Brandon Duderstadt co-founded Nomic and was its founding CEO. Duderstadt is a co-author of the technical report for GPT4All, Nomic's open-source application for running large language models privately on everyday desktops and laptops. The Nomic Embed technical report credits Duderstadt with design contributions across the entire stack and the base implementation of its data curation pipeline. Duderstadt is now building Calcifer Computing, an AI research and development company that Duderstadt founded.12345
At a glance
- Current role
- Founder
- Company
- Calcifer Computing
- Sector
- Company
- Fields
- Language models, Datasets and data
- Education
- Johns Hopkins
- Work listed
- 4
- Sources cited
- 10
- Profile reviewed
Career
Brandon Duderstadt was an early team member at Rad AI, where Duderstadt's site says they trained the company's first CT and MRI models. Duderstadt then co-founded Nomic and served as its founding CEO.12
Duderstadt now runs Calcifer Computing, a long-term oriented AI research and development organization they founded to study the long-term impacts of AI on the epistemic environment. As a Whiting Fellow at Johns Hopkins University, Duderstadt teaches Introduction to Computational Semiotics and advises independent studies.12
Research and open-source work
Duderstadt co-authored the November 2023 GPT4All technical report, which describes an ecosystem of open-source compressed language models and was accepted at the NLP-OSS workshop at EMNLP 2023. The GPT4All repository describes the project as a way to run local language models on everyday devices.34
Duderstadt is a co-author of the Nomic Embed technical report (2024), which describes a reproducible long-context English text embedding model released with its training code, weights and curated training data, and whose contributions section credits Duderstadt with design work across the stack and the base data curation pipeline. Duderstadt also co-authored Nomic Embed Vision (2024), an image embedder sharing the text model's latent space, and a 2025 paper on training sparse mixture-of-experts text embedding models.6578
Work and contributions
GPT4All
Co-author of the GPT4All technical report and one of the authors listed in the repository's citation block.34
Nomic Embed
Made design contributions across the entire stack and wrote the base implementation of the data curation pipeline, according to the technical report's contributions section.56
nomic-embed-text-v2-moe Open weights
Second author of the paper on training sparse mixture-of-experts text embedding models, which the nomic-embed-text-v2-moe model card cites.89
nomic-embed-text-v1.5 Open weights
Third author of the Nomic Embed paper, which the nomic-embed-text-v1.5 model card cites.610
Timeline
- Co-authored the GPT4All technical report on an ecosystem of open-source compressed language models.3
- Co-authored the Nomic Embed technical report on a reproducible long-context text embedder.6
- Co-authored Nomic Embed Vision, an image embedding model aligned with Nomic's text embedding space.7
- Co-authored a paper on training sparse mixture-of-experts text embedding models with Zach Nussbaum.8
Other documented roles
Roles the sources document that are not confirmed as current.
Where they work
- Calcifer Computing 1 person in the wiki
Related people
- Vaishaal ShankarDatasets and data · Language models
- Marina DanilevskyLanguage models · Datasets and data
- Zach NussbaumLanguage models · Datasets and data
- Eugene YanLanguage models · Datasets and data
- Ronen EldanLanguage models · Datasets and data
- Ranit AharonovLanguage models · Datasets and data
- Adina WilliamsLanguage models · Datasets and data
- Dan SuLanguage models · Datasets and data
- Swabha SwayamdiptaDatasets and data · Language models
- Sheshansh AgrawalLanguage models · Datasets and data
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References
10 sources · profile reviewed Oct 21, 2026 · data updated Oct 22, 2026
- Nomad Garden (home page)
- Bio
- GPT4All: An Ecosystem of Open Source Compressed Language Models
- nomic-ai/gpt4all README
- Nomic Embed: Training a Reproducible Long Context Text Embedder (technical report)
- Nomic Embed: Training a Reproducible Long Context Text Embedder
- Nomic Embed Vision: Expanding the Latent Space (arXiv 2406.18587)
- Training Sparse Mixture Of Experts Text Embedding Models (arXiv 2502.07972)
- nomic-ai/nomic-embed-text-v2-moe model card
- nomic-ai/nomic-embed-text-v1.5 model card