frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

GenCAD

https://gencad.github.io/
123•dagenix•4h ago•24 comments

I turned a $80 RK3562 Android tablet into a Debian Linux workstation

https://github.com/tech4bot/rk3562deb
264•tech4bot•13h ago•122 comments

Prolog Coding Horror

https://www.metalevel.at/prolog/horror
60•RohanAdwankar•5h ago•23 comments

Ask an Astronaut: 333 hours of Q&A footage with astronauts

https://askanastronaut.issinrealtime.org/
40•gaws•2d ago•5 comments

Two EA-18 fighter jets collide at Mountain Home airshow, pilots ejected safely

https://idahonews.com/news/local/two-f-18-fighter-jets-have-crashed-during-an-airshow-at-mountain...
103•ChrisArchitect•4h ago•86 comments

Show HN: Semble – Code search for agents that uses 98% fewer tokens than grep

https://github.com/MinishLab/semble
182•Bibabomas•10h ago•47 comments

Magical Realism: “Northern Exposure” 25 Years Later (2015)

https://www.rogerebert.com/streaming/magical-realism-nothern-exposure-25-years-later
75•walterbell•2d ago•29 comments

Cannibalistic attacks between gray seals leave telltale “corkscrew” injuries

https://www.science.org/content/article/scientists-id-corkscrew-killer-behind-gruesome-seal-deaths
39•gmays•3d ago•4 comments

Jank now has its own custom IR

https://jank-lang.org/blog/2026-05-08-optimization/
50•DASD•2d ago•4 comments

Mercurial, 20 years and counting: how are we still alive and kicking? [video]

https://fosdem.org/2026/schedule/event/AGWUVH-mercurial-aint-you-dead-yet/
164•ibobev•2d ago•154 comments

VoIP brings back old-fashioned pay phones to rural Vermont (2025)

https://spectrum.ieee.org/payphone-voip
115•bookofjoe•6h ago•36 comments

Design posters showcasing your country's electrical grid

https://github.com/open-energy-transition/grid2poster
61•lyoncy•3h ago•15 comments

The History of ThinkPad: From IBM’s Bento Box to Lenovo’s AI Workstations

https://www.jdhodges.com/blog/thinkpad-history/
57•zdw•4h ago•30 comments

CUDA Books

https://github.com/alternbits/awesome-cuda-books
131•dariubs•13h ago•26 comments

A Good Lemma Is Worth a Thousand Theorems

https://sites.math.rutgers.edu/~zeilberg/Opinion82.html
7•susam•1d ago•1 comments

I don't think AI will make your processes go faster

https://frederickvanbrabant.com/blog/2026-05-15-i-dont-think-ai-will-make-your-processes-go-faster/
499•TheEdonian•14h ago•355 comments

Hindenburg’s Smoking Room

https://www.airships.net/hindenburg-smoking-room/
159•crescit_eundo•3d ago•117 comments

Fabricked: Misconfiguring Infinity Fabric to Break AMD SEV-SNP

https://xca-attacks.github.io/fabricked/
26•negura•4h ago•15 comments

Prolog Basics Explained with Pokémon

https://unplannedobsolescence.com/blog/prolog-basics-pokemon/
209•birdculture•2d ago•34 comments

High-Entropy Alloy

https://en.wikipedia.org/wiki/High-entropy_alloy
111•leonidasrup•3d ago•23 comments

Trials on veterans suggest ibogaine could provide a new treatment for PTSD

https://www.bbc.com/future/article/20260514-how-hallucinogenic-ibogaine-helps-veterans-overcome-ptsd
82•bushwart•14h ago•89 comments

Tesla Solar Roof is on life support as it pivot to panels

https://electrek.co/2026/05/14/tesla-solar-roof-promise-vs-reality-pivot-panels/
172•celsoazevedo•22h ago•173 comments

The occasional ECONNRESET

https://movq.de/blog/postings/2026-05-05/1/POSTING-en.html
95•zdw•9h ago•21 comments

Colossus: The Forbin Project

https://en.wikipedia.org/wiki/Colossus:_The_Forbin_Project
216•doener•3d ago•84 comments

Mozilla to UK regulators: VPNs are essential privacy and security tools

https://blog.mozilla.org/netpolicy/2026/05/15/mozilla-to-uk-regulators-vpns-are-essential-privacy...
656•WithinReason•20h ago•271 comments

Schanuel's Conjecture and the Semantics of Triton's FPSan

https://cp4space.hatsya.com/2026/05/03/schanuels-conjecture-and-the-semantics-of-fpsan/
23•c1ccccc1•1d ago•3 comments

A nicer voltmeter clock

https://lcamtuf.substack.com/p/a-nicer-voltmeter-clock
312•surprisetalk•1d ago•42 comments

Native all the way, until you need text

https://justsitandgrin.im/posts/native-all-the-way-until-you-need-text/
391•dive•14h ago•262 comments

AI is a technology not a product

https://daringfireball.net/2026/05/ai_is_technology_not_a_product
341•ch_sm•13h ago•138 comments

Apple Silicon costs more than OpenRouter

https://www.williamangel.net/blog/2026/05/17/offline-llm-energy-use.html
300•datadrivenangel•14h ago•256 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•12mo 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•12mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•12mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•12mo 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•12mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•12mo 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•12mo 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•12mo 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•11mo 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•12mo 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•12mo 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•12mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•12mo 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•12mo 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•12mo 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•12mo 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•12mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•12mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•12mo 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•12mo 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•12mo 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•12mo 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?