Paper suggestions

Tom Zahavy · ICML · 2026

The abductive leap, inventing the premises rather than deriving the proof, is the one move LLMs still can't make. Read it right after The Bitter Lesson and let the two argue.

Rich Sutton · essay · 2019

1,100 words explaining seventy years of AI research regret: general methods plus compute beat human cleverness, every time.

Claude Shannon · Bell System Technical Journal · 1948

One paper invents the bit, entropy, and the ceiling on every channel. Everything else on this list is measured in its units.

Brown et al. · NeurIPS · 2020

Scale as a research result in its own right, and the paper where the current era of AI actually begins.

Krizhevsky, Sutskever & Hinton · NeurIPS · 2012

The starting gun for modern deep learning. Eight pages, one GPU trick, and a decade of consequences.

John Ioannidis · PLoS Medicine · 2005

The cheapest inoculation available against taking p-values at face value: uncomfortable, famous, and worth the discomfort.

Hadley Wickham · Journal of Statistical Software · 2014

The paper behind why every dataframe you've ever liked felt likeable. You already follow its rules; this is where they come from.

Halevy, Norvig & Pereira · IEEE Intelligent Systems · 2009

Why more data beats a cleverer model more often than anyone's pride would like. Four pages that predicted the next fifteen years.

Sculley et al. · NeurIPS · 2015

The model is the smallest box in the diagram; everything around it is the actual job. Read before your first ML role, re-read during it.

Leo Breiman · Statistical Science · 2001

The stats-versus-ML worldview split, named in 2001, and still the argument underneath every modeling debate you'll ever be in.