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Ghostty is now non-profit

https://mitchellh.com/writing/ghostty-non-profit
1043•vrnvu•13h ago•210 comments

Valve reveals it’s the architect behind a push to bring Windows games to Arm

https://www.theverge.com/report/820656/valve-interview-arm-gaming-steamos-pierre-loup-griffais
697•evolve2k•1d ago•584 comments

Average DRAM price in USD over last 18 months

https://pcpartpicker.com/trends/price/memory/
250•zekrioca•8h ago•153 comments

Uncloud - Tool for deploying containerised apps across servers without k8s

https://uncloud.run/
41•rgun•2h ago•15 comments

Reverse engineering a $1B Legal AI tool exposed 100k+ confidential files

https://alexschapiro.com/security/vulnerability/2025/12/02/filevine-api-100k
643•bearsyankees•14h ago•201 comments

Micron Announces Exit from Crucial Consumer Business

https://investors.micron.com/news-releases/news-release-details/micron-announces-exit-crucial-con...
530•simlevesque•14h ago•261 comments

The Differences Between an IndyCar and a F1 Car

https://www.openwheelworld.net/en/indycar101/76/IndyCar_vs_Formula_1_cars
61•1659447091•3d ago•37 comments

1D Conway's Life glider found, 3.7B cells long

https://conwaylife.com/forums/viewtopic.php?&p=222136#p222136
427•nooks•14h ago•144 comments

Saturn (YC S24) Is Hiring Senior AI Engineer

https://www.ycombinator.com/companies/saturn/jobs/R9s9o5f-senior-ai-engineer
1•etticat•1h ago

Show HN: I built a dashboard to compare mortgage rates across 120 credit unions

https://finfam.app/blog/credit-union-mortgages
239•mhashemi•11h ago•75 comments

RCE Vulnerability in React and Next.js

https://github.com/vercel/next.js/security/advisories/GHSA-9qr9-h5gf-34mp
498•rayhaanj•16h ago•171 comments

Acme, a brief history of one of the protocols which has changed the Internet

https://blog.brocas.org/2025/12/01/ACME-a-brief-history-of-one-of-the-protocols-which-has-changed...
103•coffee--•8h ago•41 comments

Why WinQuake exists and how it works

https://fabiensanglard.net/winquake/index.html
50•wicket•6h ago•1 comments

Show HN: A Minimal Monthly Task Planner (printable, offline, no signup)

https://printcalendar.top/
26•defcc•2h ago•7 comments

Kea DHCP: Modern, open source DHCPv4 and DHCPv6 server

https://www.isc.org/kea/
82•doener•8h ago•25 comments

In Northern Scotland, the Neolithic Age Never Ended

https://www.newyorker.com/magazine/2025/12/01/in-northern-scotland-the-neolithic-age-never-ended
6•samizdis•4d ago•1 comments

8086 Microcode Browser

https://nand2mario.github.io/posts/2025/8086_microcode_browser/
98•zdw•11h ago•0 comments

Ethiopian Volcano Erupts for First Time in Nearly 12K Years of Records

https://www.smithsonianmag.com/smart-news/ethiopian-volcano-erupts-for-the-first-time-in-nearly-1...
46•pseudolus•3d ago•8 comments

Euler Conjecture and CDC 6600

https://fortran-lang.discourse.group/t/euler-conjecture-and-cdc-6600/10501
31•zaikunzhang•4h ago•4 comments

Show HN: Mirror_bridge – C++ Reflection powered Python binding generation

https://github.com/FranciscoThiesen/mirror_bridge
6•fthiesen•2h ago•0 comments

Launch HN: Phind 3 (YC S22) – Every answer is a mini-app

104•rushingcreek•14h ago•78 comments

Lie groups are crucial to some of the most fundamental theories in physics

https://www.quantamagazine.org/what-are-lie-groups-20251203/
132•ibobev•13h ago•45 comments

Preserving Snow Crystals

https://www.its.caltech.edu/~atomic/snowcrystals/preserve/preserve.htm
38•jameslk•4d ago•12 comments

How to Synthesize a House Loop

https://loopmaster.xyz/tutorials/how-to-synthesize-a-house-loop
214•stagas•6d ago•80 comments

Anthropic taps IPO lawyers as it races OpenAI to go public

https://www.ft.com/content/3254fa30-5bdb-4c30-8560-7cd7ebbefc5f
337•GeorgeWoff25•22h ago•263 comments

Mirror_bridge – C++ reflection for generating Python/JS/Lua bindings

https://chico.dev/Mirror-Bridge/
8•fthiesen•2h ago•2 comments

Everyone in Seattle hates AI

https://jonready.com/blog/posts/everyone-in-seattle-hates-ai.html
769•mips_avatar•12h ago•766 comments

Why are my headphones buzzing whenever I run my game?

https://alexene.dev/2025/12/03/Why-do-my-headphones-buzz-when-i-run-my-game.html
179•pacificat0r•16h ago•125 comments

You can't fool the optimizer

https://xania.org/202512/03-more-adding-integers
249•HeliumHydride•20h ago•153 comments

What I don’t like about chains of thoughts (2023)

https://samsja.github.io/blogs/cot/blog/
39•jxmorris12•3d ago•16 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?