Feel free to reach me out via hi at phail dot ai

All real hardware, no simulation. Franka FR3 arm with a Robotiq gripper, physical totes, real objects. Every run is recorded with synced video and telemetry (you can watch any episode on the site).

That's the whole point – simulation benchmarks exist, but operators deploying robots care about real-world performance.

We're working on adding DreamZero (NVIDIA's latest) next. The leaderboard is open to any model – both open-source and closed-source. If you have a checkpoint, we'll run it on the same hardware under the same blind protocol. Closed-source participants can submit their model as a container and we evaluate it without accessing the weights. Reach out at hi@phail.ai if you want to submit.

Hi HN, I’m Sergey, the author of pos3.

I built this because I hit a wall with ML pipelines where I needed to feed S3 data into libraries that only understand local paths (like OpenCV imread, pandas, or PyTorch), and I didn't want to rewrite all my I/O code to use boto3 or s3fs.

Unlike s3fs which mounts S3 as a virtual filesystem (often slow for heavy random access), pos3 mirrors the specific data you need to a local cache before your code block runs. This means your script runs at native disk speed.

It handles the diffing/syncing automatically using a context manager:

---

import pos3, pandas as pd

with pos3.mirror():

    dataset = pos3.download("s3://bucket/dataset")
    df = pd.read_csv(dataset / "data.csv")

    logs = pos3.upload("s3://bucket/output/", interval=30)
    df.to_csv(logs / "processed.csv")

---

It's open source (Apache 2.0). I’d love to hear your feedback or if you've solved this differently!

We are working on open source platform for AI robotics, https://positronic.ro

Fully open hardware and software, including ML, so that you can start building useful robots immediately