Howdy

I’m a Machine Learning Researcher currently at Tacit Labs. Before that I was at MosaicML / Databricks, a Research Scholar at cohere labs, and earlier an MLE at KUNGFU.AI. I was a main contibutor to LifeSciBench and have published work on data pruning (the longer pre-print here) for LLM pretraining. My reearch has been in LLM evaluations, faithfulness, but has reached into computer vision, audio, and more.

My motion based hobbies include surfing, backpacking where I can forget about the anthropocene, lifting, and playing ultimate frisbee. My more stationary hobbies include puzzle games, rougelikes, and reading. In Austin I played frisbee on Riverside and loved hanging out in my backyard with my cat, Callie. I grew up in Austin, went to school in Los Angeles, moved back home, then to San Francisco in October 2023.

my worst takes are here

my poor attempts at professionalism are here

my code is here

my str8 up email (remove the hightech captcha): m m a r i o n 5 3 8 @ < r o b o t s g o a w a y > @ g m a i l

I was recently briefly featured in this Scientific American article on LLMs and their possibilities for religious applications and this Wall Street Journal article on Noah Lyles and the “rise of nerds.”

Here’s a list of the cooler projects I’ve worked on, during which my role always fell under “make the neural network work”:

Evals for SOTA LLMs
Hallucination detection and correction
Efficacy of LLMAsAJudge
My paper exploring various methods of judging language data as low or high quality (paper link)
An algorithm to judge the price of collectibles like Pokemon cards, baseball cards, or rare coins
A computer vision project identifying and pricing exterior damage on cars from cell phone photos
A model for processing ambient rainforest noise to find gunshots, chainsaws, and vehicles indicating poaching and logging
A system to scan insurance corpora to extract helpful sentences like “drug X is covered by plan Y under situation Z, but not situation A”
A CTR (Click Through Rate) predictor for crowd groaning noises ads
A FOD detector for runway radar scans (detects debris on your runway that’d destroy your fancy plane engines)
A number of “information extractors” for large datastores of pdfs
The algorithm that judges SXSW speaker applications alongside human judges
and more! that are either less interesting or I’m not allowed to tell you about