*Exploring how AI is accelerating, augmenting, and reshaping the scientific process.*

From designing new proteins and materials to generating research hypotheses and automating experiments, artificial intelligence is changing how science gets done.

But what does it really mean for AI to “do science”? Can algorithms generate ideas, test them, and learn like humans—or are they simply pattern-matching on data we’ve already collected? And what will the results look like for scientific progress?

In this interactive session, we’ll explore how AI systems are being used to bolster, automate, and reimagine the scientific process across disciplines—from biology and physics to climate science and social research.

We’ll walk through real examples such as:

* 🧬 AlphaFold & ESM — how deep learning cracked the protein-folding problem
* ⚗️ AI-driven lab automation — robotic scientists designing and running experiments
* 🌎 Climate & materials modeling — using AI to simulate complex systems and accelerate discovery
* 🧮 Explainable AI in the hard sciences — rediscovering natural laws from raw data
* 🧠 Agentic AI co-scientists — the emerging frontier of autonomous research systems proposed by companies like Google.

Along the way, we’ll discuss the philosophical and practical questions raised by these developments.

## 💬 Why Attend

* Learn how cutting-edge AI models are being applied in real scientific contexts.
* See live examples of “AI co-scientist” systems in action.
* Connect with researchers, technologists, and curious thinkers at the intersection of AI and discovery.
* Participate in short exercises exploring how your own domain could leverage AI for faster, smarter insights.

Join us for a thought-provoking evening where AI meets the scientific method. Come ready to ask questions, share your experiences, and imagine what a future of human–AI collaboration in science might look like.

NYC AI from Scratch Mastermind

Daniel

Andrew

Matt

Ilya Shlyakhter

Elijah S

Reena Daniel

Jack

Barbara Scobee

Jody S.

Magnus Hedemark

Mike Hillowalla

Jessica Oistacher

Irina Astrovskaya

Nihal Jain

Olaf

Santosh K

FrankG

Victor Manske

AI in Scientific Discovery: How Machine Intelligence is Transforming Research

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