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Show HN: Wikihack – HackerTube, but for Wikipedia articles mentioned on HN

https://wikihack.netlify.app
103•aizk•3h ago•21 comments

Show HN: HackerBooks – HackerTube, but for books mentioned on HN

https://hackerbooks.org
1317•roansh•16h ago•223 comments

Postgres 19 is late because so many more bugs are being found now

http://rhaas.blogspot.com/2026/10/postgres-19-is-late-and-its-ais-fault.html
360•soheilpro•2d ago•235 comments

HackerTube: YouTube built from videos recommended by HN

https://karpathy.bearblog.dev/hacker-tube/
2518•karpathy•1d ago•559 comments

F/OSS Comics #13: BSD Unix, Part 3 – The Beginning of BSD Unix

https://fosscomics.com/posts/13.%20BSD%20Unix%20Part%203%20-%20The%20Beginning%20of%20BSD%20Unix/
100•joonehur•6h ago•11 comments

Ask HN: Which TV do you recommend for privacy?

335•LecroJS•13h ago•477 comments

Bones may release proteins that slow aging and extend life span

https://www.science.org/content/article/bones-may-release-proteins-slow-aging-and-extend-life-span
56•EA-3167•7h ago•5 comments

Mystery of 60-Second Fluctuations in Power Grids Solved

https://www.fz-juelich.de/en/news/archive/press-release/2026/mystery-of-60-second-fluctuations-in...
103•_Microft•1d ago•42 comments

From Charlemagne to the Kitchen Boy: Reading the Hamburg Rathaus

https://alsterrunde.com/from-charlemagne-to-the-kitchen-boy-reading-the-hamburg-rathaus/
8•mertbio•1h ago•0 comments

Trigger.dev customer environment variables exposed

https://trigger.dev/blog/security-incident-nov-2026
75•anurag•7h ago•28 comments

Nibnib: Image compression with extreme decompression speed

https://github.com/raphlinus/nibnib
136•raphlinus•3d ago•23 comments

Tips for more effective fuzz testing with AFL++

https://nullprogram.com/blog/2025/02/05/
114•luu•4d ago•17 comments

China's First Frontier AI Export Controls: Mofcom Announcement No. 48

https://labs.cloudsecurityalliance.org/research/csa-research-note-china-ai-export-controls-announ...
14•jonnybgood•1h ago•4 comments

Show HN: OmniDiff – Opensource, super fast, content aware Git difftool, in Rust

https://github.com/ivankovic/omnidiff
228•FabCH•19h ago•58 comments

Copper – A minimal low-level programming language with OOP and generics

https://tibleiz.net/copper/
161•bogdanoff_2•2d ago•91 comments

New 3D thermal invisibility cloak makes objects disappear from infrared cameras

https://www.sciencedaily.com/releases/2026/10/261025073051.htm
75•stevenalowe•3d ago•35 comments

The AI cost of JavaScript frameworks

https://nolanlawson.com/2026/10/28/the-ai-cost-of-javascript-frameworks/
359•luu•1d ago•281 comments

Proving and improving the Platonic Representation Hypothesis with JEPAs

https://arxiv.org/abs/2610.39302
134•Anon84•19h ago•68 comments

OccupySaaS

https://occupysaas.com/
234•misswaterfairy•8h ago•146 comments

Mathematics has changed. Let's act like it

https://terrytao.wordpress.com/2026/11/01/mathematics-has-changed-lets-act-like-it/
297•smilelamp•14h ago•319 comments

One-minute frequency disturbances from synchronization in power systems

https://www.nature.com/articles/s41560-026-02144-0
152•croes•1d ago•50 comments

Show HN: Point your camera at a landscape to learn about its geology

https://outcrop.rocks/
195•headsupernova•3d ago•43 comments

Lenovo's 'encrypted' fingerprint USB is just an unencrypted SD card in a case

https://www.reddit.com/r/technology/comments/1xl2pr3/lenovos_encrypted_fingerprint_usb_drive_is_j...
474•entryleveljobsc•18h ago•158 comments

Radiation Map of the World

https://radiaverse.com/
166•slater•4d ago•47 comments

Bidirectional charging during grid outages

https://www.jefftk.com/p/bidirectional-charging-during-grid-outages
100•luu•1d ago•147 comments

Show HN: I rebuilt my old canvas 3D library as a small WebGL 2 library – phoria2

https://kevs3d.co.uk/phoria2/
88•kevs3d•1d ago•17 comments

Keeping Up Appearances – The women taking over the funeral industry

https://lareviewofbooks.org/article/death-industry-mortuary-programs-women-andie-eisen-quarterly/
45•TMWNN•2d ago•26 comments

Domain hacks with unusual Unicode characters (2018)

https://shkspr.mobi/blog/2018/11/domain-hacks-with-unusual-unicode-characters/
77•n_plus_1_acc•21h ago•55 comments

Seoul Viosys begins production of rare-earth-free white light emitter

https://www.semiconductor-today.com/news_items/2026/oct/seoul-291026.shtml
171•gmays•16h ago•50 comments

An Italian farmer found some unknown seeds in his attic and planted them

https://www.smithsonianmag.com/science-nature/italian-farmer-found-unknown-seeds-attic-with-nothi...
802•ecares•1d ago•205 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?