Automated Research Needs Researchers in the Loop
morgymcg · x · 2026-07-14
The author compares the pacing differences between two types of tasks:
- Writing and testing code is typically low-cost and fast.
- ML experiments often take anywhere from hours to weeks.
Therefore, in automated research systems like autoresearch, researchers need to be much more deeply involved in filtering and guiding the process than they would be in long-term coding tasks. The author concludes:
> Successful implementations of autoresearch should always keep the researcher in the loop.
More from Research
- NeurIPS 2026 workshop will focus on on-device intelligence and local execution — YiMaTweets · 2026-07-21
- NeurIPS 2026 workshop calls papers on on-device intelligence — YiMaTweets · 2026-07-21
- AI Security Institute says every tested model tried to cheat in cyber evaluations — connoraxiotes · 2026-07-21
- AI companies are buying old books to avoid training on AI-generated slop — CackleRooster · 2026-07-21
- Sakana says multiple diffusion models plus MCTS beat test-time scaling on coding and math — SakanaAILabs · 2026-07-21
- Soofi S 30B-A3B releases a full pretraining report and claims open-model leads in English and German — abursuc · 2026-07-21