PeopleofSuperintelligence

Researcher

Clayton Mullis

Also known as Clay Mullis, afiaka87

Clayton Mullis is a researcher and software engineer whose work connects open image-text datasets with generative models. In 2021, he became a core figure in LAION’s DALL·E reproduction effort and coauthored LAION-400M. He fine-tuned GLIDE on LAION data, coauthored LAION-5B, and shared the team’s 2022 NeurIPS award. As of October 2026, he is a software engineer.

Timeline

  1. 2021

    DALL·E reproduction community

    In 2021, Mullis is one of the core figures in LAION’s effort to reproduce OpenAI’s DALL·E model.

  2. 2021

    LAION-400M dataset

    He coauthors LAION-400M in 2021, an open dataset of 400 million CLIP-filtered image-text pairs with CLIP embeddings and nearest-neighbor indices for similarity search.

  3. March 2022

    GLIDE fine-tuning at LAION

    In March 2022, Mullis fine-tunes OpenAI’s GLIDE on LAION-2B subsets and brings human generations back into its outputs. LAION credits him with DALL·E-PyTorch training and analysis, GLIDE training, and WDS filtering for LAION-5B.

  4. April 2022

    DeepSpeed diffusion fine-tuning

    In April 2022, Mullis owns latent-diffusion-deepspeed, a work-in-progress project to fine-tune CompVis’s 1.4B latent diffusion text-to-image checkpoint with DeepSpeed.

  5. 2022

    LAION-5B dataset

    He coauthors LAION-5B in 2022, an open dataset of 5.85 billion CLIP-filtered image-text pairs, including 2.32 billion in English. It provides nearest-neighbor indices and a web interface for exploration and subset creation.

  6. 2022

    NeurIPS dataset award

    He shares the 2022 NeurIPS Outstanding Datasets and Benchmarks Paper award with the LAION-5B author team.

  7. As of October 2026

    Software engineer

    As of October 2026, he is a software engineer.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. The United States employs an estimated 48% of people shaping AIWe estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  3. 43% of living people shaping AI work outside their country of birthWe estimate that 43% of living people shaping AI work outside their country of birth (520 of 1,198 people with known birth and employment countries).
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionWe estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Sources and credits

Photo: We have no published photo of Clayton Mullis yet. Send us a free-licensed photo.

  1. Dialogue with Jenia Jitsev, LAION Research Lead gosim.org. Checked 22 October 2026.
  2. LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs arxiv.org. Checked 22 October 2026.
  3. LAION-5B: A NEW ERA OF OPEN LARGE-SCALE MULTI-MODAL DATASETS laion.ai. Checked 22 October 2026.
  4. latent-diffusion-deepspeed | Ecosystem Directory explore.market.dev. Checked 22 October 2026.
  5. LAION-5B: An open large-scale dataset for training next generation image-text models arxiv.org. Checked 22 October 2026.
  6. Announcing the NeurIPS 2022 Awards – NeurIPS Blog blog.neurips.cc. Checked 22 October 2026.
  7. afiaka87 (Clay Mullis) · GitHub github.com. Checked 22 October 2026.