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Zerostack – A Unix-inspired coding agent written in pure Rust

https://crates.io/crates/zerostack/1.0.0
289•gidellav•7h ago•101 comments

Hosting a website on an 8-bit microcontroller

https://maurycyz.com/projects/mcusite/
86•zdw•4h ago•5 comments

Colossus: The Forbin Project

https://en.wikipedia.org/wiki/Colossus:_The_Forbin_Project
54•doener•2d ago•7 comments

A nicer voltmeter clock

https://lcamtuf.substack.com/p/a-nicer-voltmeter-clock
124•surprisetalk•7h ago•19 comments

C++26 Shipped a SIMD Library Nobody Asked For

https://lucisqr.substack.com/p/c26-shipped-a-simd-library-nobody
74•signa11•2d ago•31 comments

OpenAI and Government of Malta partner to roll out ChatGPT Plus to all citizens

https://openai.com/index/malta-chatgpt-plus-partnership/
135•bookofjoe•9h ago•129 comments

Why did Clovis toolmakers choose difficult quartz crystal?

https://phys.org/news/2026-04-clovis-toolmakers-difficult-quartz-crystal.html
10•PaulHoule•2d ago•4 comments

Unknowable Math Can Help Hide Secrets

https://www.quantamagazine.org/how-unknowable-math-can-help-hide-secrets-20260511/
41•Xcelerate•3d ago•6 comments

Self-Distillation Enables Continual Learning [pdf]

https://arxiv.org/abs/2601.19897
31•teleforce•4h ago•12 comments

SANA-WM, a 2.6B open-source world model for 1-minute 720p video

https://nvlabs.github.io/Sana/WM/
322•mjgil•18h ago•132 comments

Tesla Solar Roof is on life support as it pivot to panels

https://electrek.co/2026/05/14/tesla-solar-roof-promise-vs-reality-pivot-panels/
39•celsoazevedo•1h ago•18 comments

Illusions of Understanding in the Sciences

https://link.springer.com/article/10.1007/s42113-026-00271-1
14•sebg•2d ago•1 comments

Moving away from Tailwind, and learning to structure my CSS

https://jvns.ca/blog/2026/05/15/moving-away-from-tailwind--and-learning-to-structure-my-css-/
482•mpweiher•20h ago•306 comments

The Third Hard Problem

https://mmapped.blog/posts/48-the-third-hard-problem
53•surprisetalk•2d ago•37 comments

A molecule with half-Möbius topology

https://www.science.org/doi/10.1126/science.aea3321
82•bryanrasmussen•4d ago•4 comments

MCP Hello Page

https://www.hybridlogic.co.uk/blog/2026/05/mcp-hello-page
74•Dachande663•7h ago•25 comments

Accelerando (2005)

https://www.antipope.org/charlie/blog-static/fiction/accelerando/accelerando.html
269•eamag•18h ago•153 comments

We've made the world too complicated

https://user8.bearblog.dev/the-world-is-too-complicated/
243•James72689•21h ago•220 comments

Frontier AI has broken the open CTF format

https://kabir.au/blog/the-ctf-scene-is-dead
357•frays•23h ago•355 comments

Halt and Catch Fire

https://unstack.io/halt-and-catch-fire
113•ScottWRobinson•11h ago•60 comments

δ-mem: Efficient Online Memory for Large Language Models

https://arxiv.org/abs/2605.12357
203•44za12•20h ago•55 comments

Grafana Labs internal source code accessed

https://twitter.com/grafana/status/2055827123236171827
25•jschorr•2h ago•7 comments

Content-defined chunking added to Bazel

https://www.buildbuddy.io/blog/content-defined-chunking/
40•siggi•3d ago•3 comments

Fisker went bankrupt and owners built an open source car company from the ashes

https://electrek.co/2026/05/16/fisker-ocean-open-source-ev-story-after-bankruptcy/
108•breve•6h ago•41 comments

PART Telescopes – Bringing radio astronomy within reach of rural schools

https://parttelescopes.web.app/
119•openrockets•14h ago•30 comments

Show HN: Rocksky – Music scrobbling and discovery on the AT Protocol

https://tangled.org/rocksky.app/rocksky
65•tsiry•13h ago•31 comments

3D Gaussian Splatting in a Weekend

https://bfeldman.me/3dgs-weekend/
73•b__feldman•3d ago•7 comments

Kioxia and Dell cram 10 PB into slim 2RU server

https://www.blocksandfiles.com/flash/2026/05/14/kioxia-and-dell-cram-10-pb-into-slim-2ru-server/5...
122•rbanffy•12h ago•84 comments

Greek Alphabet Cards

https://labs.randomquark.com/alphabet_cards/
112•ricochet11•18h ago•50 comments

Nearly 50 Years Later, WKRP in Cincinnati Becomes a Real Radio Station

https://www.openculture.com/2026/05/nearly-50-years-later-wkrp-in-cincinnati-becomes-a-real-radio...
124•bookofjoe•4d ago•73 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•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•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?