science. This new edition continues the author’s tradition of highlighting meaningful research, not just the latest models.
Introduction
After a long break, the author returns to Towards Data Science to resume a well-received series of AI paper recommendations. The previous four editions have attracted a loyal audience interested in critical and reflective insights on AI research.
Purpose of the List
This list is intentionally subjective. It aims to inspire deeper understanding and encourage readers to think critically about how AI evolves rather than focus solely on technical supremacy. Each of the ten selected papers includes:
- A summary of the paper’s main contribution.
- Clear reasoning behind its inclusion.
- Additional references for extended exploration.
Author’s Reflection
“We don’t need larger models; we need solutions.”
“Do not expect me to suggest GPT nonsense here.”
In 2022, the author anticipated that future GPT iterations would be merely scaled-up versions with incremental improvements rather than revolutionary breakthroughs. Yet, the conclusion remains balanced:
“Credit where credit is due.”
Closing Thoughts
The article emphasizes thoughtful engagement with AI research, encouraging readers to look beyond hype and concentrate on meaningful progress and problem-solving.
Author’s Summary
This article gathers ten AI papers worth reading in 2025, encouraging critical thinking and offering practical insight into the evolving AI landscape.