https://archive.is/cGvKG
Readit NewsKerrickStaley commented on Proton Mail Helped FBI Unmask Anonymous 'Stop Cop City' Protester 404media.co/proton-mail-h... · Posted by u/sedatk
KerrickStaley commented on Google Workspace CLI github.com/googleworkspac... · Posted by u/gonzalovargas
Tried this out today and it feels half-baked unfortunately. I can't get auth working (https://github.com/googleworkspace/cli/issues/198).
The decision to pass all params as a JSON string to --params makes it unfriendly for humans to experiment with, although Claude Code managed to one-shot the right command for me, so I guess this is fine. This is an intentional design per https://justin.poehnelt.com/posts/rewrite-your-cli-for-ai-ag...
Side note, a lot happens at C3 other than the talks! Art, electronic gizmos and demos of all kinds, people hacking in realtime on projects, impromptu meetups, and bumping techno music :) I'd encourage people to attend in person if they get a chance; just watching the talks online is only a fraction of the experience.
KerrickStaley commented on Show HN: Vibe Code your 3D Models github.com/ierror/synaps-... · Posted by u/burrnii
I have been trying to force LLMs to work with geometries for over a month and it's so hard. Even the best LLMs have an extremely poor sense of geometric relationships in my testing. I would also stay away from mesh based CAD like OpenSCAD and go straight for build123d which operates on real solid models (BREP): https://build123d.readthedocs.io/en/latest/index.html
I recently designed an eval to see if LLMs can produce usable CAD models: https://kerrickstaley.com/2026/02/22/can-frontier-llms-solve...
Claude 4.6 Opus and Gemini 3.1 Pro can to some degree, although the 3D models they produce are often deficient in some way that my eval didn't capture.
My eval used OpenSCAD simply due to familiarity and not having time to experiment with build123d/CadQuery. There is an academic paper where they were successful at fine-tuning a small VLM to do CadQuery: https://arxiv.org/pdf/2505.14646
KerrickStaley commented on Can frontier LLMs solve CAD tasks? kerrickstaley.com/2026/02... · Posted by u/KerrickStaley
Pretty interesting that simulator-only binary feedback (unless I am reading it wrong) was enough here to build some pretty robust models!
I maintain [1], which provides the models with the ability to render a screenshot from any angle and as far as I can tell, visually driven feedback does not work that well as this point. The models probably don't get enough of "lovecraftian garbled 3D model mess" in the training data or something...
Cool project, thanks for sharing!
The simulator lets the LLM request renders from different angles/times, so the LLM can get visual feedback. For failures, the simulator also returns status codes like `object_fell` or `mount_initially_collided_with_object` depending on what happened. You can see what the tool call looks like by looking at the Transcript tab, e.g. here https://kerrickstaley.com/ai-cad-design-mount-viz/gso__mug__...
I agree it's not clear how much benefit models get from iteration. Many of the successful runs are one-shots. You can see some examples of basic spatial reasoning e.g. here https://kerrickstaley.com/ai-cad-design-mount-viz/gso__mug__... :
> The initial collision is because the mount was positioned at the same height as the mug's body center (z=-22), causing overlap. I need to lower the mount significantly so the mug starts above it and drops into the cradle.
KerrickStaley commented on Chained Assignment in Python Bytecode loriculus.org/blog/python... · Posted by u/wenderen
a = b = []
b = []
a = b
A fun way to play this game with less downside is to run `set -euo pipefail` in an interactive session. Then, whenever you execute a command that returns a non-zero exit code, your shell will exit immediately.
Unfortunately certain commands like `rg` will return non-zero by design when there are no matches, which could be an intentional outcome.
Super cool to read but can someone eli5 what Gaussian splatting is (and/or radiance fields?) specifically to how the article talks about it finally being "mature enough"? What's changed that this is now possible?
This 2-minute video is a great intro to the topic https://www.youtube.com/watch?v=HVv_IQKlafQ
I think this tech has become "production-ready" recently due to a combination of research progress (the seminal paper was published in 2023 https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/) and improvements to differentiable programming libraries (e.g. PyTorch) and GPU hardware.