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SHARP, an approach to photorealistic view synthesis from a single image

https://apple.github.io/ml-sharp/
354•dvrp•8h ago•77 comments

A2UI: A Protocol for Agent-Driven Interfaces

https://a2ui.org/
45•makeramen•3h ago•16 comments

Children with cancer scammed out of millions fundraised for their treatment

https://www.bbc.com/news/articles/ckgz318y8elo
290•1659447091•6h ago•231 comments

Quill OS: An open-source OS for Kobo's eReaders

https://quill-os.org/
312•Curiositry•12h ago•100 comments

Bonsai: A Voxel Engine, from scratch

https://github.com/scallyw4g/bonsai
91•jesse__•6h ago•11 comments

Full Unicode Search at 50× ICU Speed with AVX‑512

https://ashvardanian.com/posts/search-utf8/
4•ashvardanian•19h ago•0 comments

Cekura (YC F24) Is Hiring

https://www.ycombinator.com/companies/cekura-ai/jobs/YFeQADI-product-engineer-us
1•atarus•20m ago

A linear-time alternative for Dimensionality Reduction and fast visualisation

https://medium.com/@roman.f/a-linear-time-alternative-to-t-sne-for-dimensionality-reduction-and-f...
70•romanfll•5h ago•19 comments

Erdős Problem #1026

https://terrytao.wordpress.com/2025/12/08/the-story-of-erdos-problem-126/
109•tzury•7h ago•12 comments

Internal RFCs saved us months of wasted work

https://highimpactengineering.substack.com/p/the-illusion-of-shared-understanding
49•romannikolaev•5d ago•17 comments

ArkhamMirror: Airgapped investigation platform with CIA-style hypothesis testing

https://github.com/mantisfury/ArkhamMirror
24•ArkhamMirror•2h ago•7 comments

JetBlue flight averts mid-air collision with US Air Force jet

https://www.reuters.com/world/americas/jetblue-flight-averts-mid-air-collision-with-us-air-force-...
315•divbzero•13h ago•204 comments

Creating C closures from Lua closures

https://lowkpro.com/blog/creating-c-closures-from-lua-closures.html
37•publicdebates•4d ago•10 comments

“Are you the one?” is free money

https://blog.owenlacey.dev/posts/are-you-the-one-is-free-money/
360•samwho•4d ago•78 comments

8M users' AI conversations sold for profit by "privacy" extensions

https://www.koi.ai/blog/urban-vpn-browser-extension-ai-conversations-data-collection
549•takira•9h ago•191 comments

Native vs. emulation: World of Warcraft game performance on Snapdragon X Elite

https://rkblog.dev/posts/pc-hardware/pc-on-arm/x86_versus_arm_native_game/
83•geekman7473•12h ago•36 comments

7 Years, 2 Rebuilds, 40K+ Stars: Milvus Recap and Roadmap

https://milvus.io/blog/milvus-exceeds-40k-github-stars.md
25•Fendy•5d ago•8 comments

Show HN: I designed my own 3D printer motherboard

https://github.com/KaiPereira/Cheetah-MX4-Mini
79•kaipereira•1w ago•17 comments

High Performance SSH/SCP

https://www.psc.edu/hpn-ssh-home/
12•gslin•5d ago•4 comments

Essential Semiconductor Physics [pdf]

https://nanohub.org/resources/43623/download/Essential_Semiconductor_Physics.pdf
194•akshatjiwan•2d ago•8 comments

I'm a Tech Lead, and nobody listens to me. What should I do?

https://world.hey.com/joaoqalves/i-m-a-tech-lead-and-nobody-listens-to-me-what-should-i-do-e16e454d
67•joaoqalves•2h ago•55 comments

Economics of Orbital vs. Terrestrial Data Centers

https://andrewmccalip.com/space-datacenters
126•flinner•14h ago•181 comments

VS Code deactivates IntelliCode in favor of the paid Copilot

https://www.heise.de/en/news/VS-Code-deactivates-IntelliCode-in-favor-of-the-paid-Copilot-1111578...
40•sagischwarz•3h ago•7 comments

Show HN: Search the lyrics of 500 HÖR Berlin techno sets

https://hor.greg.technology/
8•gregsadetsky•4d ago•4 comments

Chafa: Terminal Graphics for the 21st Century

https://hpjansson.org/chafa/
171•birdculture•18h ago•28 comments

The appropriate amount of effort is zero

https://expandingawareness.org/blog/the-appropriate-amount-of-effort-is-zero/
140•gmays•16h ago•81 comments

Umbrel – Personal Cloud

https://umbrel.com
192•oldfuture•16h ago•106 comments

In Defense of Matlab Code

https://runmat.org/blog/in-defense-of-matlab-whiteboard-style-code
130•finbarr1987•3d ago•135 comments

Secret Documents Show Pepsi and Walmart Colluded to Raise Food Prices

https://www.thebignewsletter.com/p/secret-documents-show-pepsi-and-walmart
454•connor11528•14h ago•113 comments

A kernel bug froze my machine: Debugging an async-profiler deadlock

https://questdb.com/blog/async-profiler-kernel-bug/
104•bluestreak•15h ago•18 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•6mo ago
Hey HN! We recently graduated from YC, and have been building customer personas for large e-commerce companies. We recently expanded into the image generation space, and have been working on research about how to automatically improve the quality of generated images.

Comments

average_r_user•6mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•6mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•6mo ago
This is a wonderful writeup of building a simple agentic system in general. What OP describes is more or less the bare minimum you should be doing at this point to get good (consistent) results from an LLM; single-shot prompting is a thing of the past.
palashshah•6mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•6mo ago
I'm surprised you landed on using o3 as the judge - we found it way too expensive. I use llm as a judge for generating color variations of products, definitely hoping for some improvements - it can be brutal to get non hallucinated features along with proper final rendering.
omneity•6mo ago
Have you tried open weights vision models such as Qwen VL, MiniCPM, PaliGemma...?

I'm also curious how usable are simpler vision models such as Florence in case you explored this direction.

palashshah•6mo ago
we're currently in the process of doing this. i think something that could potentially work is to iterate upon the initial image composition / structure using cheaper models, and then upscale at the end. this way you're saving on that iteration cost, but eventually land on a higher-scale image.
shmoogy•6mo ago
I actually haven't but nova from Amazon was surprisingly good at things like bounding boxes compared to some others You kind of have to test and measure so many different aspects to get the best at specific tasks Thanks for the idea
elif•6mo ago
This is great and provides a good starting point for any similar efforts.

However I think the temptation to lean all tasks on AI is perhaps a little naive if not lazy.

For mask generation, there is really not much reason to use AI. In this example, simple stochastic blob detection, a trivial function you could get from openCV or ask a college sophomore to write would generate much better quality masks.

palashshah•6mo ago
totally agreed here. i think my goal primarily with the mask generation was to test out how effective openai's capabilities were.

we're currently working on pipelines that limit the the involvement of AI to various tasks. for example, when generating an ad there's usually logo, some banner text, and background image.

we can use gpt-image-1 to generate the background image, another LLM to identify the coordinates of where we place the logo, and just add the logo onto the image. this is just one example!

jackphilson•6mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•6mo ago
"Simple stochastic blob detection" is an abstraction. You write (or import) a function where the the gnarly logic lives and call `detectBlobs()`. "Use an abstraction" doesn't mean you should use the same abstraction for every task, you should use the right tool for the job.
mentalgear•6mo ago
Again another example of "the unreasonable effectiveness of LLMs in a loop". At with time, the tasks for loop become bigger and more complex, until we find ourselves "outlooped" at least job wise.
ramoz•6mo ago
Nice retrospective but I guess this process is no longer needed as model's get better; esp as they start enabling features like consistent subjects. Seems like a lot of overhead to correct text for inspirational images, but I can imagine you need to always present some form of _quality_ to your clients.

Feel like control nets and some minimal photoshop work would've been better.

palashshah•6mo ago
totally. it got to a point where most of the text generated in our images was incorrect, and so it wasn't a great look showing that to our clients.

we're actually working on some form of what you described where we take images generated from LLMs + add consistent logos discretely rather than generatively.

abshkbh•6mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•6mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•6mo ago
I was kind of hoping this would be in the 'Dreambooth mold' of finetuning open weights models. I have used that with some success some ~2 years ago, does anyone know what improvements there have been in that direction since Dreambooth?
zahlman•6mo ago
It's frankly amazing to me that "ask another LLM to evaluate the image" actually produces useful feedback that results in actual improvement from the first LLM.

But then, I guess it's not much different of an idea from the earlier use of GANs, or of telling LLMs to "stop hallucinating", etc.

palashshah•6mo ago
totally. the way i think about it (purely based on intuition) is that asking an LLM to do understanding + image generation is too complex for it to be effective. if we separate out the tasks into discrete steps, the evaluation becomes better, and the generation simply becomes instruction following.
jacob019•6mo ago
This is all edited with gpt-image-1? The revised images are amazing. Were example logos provided or is it just working off of it's knowledge of a well known brand?