AI Papers to Read in 2025
Here are some reading suggestions to help you stay informed about the most influential and insightful research in AI and Data Science. This marks the author’s return to writing for Towards Data Science with the continuation of a popular series of paper recommendations.
About the Series
The previous four editions built a consistent tradition of sharing personally curated AI works. This edition maintains that spirit by providing ten carefully selected papers, each accompanied by commentary on their impact and relevance.
Purpose of the List
The list aims to inspire thoughtful reflection on current and future developments in AI. Rather than focusing on the newest or largest models, it prioritizes papers that offer valuable insights, new perspectives, or overlooked discoveries from earlier research.
Key Features
- Ten recommended papers with short summaries of their core ideas.
- Detailed reasoning on why each paper is significant.
- A “further reading” section following each suggestion for exploring related topics.
Looking Back
The author references a 2022 article where they emphasized the importance of solving meaningful problems over simply scaling models.
“We don’t need larger models; we need solutions.”
“Do not expect me to suggest GPT nonsense here.”
The author once believed that new GPT versions would offer minimal innovation beyond size improvements. Yet, they acknowledge that credit should be given where it’s deserved, hinting that some advancements have proven more substantial than expected.
Author’s Summary
This edition continues the journey of critical exploration in AI, offering fresh, insightful reading suggestions designed to challenge assumptions and inspire constructive thinking about the field’s evolution.