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10th Gen Honda Civic Updates Are Signed with AOSP Test Keys

https://juniperspring.org/posts/honda-evil-valet/
133•librick•4h ago•19 comments

Noise infusion banned from statistical products published by Census Bureau

https://desfontain.es/blog/banning-noise.html
777•nl•15h ago•481 comments

GLM 5.2 Is Out

https://twitter.com/jietang/status/2065784751345287314
445•aloknnikhil•12h ago•243 comments

Every Frame Perfect

https://tonsky.me/blog/every-frame-perfect/
633•ravenical•17h ago•204 comments

The Redistribution of Housing Wealth Caused by Rent Control [pdf]

https://www.rhawa.org/file/secure/shs-the-impact-of-rent-control-in-st-paul.pdf
57•luu•2h ago•69 comments

FreeOberon – Open-Source, Cross-Platform, Free Pascal/Turbo Pascal-Like Language

https://github.com/kekcleader/FreeOberon
52•peter_d_sherman•2d ago•19 comments

Building a serial and VGA "everything console"

http://oldvcr.blogspot.com/2026/06/building-serial-and-vga-everything.html
10•classichasclass•2h ago•0 comments

Treating pancreatic tumours may have revealed cancer's master switch

https://economist.com/science-and-technology/2026/06/12/treating-pancreatic-tumours-may-have-reve...
330•andsoitis•15h ago•117 comments

Pyodide 314.0: Python packages can now publish WebAssembly wheels to PyPI

https://blog.pyodide.org/posts/314-release/
101•agriyakhetarpal•4d ago•23 comments

Python 3.14 garbage collection rigamarole

https://theconsensus.dev/p/2026/06/06/python-3-14-garbage-collection-rigamarole.html
23•eatonphil•1d ago•14 comments

Weave: Merging based on language structure and not lines

https://ataraxy-labs.github.io/weave/
11•rohanat•2h ago•2 comments

Software Architecture Guide

https://martinfowler.com/architecture/
5•laxmena•55m ago•0 comments

Codex for open source

https://openai.com/form/codex-for-oss/
202•EvgeniyZh•2d ago•67 comments

Apt Encounters of the Third Kind

https://igor-blue.github.io/2021/03/24/apt1.html
15•ogurechny•2h ago•3 comments

GameBoy Workboy

https://tcrf.net/Workboy
173•tosh•11h ago•59 comments

Amazon CEO's talks with U.S. officials triggered crackdown on Anthropic models

https://www.wsj.com/tech/ai/amazon-ceos-talks-with-u-s-officials-triggered-crackdown-on-anthropic...
613•ls612•12h ago•446 comments

ReactOS (FOSS "Windows") achieves 3D-accelerated Half-Life on real hardware

https://www.phoronix.com/news/ReactOS-Running-Half-Life
141•jeditobe•5h ago•25 comments

Free SQL→ER diagram tool, runs in the browser, nothing uploaded

https://sqltoerdiagram.com/
3•robhati•1h ago•1 comments

Running DOS on Behringers DDX3216 with a DIY x86-Bios from Scratch

https://chrisdevblog.com/2026/06/08/running-dos-on-behringers-ddx3216-using-a-diy-x86-bios/
84•rasz•10h ago•19 comments

A low-carbon computing platform from your retired phones

https://research.google/blog/a-low-carbon-computing-platform-from-your-retired-phones/
262•vikas-sharma•19h ago•141 comments

Appreciating Exif

https://brentfitzgerald.com/posts/appreciating-exif/
143•burnto•4d ago•30 comments

(Re//Verse 2026) Taxonomy and Deobfuscation of a Real World Binary Obfuscator [pdf]

https://github.com/AnalogCyberNuke/RE-Verse-2026-Slides/blob/main/Reverse26.pdf
3•not_a9•2d ago•1 comments

Human Routers of Machine Words

https://borretti.me/article/human-routers-of-machine-words
50•zx321•7h ago•25 comments

Police officer investigated for using AI to 'create evidence' in multiple cases

https://news.sky.com/story/derbyshire-police-officer-investigated-for-using-ai-to-create-evidence...
272•austinallegro•9h ago•130 comments

The Field Guide to CSS Grid Lanes

https://gridlanes.webkit.org/
12•ingve•3d ago•2 comments

RTX 5080 and RTX 3090 Setup: 80 Tok/s on Qwen 3.6 27B Q8

https://imil.net/blog/posts/2026/rtx-5080-+-rtx-3090-setup-80+-tok-s-on-qwen-3.6-27b-q8/
217•iMil•19h ago•74 comments

Quadratic funding democratizes allocation by rewarding projects w/ broad support

https://internetfreedom.torproject.org/funding-distribution/
5•Cider9986•2h ago•4 comments

The adder at the heart of Intel's 8087 floating-point chip

https://www.righto.com/2026/06/intel-8087-adder-reverse-engineered.html
102•pwg•12h ago•26 comments

4 things to know about the new sunscreen ingredient the FDA approved

https://www.npr.org/2026/06/13/nx-s1-5856385/sunscreen-skin-protection-bemotrizinol
68•mikhael•3h ago•24 comments

Ancient genome duplications laid the foundations of complex brains

https://www.ox.ac.uk/news/2026-06-09-ancient-genome-duplications-laid-the-foundations-of-complex-...
25•hhs•6h ago•1 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•1y 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•1y ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•1y ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•1y 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•1y ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•1y 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•1y 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•1y 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•1y 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•1y 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•1y 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•1y ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•1y 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•1y 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•1y 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•1y 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•1y ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•1y ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•1y 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•1y 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•1y 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•1y 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?