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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.


Great work! If anyone’s planning to use AI generated artwork in their projects, I’ve added an image search API to Lexica, similar to Unsplash. All the images are licensed CC0 and millions more are being added every few weeks.

Docs here: https://lexica.art/docs


Been using Lexica quite a bit for prompt analysis, thanks for the work.

General browsing is heavily dominated by portraits though. I was wondering if it would be worth having a face detected flag on images so you could filter portraits.


That’s a really cool idea. Especially since that in particular doesn’t seem quite hard. Do you have any ideas in how you’d implement that?


Great work on Lexica.art, it's been indispensable for finding good prompts and combinations.

How much does it cost to host it? Feels like hosting 500GB of images and serving them can't be cheap.


Last month Lexica served a little over 1 billion images and the Cloudflare bill (I'm using R2 + workers) was a little over $5k. I've since gotten it down to a more reasonable amount after spending some time to re-encode the images to reduce our bandwidth usage significantly. If Lexica were running on AWS/S3 I imagine our first month's bill would be closer to $100k rather than $5k. This is only image serving, so not including costs to run the beefy CPU servers to run CLIP search, frontend, DB, backend, etc.


Why not go with a server or two or some VMs on Hetzner/Kimsufi/OVH/Netcup/BuyVM etc where they have very generous included transfer or even unmetered (BuyVM) ?

I get it that everyone wants to use the trendy newest tech (workers etc or whatever the latest is), but your bill could easily be 20% (or less) of the $5k kind of numbers you are mentioning.

I guess if those kind of numbers are just water under the bridge for you than you may as well go with the easier cloud setup/infra though.


Having used many different providers (though not all of the ones on your list), be very careful with suspiciously generous or unmetered anything. More often than not, you'll hit a soft limit where your performance will degrade and/or you'll get kicked for ToS violations.

Most apps never hit those limits, but once you get to multi-thousands/mo in cloud bills, there's benefits in pay-as-you-go billing where the provider is incentivized to let you use as much as you want to pay for.


> More often than not, you'll hit a soft limit where your performance will degrade and/or you'll get kicked for ToS violations.

Hetzner does have truly unmetered root servers, been using it myself for years. If you're doing Tor, Torrents or commercial CDN traffic, they might kick you out, but for other "normal" things, they seem to have no issues with handling it as they say they will.


Besides search and image listing, what other plans do you have with Lexica? Also, do you plan to open-source anything of it?


Weird 1billion 50k request ends up about 5k on the cloudfront pricing calculator. Do you have a bandwidth estimate? Idk how you got that 100k quote


What is the bandwidth like? I guess something in the order of a few 100 TB? Perhaps you can host this from a an "unmetered" server for $50 per month. Not sure how high your peak loads are though.


Thanks! Great work with Lexica.

We also released a free API https://devapi.krea.ai/ if anyone wants to check it out.

It will soon have endpoints with custom image generation features.


Amazing! Great to see more prompt APIs!


Amazing work, love Lexica! Thank you!


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