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Can Dutch universities do without Microsoft?

https://dub.uu.nl/en/news/can-dutch-universities-do-without-microsoft
110•robtherobber•1h ago•76 comments

C++ Web Server on my custom hobby OS

https://oshub.org/projects/retros-32/posts/getting-a-webserver-running
20•joexbayer•38m ago•3 comments

So you wanna build a local RAG?

https://blog.yakkomajuri.com/blog/local-rag
27•pedriquepacheco•58m ago•3 comments

Bringing Sexy Back. Internet surveillance has killed eroticism

https://lux-magazine.com/article/privacy-eroticism/
50•eustoria•47m ago•8 comments

Don't tug on that, you never know what it might be attached to

https://blog.plover.com/2016/07/01/#tmpdir
43•todsacerdoti•1h ago•8 comments

True P2P Email on Top of Yggdrasil Network

https://github.com/JB-SelfCompany/Tyr
32•basemi•1h ago•5 comments

Meta hiding $27B in debt using advanced geometry

https://stohl.substack.com/p/exclusive-credit-report-shows-meta
155•FreeQueso•1h ago•65 comments

Atuin’s New Runbook Execution Engine

https://blog.atuin.sh/introducing-the-new-runbook-execution-engine/
62•emschwartz•3d ago•8 comments

Show HN: An LLM-Powered Tool to Catch PCB Schematic Mistakes

https://netlist.io/
7•wafflesfreak•22m ago•2 comments

Show HN: Glasses to detect smart-glasses that have cameras

https://github.com/NullPxl/banrays
417•nullpxl•12h ago•150 comments

AI Adoption Rates Starting to Flatten Out

https://www.apolloacademy.com/ai-adoption-rates-starting-to-flatten-out/
77•toomuchtodo•1h ago•33 comments

Petition to formally recognize open source work as civic service in Germany

https://www.openpetition.de/petition/online/anerkennung-von-open-source-arbeit-als-ehrenamt-in-de...
347•PhilippGille•3h ago•92 comments

JSON Schema Demystified: Dialects, Vocabularies and Metaschemas

https://www.iankduncan.com/engineering/2025-11-24-json-schema-demystified/
3•navigate8310•19m ago•0 comments

Tech Titans Amass Multimillion-Dollar War Chests to Fight AI Regulation

https://www.wsj.com/tech/ai/tech-titans-amass-multimillion-dollar-war-chests-to-fight-ai-regulati...
142•thm•8h ago•141 comments

Moss: a Rust Linux-compatible kernel in 26,000 lines of code

https://github.com/hexagonal-sun/moss
305•hexagonal-sun•6d ago•76 comments

Pocketbase – open-source realtime back end in 1 file

https://pocketbase.io/
545•modinfo•14h ago•147 comments

Stellantis Is Spamming Owners' Screens with Pop-Up Ads for New Car Discounts

https://www.thedrive.com/news/stellantis-is-spamming-owners-screens-with-pop-up-ads-for-new-car-d...
46•cf100clunk•1h ago•15 comments

The Signal Is the Noise

https://www.magazine.dirt.fyi/p/the-signal-is-the-noise
11•surprisetalk•1h ago•4 comments

A Tale of Four Fuzzers

https://tigerbeetle.com/blog/2025-11-28-tale-of-four-fuzzers/
45•jorangreef•5h ago•13 comments

A Remarkable Assertion from A16Z

https://nealstephenson.substack.com/p/a-remarkable-assertion-from-a16z
241•boplicity•5h ago•97 comments

Tell HN: Want a better HN? Visit /newest

177•alecco•1h ago•55 comments

Apple and Intel Rumored to Partner on Mac Chips

https://www.macrumors.com/2025/11/28/intel-rumored-to-supply-new-mac-chip/
38•bigyabai•52m ago•5 comments

Swedish publishers file police report against Meta's Zuckerberg for fraud

https://www.sverigesradio.se/artikel/swedish-publishers-file-police-report-against-metas-zuckerbe...
71•Frieren•2h ago•17 comments

A Repository with 44 Years of Unix Evolution

https://www.spinellis.gr/pubs/conf/2015-MSR-Unix-History/html/Spi15c.html
74•lioeters•8h ago•18 comments

Generating 3D Meshes from Text

https://cprimozic.net/notes/posts/generating-3d-meshes-from-text/
8•todsacerdoti•2h ago•1 comments

Playtiles: The Pocket-Sized Gaming Platform

https://get.playtil.es
12•surprisetalk•1h ago•4 comments

Lobsters Interview

https://susam.net/my-lobsters-interview.html
3•blenderob•1h ago•0 comments

The Math of Why You Can't Focus at Work

https://justoffbyone.com/posts/math-of-why-you-cant-focus-at-work/
57•0x79de•8h ago•18 comments

Writing Builds Resilience in Everyday Challenges by Changing Your Brain

https://scienceclock.com/writing-builds-resilience-in-everyday-challenges-by-changing-your-brain/
17•PikelEmi•4h ago•2 comments

Show HN: Spikelog – A simple metrics service for scripts, cron jobs, and MVPs

https://spikelog.com
25•dsmurrell•1d ago•12 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?