Why would you use Codex for code reviews but not as your daily driver?

This is awesome! Using a CLIP or Dino v2 model to produce image embeddings would probably improve the similarity search a lot - kind of similar to http://same.energy/ .

Thank you for your efforts!

This is very useful! I think the interfaces around models being used in an async manner will look very different than the synchronous chat UIs we are today. Claude Code is the first real “agent” that is providing true economic value, and there’s so much low hanging fruit in making the interfaces far better.

Thank you! Yes I agree :)

I have a few private “vibe check” questions and the 4 bit QAT 27B model got them all correctly. I’m kind of shocked at the information density locked in just 13 GB of weights. If anyone at Deepmind is reading this — Gemma 3 27B is the single most impressive open source model I have ever used. Well done!

I tried to use the -it models for translation, but it completely failed at translating adult content.

I think this means I either have to train the -pt model with my own instruction tuning or use another provider :(

Try mradermacher/amoral-gemma3-27B-v2-qat-GGUF

My current architecture is an on-device model for fast translation and then replace that with a slow translation (via an API call) when its ready.

24b would be too small to run on device and I'm trying to keep my cloud costs low (meaning I can't afford to host a small 27b 24/7).

Have you tried Mistral Small 24b?

My current architecture is an on-device model for fast translation and then replace that with a slow translation (via an API call) when its ready.

24b would be too small to run on device and I'm trying to keep my cloud costs low (meaning I can't afford to host a small 24b 24/7).

I agree, I instantly recognized signature ChatGPT-isms. Once I realized it wasn’t written by a person, I stopped reading.

Wow! I'd love to read a more in-depth blog post describing how to create one of these myself, and maybe even contribute my own splats to a collaborative library for iconic landmarks. I could see interactive splats being added to Wikipedia for popular locations.

https://reddit.com/r/GaussianSplatting/ has been slowly talking about the subject for a while now. There are probably several articles and vids in the search bar.

If you want GS news, https://radiancefields.com/ reports a lot of advances all the time.

I give a bit more color in the twitter thread https://x.com/fulligin/status/1892685973731061937

Only seems to have the first post; rest of thread didn’t load

Works for me.

Pretty much the same workflow as photogrammetry take a lot of images/videos and put them in one of the SOTA gaussian splatting tools.

There is an app you can try https://scaniverse.com/. it splats using your phone's gpu.

This is great! I wonder how hard it would be to use a pen plotter instead of a thermal printer. You could even use a procedurally generated handwriting font and Claude to make it feel like a handwritten letter.

That’s a neat idea — I wonder about pairing it with a low cost plotter like: https://www.generativehut.com/post/ly-drawbot-a-70-pen-plott...

Agreed. I keep my iPhone in my right pocket and my Ricoh GRIIIx in my left pocket whenever I go out. It’s such a fantastic camera given its size, especially with the APSC sensor in such a compact body.

I also have a Sony A7C but I haven’t used it since getting the Ricoh. Being pocketable is a massive factor in how much I use a camera.

This is awesome! Could you share more details on how you’re storing the image embeddings and performing the KNN search? Is there an on-device vector database for iOS?

Thanks for your attention. I did not use any database, but stored the embedding calculations as Object files. When the user opens the app, the program preload them and turn them into `MLMultiArray`. when the user searches, these `MLMultiArray` are traversed and the similarity is calculated separately.