frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
568•klaussilveira•10h ago•160 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
885•xnx•16h ago•538 comments

How we made geo joins 400× faster with H3 indexes

https://floedb.ai/blog/how-we-made-geo-joins-400-faster-with-h3-indexes
89•matheusalmeida•1d ago•20 comments

What Is Ruliology?

https://writings.stephenwolfram.com/2026/01/what-is-ruliology/
16•helloplanets•4d ago•8 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
16•videotopia•3d ago•0 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
195•isitcontent•10h ago•24 comments

Monty: A minimal, secure Python interpreter written in Rust for use by AI

https://github.com/pydantic/monty
197•dmpetrov•11h ago•88 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

https://vecti.com
305•vecti•13h ago•136 comments

Microsoft open-sources LiteBox, a security-focused library OS

https://github.com/microsoft/litebox
352•aktau•17h ago•173 comments

Sheldon Brown's Bicycle Technical Info

https://www.sheldonbrown.com/
348•ostacke•16h ago•90 comments

Delimited Continuations vs. Lwt for Threads

https://mirageos.org/blog/delimcc-vs-lwt
20•romes•4d ago•2 comments

Hackers (1995) Animated Experience

https://hackers-1995.vercel.app/
450•todsacerdoti•18h ago•228 comments

Dark Alley Mathematics

https://blog.szczepan.org/blog/three-points/
78•quibono•4d ago•16 comments

PC Floppy Copy Protection: Vault Prolok

https://martypc.blogspot.com/2024/09/pc-floppy-copy-protection-vault-prolok.html
50•kmm•4d ago•3 comments

Show HN: If you lose your memory, how to regain access to your computer?

https://eljojo.github.io/rememory/
247•eljojo•13h ago•150 comments

An Update on Heroku

https://www.heroku.com/blog/an-update-on-heroku/
384•lstoll•17h ago•260 comments

Zlob.h 100% POSIX and glibc compatible globbing lib that is faste and better

https://github.com/dmtrKovalenko/zlob
10•neogoose•3h ago•6 comments

How to effectively write quality code with AI

https://heidenstedt.org/posts/2026/how-to-effectively-write-quality-code-with-ai/
228•i5heu•13h ago•173 comments

Show HN: R3forth, a ColorForth-inspired language with a tiny VM

https://github.com/phreda4/r3
66•phreda4•10h ago•11 comments

Why I Joined OpenAI

https://www.brendangregg.com/blog/2026-02-07/why-i-joined-openai.html
113•SerCe•6h ago•90 comments

I spent 5 years in DevOps – Solutions engineering gave me what I was missing

https://infisical.com/blog/devops-to-solutions-engineering
134•vmatsiiako•15h ago•59 comments

Introducing the Developer Knowledge API and MCP Server

https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/
42•gfortaine•8h ago•12 comments

Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
23•gmays•5h ago•4 comments

Understanding Neural Network, Visually

https://visualrambling.space/neural-network/
263•surprisetalk•3d ago•35 comments

I now assume that all ads on Apple news are scams

https://kirkville.com/i-now-assume-that-all-ads-on-apple-news-are-scams/
1037•cdrnsf•20h ago•429 comments

Learning from context is harder than we thought

https://hy.tencent.com/research/100025?langVersion=en
165•limoce•3d ago•87 comments

FORTH? Really!?

https://rescrv.net/w/2026/02/06/associative
59•rescrv•18h ago•22 comments

Show HN: ARM64 Android Dev Kit

https://github.com/denuoweb/ARM64-ADK
14•denuoweb•1d ago•2 comments

Show HN: Smooth CLI – Token-efficient browser for AI agents

https://docs.smooth.sh/cli/overview
86•antves•1d ago•63 comments

WebView performance significantly slower than PWA

https://issues.chromium.org/issues/40817676
22•denysonique•7h ago•4 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•8mo 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•8mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•8mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•8mo 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•8mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•8mo 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•8mo 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•8mo 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•8mo 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•8mo 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•8mo 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•8mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•8mo 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•8mo 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•8mo 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•8mo 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•8mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•8mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•8mo 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•8mo 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•8mo 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•8mo 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?