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I ported Mac OS X to the Nintendo Wii

https://bryankeller.github.io/2026/04/08/porting-mac-os-x-nintendo-wii.html
712•blkhp19•4h ago•145 comments

Git commands I run before reading any code

https://piechowski.io/post/git-commands-before-reading-code/
1425•grepsedawk•10h ago•320 comments

Understanding the Kalman filter with a simple radar example

https://kalmanfilter.net
79•alex_be•2h ago•15 comments

Muse Spark: Scaling towards personal superintelligence

https://ai.meta.com/blog/introducing-muse-spark-msl/?_fb_noscript=1
155•chabons•3h ago•206 comments

I've been waiting over a month for Anthropic support to respond

https://nickvecchioni.github.io/thoughts/2026/04/08/anthropic-support-doesnt-exist/
49•nickvec•2h ago•22 comments

Show HN: Orange Juice – Small UX improvements that make HN easier to read

http://oj-hn.com/
31•latchkey•1h ago•29 comments

They're made out of meat (1991)

http://www.terrybisson.com/theyre-made-out-of-meat-2/
267•surprisetalk•8h ago•93 comments

ML promises to be profoundly weird

https://aphyr.com/posts/411-the-future-of-everything-is-lies-i-guess
244•pabs3•6h ago•274 comments

MegaTrain: Full Precision Training of 100B+ Parameter LLMs on a Single GPU

https://arxiv.org/abs/2604.05091
217•chrsw•7h ago•41 comments

Veracrypt project update

https://sourceforge.net/p/veracrypt/discussion/general/thread/9620d7a4b3/
973•super256•12h ago•360 comments

USB for Software Developers: An introduction to writing userspace USB drivers

https://werwolv.net/posts/usb_for_sw_devs/
13•WerWolv•24m ago•0 comments

Škoda DuoBell: A bicycle bell that penetrates noise-cancelling headphones

https://www.skoda-storyboard.com/en/skoda-world/skoda-duobell-a-bicycle-bell-that-outsmarts-even-...
406•ra•10h ago•479 comments

Understanding Traceroute

https://tech.stonecharioteer.com/posts/2026/traceroute/
25•stonecharioteer•2d ago•0 comments

Show HN: TUI-use: Let AI agents control interactive terminal programs

https://github.com/onesuper/tui-use
23•dreamsome•3h ago•23 comments

Microsoft Abruptly Terminates VeraCrypt Account, Halting Windows Updates

https://www.404media.co/microsoft-abruptly-terminates-veracrypt-account-halting-windows-updates/
313•donohoe•5h ago•118 comments

US cities are axing Flock Safety surveillance technology

https://www.cnet.com/home/security/when-flock-comes-to-town-why-cities-are-axing-the-controversia...
502•giuliomagnifico•7h ago•298 comments

Expanding Swift's IDE Support

https://swift.org/blog/expanding-swift-ide-support/
3•frizlab•25m ago•0 comments

Ask HN: Any interesting niche hobbies?

126•e-topy•2d ago•224 comments

Teardown of unreleased LG Rollable shows why rollable phones aren't a thing

https://arstechnica.com/gadgets/2026/04/teardown-of-unreleased-lg-rollable-shows-why-rollable-pho...
50•DamnInteresting•1d ago•22 comments

Show HN: Unicode Steganography

https://steganography.patrickvuscan.com
27•PatrickVuscan•1d ago•5 comments

One item purchased, ten emails

https://joshghent.com/online-shopping/
83•speckx•1h ago•62 comments

Show HN: Skrun – Deploy any agent skill as an API

https://github.com/skrun-dev/skrun
4•frizull•7h ago•3 comments

Audio Reactive LED Strips Are Diabolically Hard

https://scottlawsonbc.com/post/audio-led
154•surprisetalk•1d ago•50 comments

Show HN: Go-Bt: Minimalist Behavior Trees for Go

https://github.com/rvitorper/go-bt
41•rvitorper•5h ago•3 comments

Revision Demoparty 2026: Razor1911 [video]

https://www.youtube.com/watch?v=Lw4W9V57SKs&t=5716s
324•tetrisgm•14h ago•109 comments

We moved Railway's frontend off Next.js. Builds went from 10+ mins to under 2

https://blog.railway.com/p/moving-railways-frontend-off-nextjs
131•bundie•13h ago•112 comments

Science confirms torpedo [baseball] bat works as well as regular bat

https://news.wsu.edu/press-release/2026/04/02/science-confirms-torpedo-bat-works-as-well-as-regul...
7•Magi604•5d ago•3 comments

Union types in C# 15

https://devblogs.microsoft.com/dotnet/csharp-15-union-types/
130•0x00C0FFEE•3d ago•121 comments

Claude Managed Agents

https://claude.com/blog/claude-managed-agents
86•adocomplete•2h ago•42 comments

Virtual Mars Traverse: Every inch of Curiosity rover's path since 2012 landing

https://www.rovers.land/
33•bookofjoe•3d ago•11 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•10mo 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•10mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•10mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•10mo 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•10mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•10mo 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•10mo 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•10mo 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•10mo 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•10mo 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•10mo 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•10mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•10mo 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•10mo 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•10mo 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•10mo 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•10mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•10mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•10mo 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•10mo 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•10mo 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•10mo 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?