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Shopify is moving from React Native back to Swift and Kotlin

https://shopify.engineering/back-to-native
821•fnthawar2•12h ago•544 comments

Mexican student creates an acoustic fire extinguisher to put out fire in seconds

https://www.upsocl.com/en/16-year-old-mexican-student-creates-an-acoustic-fire-extinguisher-that-...
45•rguiscard•1h ago•11 comments

YuE2 · Frontier Music with Symbolic Planning

https://map-yue2.github.io/
51•sexy_seedbox•2h ago•45 comments

More questions about whether researchers can trust OpenAI with unpublished math

https://mathstodon.xyz/@andreasthom/117240535270608201
706•pred_•19h ago•647 comments

OpenAI Agents API

https://developers.openai.com/api/docs/guides/agents-api/overview
151•aquir•7h ago•97 comments

Thelio Mira AI Linux Workstation: 192 GB GPU Memory

https://system76.com/workstations/thelio-mira-ai
43•jonifico•3h ago•26 comments

Google will buy half the electricity of a nuclear power plant

https://www.bbc.com/news/articles/c8r6y4me2g6o
98•lukaspetersson•2h ago•70 comments

Don't let anyone take away your big box of cables

https://blog.jim-nielsen.com/2026/hands-off-my-cables/
346•Brajeshwar•11h ago•263 comments

Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra

https://cognition.com/blog/swe-2
361•seelos•11h ago•152 comments

The Deathray: A simple way for an untrusted site to freeze a Mac

https://auberon.xyz/blog/posts/deathray/
94•auberonedu•7h ago•60 comments

Technique for Manipulating Satellite Photos Now Reveals Ancient Images (2025)

https://spinoff.nasa.gov/Manipulating_Satellite_Photos_Now_Reveals_Ancient_Images
280•gumby•11h ago•44 comments

NTSB issues investigative update on B-767 runway excursion accident in Miami

https://www.ntsb.gov:443/news/press-releases/Pages/NR20260909.aspx
64•mckn1ght•5h ago•107 comments

Customizing my Compaq MX-11800 keyboard

https://blog.webb.page/WM-102
16•NetOpWibby•3d ago•3 comments

Music Theory for the 21st-Century Classroom

https://musictheory.pugetsound.edu/mt21c/MusicTheory.html
168•aanet•9h ago•80 comments

Neki – Sharded Postgres

https://planetscale.com/blog/introducing-neki
204•simon_weber•11h ago•113 comments

Forgejo <=16.0.3 Critical RCE

https://codeberg.org/forgejo/forgejo/src/branch/forgejo/release-notes-published/16.0.4.md
155•weierstass•10h ago•57 comments

Rust is tier-1 language at Microsoft

https://rustfoundation.org/media/guest-post-rust-is-tier-1-language-at-microsoft/
615•mmastrac•13h ago•353 comments

Hitachi launches CO2 heat pump water heaters with solar-friendly tariff controls

https://www.pv-magazine.com/2026/09/07/hitachi-launches-co2-heat-pump-water-heaters-with-solar-fr...
288•thelastgallon•1d ago•231 comments

Proof of Capture: Apple Reference Image, but open source and using steganography

https://merybenavente.me/blog/proof-of-capture
72•merybenavente•7h ago•51 comments

Recursion into madness

https://blog.coredump.cx/p/recursion-into-madness
42•surprisetalk•3d ago•11 comments

Setting up OpenCode with Ollama and sbx on Mac

https://tensorsandtokens.com/posts/opencode-ollama/
8•etoxin•2h ago•7 comments

iPhone Duo

https://www.apple.com/iphone-duo/
1416•thecosmicfrog•1d ago•2447 comments

What happens when a GPU writes memory

https://blog.doubleword.ai/what-happens-when-a-gpu-writes-memory
50•ibobev•2d ago•1 comments

Detecting and countering misuse of AI: September 2026

https://www.anthropic.com/threat-intelligence-report-september-2026
90•garo-pro•9h ago•163 comments

JEP 544: Ahead-of-Time Code Compilation

https://openjdk.org/jeps/544
81•Skinney•9h ago•27 comments

Douglas Hofstadter: Analogy as the Core of Cognition [video]

https://www.youtube.com/watch?v=n8m7lFQ3njk
148•tosh•4d ago•73 comments

Embedding a bitmap font in your HyperCard stack

https://www.leadedsolder.com/2026/09/08/hypercard-custom-fonts-in-resources.html
22•zdw•2d ago•1 comments

Silicon Valley is transforming the military-industrial complex? (2024)

https://costsofwar.watson.brown.edu/paper/how-big-tech-and-silicon-valley-are-transforming-milita...
157•paimapi•10h ago•310 comments

OpenAI’s Navier-Stokes release included a Lean 4 formal proof

https://www.johndcook.com/blog/2026/09/09/formal-method-revolution/
141•ibobev•5h ago•139 comments

Show HN: Vertumnus – printable posters of farmers' market produce seasonality

https://vertumnus.fyi
29•perspectivezoom•3d ago•14 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?