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GPT-5.2

https://openai.com/index/introducing-gpt-5-2/
724•atgctg•6h ago•579 comments

Denial of service and source code exposure in React Server Components

https://react.dev/blog/2025/12/11/denial-of-service-and-source-code-exposure-in-react-server-comp...
183•sangeeth96•4h ago•86 comments

Rivian Unveils Custom Silicon, R2 Lidar Roadmap, and Universal Hands Free

https://riviantrackr.com/news/rivian-unveils-custom-silicon-r2-lidar-roadmap-universal-hands-free...
192•doctoboggan•6h ago•264 comments

Nokia N900 Necromancy – giving a new life to a classic Linux smartphone

https://yaky.dev/2025-12-11-nokia-n900-necromancy/
15•yaky•53m ago•2 comments

The highest quality codebase

https://gricha.dev/blog/the-highest-quality-codebase
412•Gricha•3d ago•286 comments

An SVG is all you need

https://jon.recoil.org/blog/2025/12/an-svg-is-all-you-need.html
126•sadiq•5h ago•53 comments

Litestream VFS

https://fly.io/blog/litestream-vfs/
214•emschwartz•6h ago•71 comments

Programmers and software developers lost the plot on naming their tools

https://larr.net/p/namings.html
134•todsacerdoti•6h ago•214 comments

The architecture of “not bad”: Decoding the Chinese source code of the void

https://suggger.substack.com/p/the-architecture-of-not-bad-decoding
57•Suggger•10h ago•55 comments

Show HN: Sim – Apache-2.0 n8n alternative

https://github.com/simstudioai/sim
136•waleedlatif1•7h ago•27 comments

Craft software that makes people feel something

https://rapha.land/craft-software-that-makes-people-feel-something/
230•lukeio•11h ago•113 comments

UK House of Lords attempting to ban use of VPNs by anyone under 16

https://alecmuffett.com/article/134925
248•nvarsj•4h ago•236 comments

Powder and stone, or, why medieval rulers loved castles

https://1517.substack.com/p/powder-and-stone-or-why-medieval
22•areoform•3h ago•1 comments

Almond (YC X25) Is Hiring SWEs and MechEs

https://www.ycombinator.com/companies/almond-2/jobs
1•shawnpatel•3h ago

My productivity app is a never-ending .txt file (2020)

https://jeffhuang.com/productivity_text_file/
148•simonebrunozzi•5h ago•104 comments

The Walt Disney Company and OpenAI Partner on Sora

https://openai.com/index/disney-sora-agreement/
138•inesranzo•10h ago•409 comments

Auto-grading decade-old Hacker News discussions with hindsight

https://karpathy.bearblog.dev/auto-grade-hn/
567•__rito__•1d ago•251 comments

Prove It All Night: With no fame or fortune, what keeps a band onstage? (1999)

https://chicagoreader.com/news/prove-it-all-night/
56•NaOH•1w ago•21 comments

RFC 6677 DNS Transport over TCP – Implementation Requirements (2016)

https://www.ietf.org/rfc/rfc7766.txt
15•1vuio0pswjnm7•3h ago•11 comments

French supermarket's Christmas advert is worldwide hit (without AI) [video]

https://www.youtube.com/watch?v=Na9VmMNJvsA
199•gbugniot•11h ago•120 comments

Launch HN: BrowserBook (YC F24) – IDE for deterministic browser automation

60•cschlaepfer•9h ago•32 comments

Pdsink: USB Power Delivery Sink library for embedded devices

https://github.com/pdsink/pdsink
3•zdw•4d ago•0 comments

EFF launches Age Verification Hub

https://www.eff.org/press/releases/eff-launches-age-verification-hub-resource-against-misguided-laws
218•iamnothere•1d ago•203 comments

An Orbital House of Cards: Frequent Megaconstellation Close Conjunctions

https://arxiv.org/abs/2512.09643
76•rapnie•9h ago•43 comments

Going Through Snowden Documents, Part 1

https://libroot.org/posts/going-through-snowden-documents-part-1/
187•libroot•6h ago•109 comments

iPhone Typos? It's Not Just You – The iOS Keyboard Is Broken [video]

https://www.youtube.com/watch?v=hksVvXONrIo
454•walterbell•9h ago•318 comments

Christmas Tree Exec

https://en.wikipedia.org/wiki/Christmas_Tree_EXEC
7•jamesgill•5d ago•1 comments

You gotta push if you wanna pull

https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/
8•ingve•3d ago•4 comments

Show HN: Gotui – a modern Go terminal dashboard library

https://github.com/metaspartan/gotui
14•carsenk•3h ago•5 comments

Golang optimizations for high‑volume services

https://packagemain.tech/p/golang-optimizations-for-highvolume
40•der_gopher•3d ago•9 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?