AI Papers to Read in 2025 | Towards Data Science
This article offers curated reading recommendations to help you stay informed about key advancements and foundational works in AI and Data Science. Returning after a break, the author revives a popular series of AI paper suggestions.
About the Series
The author’s long-time followers may remember four previous editions. This list is highly opinionated, blending insights and detours to present a broad view of AI's evolution. It focuses on meaningful perspectives rather than merely spotlighting the latest state-of-the-art models.
Purpose and Structure
The goal is to encourage critical thinking on AI’s current landscape. The article includes ten recommended papers, each accompanied by a summary of its main contribution and clear reasons for its importance. Additionally, every recommendation has a “further reading” section, providing related topics to explore more deeply.
“We don’t need larger models; we need solutions” and “do not expect me to suggest GPT nonsense here.”
These statements from the former 2022 article emphasize the author's skepticism about ever-growing model sizes without groundbreaking innovation. Although initially doubtful about new GPT models, the author acknowledges giving credit where it is deserved.
Summary
- The series prioritizes critical insights over flashy advances.
- Includes ten AI papers with detailed rationales.
- Offers pathways to deeper exploration with further reading.
- Reflects a thoughtful stance on AI progress and model scaling trends.
Author's Conclusion
This collection invites readers to look beyond hype and focus on substantive, solution-oriented AI research that shapes the field's future.
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