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Category Theory Illustrated – Orders

https://abuseofnotation.github.io/category-theory-illustrated/04_order/
43•boris_m•2h ago•9 comments

Amiga Graphics

https://amiga.lychesis.net/
35•sph•2h ago•1 comments

Claude Design

https://www.anthropic.com/news/claude-design-anthropic-labs
1027•meetpateltech•17h ago•670 comments

Show HN: I made a calculator that works over disjoint sets of intervals

https://victorpoughon.github.io/interval-calculator/
139•fouronnes3•7h ago•22 comments

The simple geometry behind any road

https://sandboxspirit.com/blog/simple-geometry-of-roads/
19•azhenley•2d ago•3 comments

Measuring Claude 4.7's tokenizer costs

https://www.claudecodecamp.com/p/i-measured-claude-4-7-s-new-tokenizer-here-s-what-it-costs-you
601•aray07•17h ago•428 comments

Towards trust in Emacs

https://eshelyaron.com/posts/2026-04-15-towards-trust-in-emacs.html
98•eshelyaron•2d ago•11 comments

All 12 moonwalkers had "lunar hay fever" from dust smelling like gunpowder (2018)

https://www.esa.int/Science_Exploration/Human_and_Robotic_Exploration/The_toxic_side_of_the_Moon
324•cybermango•14h ago•190 comments

Spending 3 months coding by hand

https://miguelconner.substack.com/p/im-coding-by-hand
201•evakhoury•16h ago•200 comments

Rewriting Every Syscall in a Linux Binary at Load Time

https://amitlimaye1.substack.com/p/rewriting-every-syscall-in-a-linux
38•riteshnoronha16•4d ago•13 comments

A simplified model of Fil-C

https://www.corsix.org/content/simplified-model-of-fil-c
172•aw1621107•11h ago•93 comments

Are the costs of AI agents also rising exponentially? (2025)

https://www.tobyord.com/writing/hourly-costs-for-ai-agents
196•louiereederson•2d ago•49 comments

It is incorrect to "normalize" // in HTTP URL paths

https://runxiyu.org/comp/doubleslash/
22•pabs3•3h ago•10 comments

Brunost: The Nynorsk Programming Language

https://lindbakk.com/blog/introducing-brunost
56•atomfinger•4d ago•23 comments

Show HN: Smol machines – subsecond coldstart, portable virtual machines

https://github.com/smol-machines/smolvm
326•binsquare•15h ago•99 comments

Slop Cop

https://awnist.com/slop-cop
173•ericHosick•17h ago•102 comments

Show HN: PanicLock – Close your MacBook lid disable TouchID –> password unlock

https://github.com/paniclock/paniclock/
186•seanieb•16h ago•78 comments

"cat readme.txt" is not safe if you use iTerm2

https://blog.calif.io/p/mad-bugs-even-cat-readmetxt-is-not
176•arkadiyt•14h ago•93 comments

Hyperscalers have already outspent most famous US megaprojects

https://twitter.com/finmoorhouse/status/2044933442236776794
188•nowflux•16h ago•150 comments

Middle schooler finds coin from Troy in Berlin

https://www.thehistoryblog.com/archives/75848
229•speckx•18h ago•103 comments

NASA Force

https://nasaforce.gov/
268•LorenDB•17h ago•266 comments

Landmark ancient-genome study shows surprise acceleration of human evolution

https://www.nature.com/articles/d41586-026-01204-5
76•unsuspecting•10h ago•61 comments

Making Wax Sealed Letters at Scale

https://waxletter.com/
16•hjconstas•2d ago•12 comments

NIST gives up enriching most CVEs

https://risky.biz/risky-bulletin-nist-gives-up-enriching-most-cves/
198•mooreds•17h ago•51 comments

Casus Belli Engineering

https://marcosmagueta.com/blog/casus-belli-engineering/
36•b-man•7h ago•7 comments

The Unix executable as a Smalltalk method (2025) [video]

https://www.youtube.com/watch?v=sZjPQ7vtLNA
52•surprisetalk•1d ago•3 comments

Introducing: ShaderPad

https://rileyjshaw.com/blog/introducing-shaderpad/
91•evakhoury•2d ago•18 comments

Arc Prize Foundation (YC W26) Is Hiring a Platform Engineer for ARC-AGI-4

https://www.ycombinator.com/companies/arc-prize-foundation/jobs/AKZRZDN-platform-engineer-benchma...
1•gkamradt_•11h ago

The GNU libc atanh is correctly rounded

https://inria.hal.science/hal-05591661
90•matt_d•3d ago•20 comments

Ban the sale of precise geolocation

https://www.lawfaremedia.org/article/it-is-time-to-ban-the-sale-of-precise-geolocation
693•hn_acker•18h ago•176 comments
Open in hackernews

Building an agentic image generator that improves itself

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