Dr. Jessica Rumbelow, founder of Leap Labs, explains how mechanistic interpretability allows AI to uncover novel scientific patterns that humans cannot perceive.
“If you've got really good interp, you can start to reframe neural networks, not as just a tool for automating things that we already know how to do, but as a tool for discovery, as like a lens through which you can see patterns in data that would otherwise
Be hidden from you.”
quote is from the automated transcript, cleaned for reading:
filler sounds and stutters are removed, nothing is rephrased. names can be misheard
(the analysis reads context, assessments check outside sources). how →
“Discovery Engine is an end-to-end system, takes in arbitrary scientific data set, automatically trains a bunch of neural networks on it, and then We systematically, with our interpretability methods, which is the real secret extract the patterns that have been…”
Rumbelow: arXiv Is Filling With Plausible but Unverified AI Papers
“I'm actually really worried about this because I think we're already seeing archive and other online repositories and... Submissions too, full of these very, very plausible papers. That may or may not be true. And like at that point, what good is the, is our s…”
Rumbelow: LLMs Are Ill-Suited for Large Numeric Datasets
“Language models are just that, right? They're models of language. They are not particularly well suited for understanding arbitrary, you know, like big numeric data sets.”
Rumbelow: Standalone Claude Opus Hallucinated Materials Science Data Findings
“So, so Claude, lovely Claude. I'm sorry Claude, but you did a terrible job. It hallucinated some stuff. It made some like big sweeping over, over generalizations. It like over indexed the few outliers. Like, it's fine. It's not Claude's fault. Like Claude is j…”
Rumbelow: Multimodal analysis is impossible without fine labeling or interpretability
“It's largely impossible to do good data analysis on multimodal data of this kind, unless you have really fine grained labeling of your images. For example, which is just very, very burdensome, but obviously deep learning, we can let the model figure out its ow…”
This entire site, over 200 episodes transcribed, diarized, checked and made playable,
runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the
moments worth sharing, cuts them, captions them, and reframes them for every feed.
We use essential cookies to make the site work. With your permission we
also use analytics cookies (Google Analytics and Mixpanel) to understand
usage and improve StarZero. See our Cookie Policy.