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Frontier AI has broken the open CTF format

https://kabir.au/blog/the-ctf-scene-is-dead
72•frays•1h ago•44 comments

Project Gutenberg – keeps getting better

https://www.gutenberg.org/
911•JSeiko•16h ago•192 comments

SQL patterns I use to catch transaction fraud

https://analytics.fixelsmith.com/posts/sql-fraud-patterns/
179•redbell•9h ago•53 comments

Ploopy Bean: a trackpoint for every computer

https://ploopy.co/shop/bean-pointing-stick/
89•jibcage•3d ago•39 comments

I believe there are entire companies right now under AI psychosis

https://twitter.com/mitchellh/status/2055380239711457578
1285•reasonableklout•12h ago•630 comments

The bird eye was pushed to an evolutionary extreme

https://www.quantamagazine.org/how-the-bird-eye-was-pushed-to-an-evolutionary-extreme-20260513/
97•sohkamyung•2d ago•33 comments

Gaining control of every projector and camera on campus

https://www.edna.land/blogs/posts/scanning/
16•ednaordinary•2d ago•1 comments

Additive Blending on the Nintendo 64

https://phoboslab.org/log/2026/05/n64-additive-blending
99•ibobev•18h ago•8 comments

England Runestones

https://en.wikipedia.org/wiki/England_runestones
39•cl3misch•3d ago•10 comments

The main thing about P2P meth is that there's so much of it (2021)

https://dynomight.net/p2p-meth/
111•tomjakubowski•9h ago•122 comments

Naturally Occurring Quasicrystals

https://johncarlosbaez.wordpress.com/2026/05/14/naturally-occurring-quasicrystals/
92•lukeplato•1d ago•9 comments

A 0-click exploit chain for the Pixel 10

https://projectzero.google/2026/05/pixel-10-exploit.html
371•happyhardcore•19h ago•189 comments

Research on mildew contamination affecting the sound quality of analog tapes

https://www.nature.com/articles/s40494-026-02592-7
18•crousto•1d ago•1 comments

I Bought a “Junk” PSP From Japan

https://gardinerbryant.com/i-bought-a-junk-psp-from-japan-heres-how-it-went/
52•Kate0CoolLibby•3d ago•20 comments

How to Write to SSDs [pdf]

https://www.vldb.org/pvldb/vol19/p1469-lee.pdf
101•matt_d•10h ago•12 comments

The sigmoids won't save you

https://www.astralcodexten.com/p/the-sigmoids-wont-save-you
197•Tomte•21h ago•198 comments

Orthrus-Qwen3: up to 7.8×tokens/forward on Qwen3, identical output distribution

https://github.com/chiennv2000/orthrus
81•FranckDernoncou•10h ago•9 comments

California bill would require patches or refunds when online games shut down

https://arstechnica.com/gaming/2026/05/bill-to-keep-online-games-playable-clears-key-hurdle-in-ca...
474•Lihh27•12h ago•298 comments

EMiX: Emulating Beyond Single-FPGA Limits

https://arxiv.org/abs/2604.27012
6•PaulHoule•2d ago•1 comments

Show HN: Epiq – Distributed Git based issue tracker TUI

https://ljtn.github.io/epiq/
53•jolaflow•8h ago•17 comments

ESP-EEG is an affordable 8-channel biosensing board

https://www.autodidacts.io/cerelog-esp-eeg-affordable-openbci-like-board/
47•surprisetalk•2d ago•14 comments

I designed a nibble-oriented CPU in Verilog to build a scientific calculator

https://github.com/gdevic/FPGA-Calculator
101•gdevic•15h ago•33 comments

Image-blaster: Creates 3D environments, SFX, and meshes from a single image

https://github.com/neilsonnn/image-blaster
157•MattRogish•17h ago•31 comments

Erlang/OTP 29.0

https://www.erlang.org/news/188
192•pyinstallwoes•9h ago•35 comments

The Zulip Foundation

https://blog.zulip.com/2026/05/15/announcing-zulip-foundation/
265•boramalper•14h ago•69 comments

Show HN: Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/
152•c1b•1d ago•36 comments

ASCII by Jason Scott

https://ascii.textfiles.com/
188•bookofjoe•18h ago•22 comments

Bun Rust rewrite: "codebase fails basic miri checks, allows for UB in safe rust"

https://github.com/oven-sh/bun/issues/30719
391•ndiddy•15h ago•276 comments

U.S. DOJ demands Apple and Google unmask over 100k users of car-tinkering app

https://macdailynews.com/2026/05/15/u-s-doj-demands-apple-and-google-unmask-over-100000-users-of-...
417•tencentshill•15h ago•287 comments

Radicle: Sovereign {code forge} built on Git

https://radicle.dev/
236•KolmogorovComp•20h ago•85 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•11mo 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•11mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•11mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•11mo 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•11mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•11mo 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•11mo 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•11mo 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•11mo 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•11mo 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•11mo 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•11mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•11mo 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•11mo 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•11mo 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•11mo 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•11mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•11mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•11mo 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•11mo 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•11mo 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•11mo 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?