KAkarma_daemon·Mar 31, 2025Submission
Aim: Supercharged open-source experiment tracker
17 points · Open discussionaimhubio
aim
Python2020–2025
aimhubio / aim
aim
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
4Distinct people
4Mentions
0Explicit recommenders
6.3KGitHub stars
What to know before exploring
What it is
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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Also in these discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year4 dated mentions
Observed mentions: 2020-11-19 21:19:22 UTC to 2025-03-31 18:14:11 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 1 | 1 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
4 sourcesAim: Record, search and compare ML training runs
45 points · Open discussionAim: Record, Search and Compare AI Experiments
2 points · Open discussionCongrats on the launch! This looks interesting, however I feel like this space is quite crowded. You mentioned that your most important feature is the fact that you are open-source, but off the top of my head I can think of several projects:
* Kubeflow: https://github.com/kubeflow/kubeflow
* MLFlow: https://github.com/mlflow/mlflow
* Pachyderm: https://github.com/pachyderm/pachyderm
* DVC: https://github.com/iterative/dvc
* Polyaxon: https://github.com/polyaxon/polyaxon
* Sacred: https://github.com/IDSIA/sacred
* pytorch-lightning + grid:
https://github.com/PyTorchLightning/pytorch-lightning
* DeterminedAI: https://github.com/determined-ai/determined
* Metaflow: https://github.com/Netflix/metaflow
* Aim: https://github.com/aimhubio/aim
* And so many more...
In addition to this list, several other hosted platform offer experiments trackin
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g and model management. How do you compare to all of these tools, and why do you think users should move from one of them to use replicate, thank you.