AI Papers to Read in 2025
Towards Data Science Recommendations
This article offers reading suggestions to keep you informed about important breakthroughs in AI and Data Science, combining both recent and classic works.
Returning to the Towards Data Science (TDS) platform, the author resumes a popular series of AI paper recommendations after a break. Long-term followers may remember the four earlier editions. This list is personal and opinionated, designed to provide insights and perspectives on AI developments rather than just showcasing state-of-the-art models.
“This is not a state-of-the-art models list but real insights on what to look for in the coming years and what you might have missed from the past.”
The goal is to encourage critical thinking about AI's current status. The list comprises ten selected papers, each summarized with its key contributions and clear reasons for their importance. Additionally, each paper suggestion includes a section for further reading with related topics to explore.
Reflecting on the author's 2022 article, they initially stated:
“We don’t need larger models; we need solutions” and “do not expect me to suggest GPT nonsense here.”
At the time, the author believed that future GPT models would only be slightly larger and better but not revolutionary. They acknowledge, however, the importance of giving credit where due.
Author's Summary
This curated selection guides readers through essential AI papers, focusing on meaningful insights beyond hype to foster a critical understanding of the field's evolution.
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