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Meghan Heintz

Staff Software Engineer, Machine Learning and AI

Meghan Heintz is a professional with a background in environmental Data Science, climate modeling, geospatial data integration, numerical modeling, spatial computing, algorithm development, statistics, econometrics, computer vision, big data/machine learning, natural language processing, machine translation, and AI. She studied BS in Environmental Resource Engineering at Humboldt State University and has held various roles including Staff Data Scientist, Senior Data Scientist, and Software Engineer in organizations like Dune, Emerson Collective, Rent The Runway, Glossier, Inc., BuzzFeed, and Zynga. She has also worked as a Water Resources Consultant and held research positions related to water quality and treatment.

Highlights

Nov 15 · twitter

This is why AI watermarking text is ultimately going to succeed. LLMs already pick from a probability distribution that feels a little off and we can just tweak that a little further to accurately predict if and which LLM it came from.

https://t.co/39wqTczokF

Aug 26 · linkedin

Today I published part two of my series on improving RAG applications focusing on re-ranking.

Check it out and let me know if you have any favorite re-ranking methods I missed. I tried to stick mostly to discussing open-source models but would love to hear about experiences implementing proprietary models.

My favorite fact I learned while writing this was TF-IDF was invented not only by a woman but a self-taught programmer!

Meghan Heintz
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Location

New York, New York, United States