ML & AI Safety Updates
About
ML & AI Safety Updates, abbreviated MLAISU, was a weekly content series produced by Apart Research starting in approximately September 2022. The series was created to address a gap in the AI safety information landscape: while existing newsletters focused on deep examinations of specific topics, MLAISU aimed to provide timely, broad weekly updates on what was happening across the entire field of alignment and ML safety research. The series was available in three formats: a written newsletter hosted at newsletter.apartresearch.com, a podcast distributed on Spotify, and short YouTube videos of 4 to 6 minutes each summarizing recent developments. Topics covered included mechanistic interpretability, scaling oversight, robustness, AI legislation, large language model behavior, and opportunities in the AI safety space such as hackathons, courses, and conferences. MLAISU was created and led by Esben Kran, co-director of Apart Research, along with Thomas Steinthal and Sabrina Zaki. It was published under Apart Research, an organization that also runs large-scale AI safety research hackathons (called Apart Sprints) and supports the development of AI safety research talent globally. The series ran from late 2022 into 2023, covering approximately 50 weekly issues. It was later discontinued when Apart Research reprioritized its organizational activities, shifting focus more heavily toward its research sprint programs and talent pipeline work.
Theory of Change
By providing timely weekly summaries of the latest alignment and ML safety research across multiple accessible formats (newsletter, podcast, YouTube), the series aimed to keep a broad audience of researchers, students, and interested practitioners informed and engaged with the AI safety field. Better-informed researchers and a larger community aware of open problems and opportunities would accelerate progress on AI safety, increasing the chances of safe AI development outcomes.
Details
- Start Date
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- End Date
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- Expected Duration
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- Funding Raised to Date
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- Last Updated
- Apr 3, 2026, 1:18 AM UTC
- Created
- Apr 3, 2026, 1:18 AM UTC