Description

I recently came across a “Top 30” reading list curated by Ilya Sutskever. The original version lives on GitHub, but there’s a more reader-friendly version that’s been making the rounds here on Substack.

Naturally, I started thinking about it while walking the dog—because what else do nerds do on a quiet stroll if not mentally categorize foundational AI papers?

That’s when it hit me: I want to know these papers. I want to understand why they matter. But some of them—say, the ones on quantum chemistry—are a bit outside my comfort zone.

Still, if the past few years have taught me anything, it’s this: I can learn almost anything as long as I ask the right questions—and let AI help break things down.

So I thought: what if others feel the same way? What if you’d love to understand “Neural Turing Machines,” but just need someone to translate the academic into approachable?

That’s the idea behind my new series: The Wolf Reads AI — formerly known in my head as “30 Papers in 30 Days.”

Starting tomorrow, I’ll be walking through one foundational paper per day. Each post will include:

* A short, friendly explainer

* A quick podcast summary

* A link to the original paper

We’ll kick it off with a classic: Attention Is All You Need.

If you’ve ever wanted to understand the AI breakthroughs behind today’s tools—but without falling into a pit of equations—you’ll want to follow along.

Subscribe now. The Wolf starts reading tomorrow.

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#Transformers #DeepLearning #AIResearch #MachineLearning #NeuralNetworks #TheWolfReadsAI #AttentionIsAllYouNeed #SubstackSeries #AIExplained #LearningTogether #ilyasutskever #30papersin30days #deeplearningwiththewolf

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit dianawolftorres.substack.com