frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

Railway Blocked by Google Cloud

https://status.railway.com/?date=20260519
394•aarondf•5h ago•184 comments

FiveThirtyEight articles on the Internet Archive

https://fivethirtyeightindex.com/
131•ChocMontePy•4h ago•32 comments

Gemini 3.5 Flash

https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5/
703•spectraldrift•12h ago•505 comments

I’ve built a virtual museum with nearly every operating system you can think of

https://virtualosmuseum.org/
701•andreww591•14h ago•159 comments

Remove–AI–Watermarks – CLI and library for removing AI watermarks from images

https://github.com/wiltodelta/remove-ai-watermarks
223•janalsncm•7h ago•116 comments

Google changes its search box

https://blog.google/products-and-platforms/products/search/search-io-2026/
468•berkeleyjunk•11h ago•656 comments

Show HN: Forge – Guardrails take an 8B model from 53% to 99% on agentic tasks

https://github.com/antoinezambelli/forge
396•zambelli•17h ago•148 comments

GitHub Compromised

https://twitter.com/github/status/2056949168208552080
119•claaams•2h ago•35 comments

OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

https://openai.com/index/advancing-content-provenance/
254•smooke•10h ago•130 comments

Apple unveils new accessibility features

https://www.apple.com/newsroom/2026/05/apple-unveils-new-accessibility-features-and-updates-with-...
646•interpol_p•18h ago•329 comments

Mistral AI acquires Emmi AI

https://www.emmi.ai/news/mistral-ai-acquires-emmi-ai
221•doener•11h ago•58 comments

Nostalgic Electronics Kits Central

https://www.nostalgickitscentral.com/
8•cf100clunk•2d ago•3 comments

In 1979 engineer Hugh Padgham discovered "gated reverb" – by accident

https://producelikeapro.com/blog/how-one-recording-mistake-created-a-musical-phenomenon-in-the-80s/
22•bookofjoe•2d ago•1 comments

Skills in Web, iOS, and Android

https://x.ai/news/grok-skills
10•surprisetalk•1d ago•1 comments

Evals will break

https://wanglun1996.github.io/blog/your-evals-will-break.html
24•rajveerb•3h ago•3 comments

India's hottest district shuts at 10 am as mercury breaches 48 C mark

https://www.hindustantimes.com/india-news/indias-hottest-district-banda-shuts-at-10-am-as-mercury...
39•rustoo•1h ago•20 comments

The Mercury logic programming system

https://github.com/Mercury-Language/mercury
55•Antibabelic•1d ago•10 comments

GitHub is investigating unauthorized access to their internal repositories

https://twitter.com/github/status/2056884788179726685
333•splenditer•6h ago•106 comments

Gemini CLI will stop working from June 18, 2026

https://developers.googleblog.com/an-important-update-transitioning-gemini-cli-to-antigravity-cli/
153•primaprashant•12h ago•63 comments

Minnesota becomes first state to ban prediction markets

https://www.npr.org/2026/05/19/nx-s1-5821265/minnesota-ban-prediction-markets
601•ortusdux•11h ago•187 comments

Lisp in Web-Based Applications (2001)

https://sep.turbifycdn.com/ty/cdn/paulgraham/bbnexcerpts.txt
71•bschne•1d ago•4 comments

Museum of Imaginary Musical Instruments

https://imaginaryinstruments.org/
25•bookofjoe•2d ago•5 comments

I’ve joined Anthropic

https://twitter.com/karpathy/status/2056753169888334312
1259•dmarcos•15h ago•520 comments

Growing Neural Cellular Automata

https://distill.pub/2020/growing-ca/
96•pulkitsh1234•2d ago•11 comments

Testing MiniMax M2.7 via API on three real ML and coding workflows

https://andlukyane.com//blog/minimax-m27-workflows
5•Artgor•1h ago•0 comments

Why is almost everyone right-handed? A new study connects it to bipedalism

https://www.ox.ac.uk/news/2026-05-15-why-is-almost-everyone-right-handed-the-answer-may-lie-in-ho...
118•gmays•15h ago•181 comments

HTML-in-Canvas Demos

https://github.com/GoogleChromeLabs/css-web-ui-demos/blob/main/html-in-canvas/awesome-html-in-can...
27•simonpure•6h ago•9 comments

The two oldest printing presses

https://museumplantinmoretus.be/en/worlds-two-oldest-printing-presses
35•janpot•2d ago•13 comments

Tool mapping 90 companies in the photonics and CPO supply chain

https://leonardo-boquillon.com/photonic-cop-supply-chain
39•lboquillon•2d ago•2 comments

Copy Fail, Dirty Frag, and Fragnesia kernel vulnerabilities

https://www.gentoo.org/news/2026/05/19/copy-fail-fragnesia-vulnerabilities.html
120•akhuettel•14h ago•47 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•12mo 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•12mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•12mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•12mo 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•12mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•12mo 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•12mo 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•12mo 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•12mo 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•12mo 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•12mo 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•12mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•12mo 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•12mo 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•12mo 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•12mo 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•12mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•12mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•12mo 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•12mo 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•12mo 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•12mo 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?