@fujikanaeda: Today marks the end of my last week at Nvidia. I joined with the rest of the excellent Gretel team when we were acquire…

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Summary

Fuji Kanaeda announces departure from Nvidia after a year, highlighting contributions to synthetic data generation (NeMo Data Designer) and Nemotron LLM builds, praising the team's work on open-source AI.

Today marks the end of my last week at Nvidia. I joined with the rest of the excellent Gretel team when we were acquired back in April of 2025, which now seems like 10 years ago thanks to the time-dilation of AI progress. Over that year, I got to do quite a lot: help build the best synthetic data generation tool in the industry (NeMo Data Designer), scaling it out for pre & post-training datasets for Nemotron by building some slick cluster tooling, contributed to 4 (!!) Nemotron LLM builds (Nvidia doesn’t mess around with open models), took a small merging experiment reproduction from small scale (30B ) up to 550B and pass along some pretty significant eval compute savings as a consequence for our pretraining heros, pull my hair out over the state of public evals & benchmarks, and most importantly, got to collaborate with some of the best researchers and engineers in the field, all working to advance the frontier of open-source AI and build the best computing platforms in the world to support it. Thank you to everyone @ Nvidia & Nemotron for welcoming me into Team Green . Thank you to the Gretelers for your support over this journey .
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Today marks the end of my last week at Nvidia.

I joined with the rest of the excellent Gretel team when we were acquired back in April of 2025, which now seems like 10 years ago thanks to the time-dilation of AI progress.

Over that year, I got to do quite a lot:

help build the best synthetic data generation tool in the industry (NeMo Data Designer),

scaling it out for pre & post-training datasets for Nemotron by building some slick cluster tooling,

contributed to 4 (!!) Nemotron LLM builds (Nvidia doesn’t mess around with open models),

took a small merging experiment reproduction from small scale (30B ) up to 550B and pass along some pretty significant eval compute savings as a consequence for our pretraining heros,

pull my hair out over the state of public evals & benchmarks,

and most importantly, got to collaborate with some of the best researchers and engineers in the field, all working to advance the frontier of open-source AI and build the best computing platforms in the world to support it.

Thank you to everyone @ Nvidia & Nemotron for welcoming me into Team Green . Thank you to the Gretelers for your support over this journey .

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