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Coursera to combine with Udemy

https://investor.coursera.com/news/news-details/2025/Coursera-to-Combine-with-Udemy-to-Empower-th...
83•throwaway019254•1h ago•28 comments

Learning the oldest programming language (2024)

https://uncenter.dev/posts/learning-fortran/
9•lioeters•1h ago•3 comments

AI will make formal verification go mainstream

https://martin.kleppmann.com/2025/12/08/ai-formal-verification.html
695•evankhoury•17h ago•356 comments

Is Mozilla trying hard to kill itself?

https://infosec.press/brunomiguel/is-mozilla-trying-hard-to-kill-itself
483•pabs3•5h ago•418 comments

TLA+ Modeling Tips

http://muratbuffalo.blogspot.com/2025/12/tla-modeling-tips.html
60•birdculture•6h ago•14 comments

alpr.watch

https://alpr.watch/
826•theamk•21h ago•386 comments

No Graphics API

https://www.sebastianaaltonen.com/blog/no-graphics-api
710•ryandrake•19h ago•129 comments

Announcing the Beta release of ty

https://astral.sh/blog/ty
684•gavide•17h ago•130 comments

Modern SID chip substitutes [video]

https://www.youtube.com/watch?v=nooPmXxO6K0
27•vismit2000•3d ago•1 comments

No AI* Here – A Response to Mozilla's Next Chapter

https://www.waterfox.com/blog/no-ai-here-response-to-mozilla/
401•MrAlex94•16h ago•233 comments

AI's real superpower: consuming, not creating

https://msanroman.io/blog/ai-consumption-paradigm
87•firefoxd•6h ago•68 comments

Pricing Changes for GitHub Actions

https://resources.github.com/actions/2026-pricing-changes-for-github-actions/
708•kevin-david•21h ago•762 comments

GPT Image 1.5

https://openai.com/index/new-chatgpt-images-is-here/
472•charlierguo•20h ago•223 comments

Playing Santa changed Bob Rutan profoundly

https://www.esquire.com/lifestyle/a69597294/santaland-bob-rutan/
33•Lightbody•3d ago•10 comments

I ported JustHTML from Python to JavaScript with Codex CLI and GPT-5.2 in hours

https://simonwillison.net/2025/Dec/15/porting-justhtml/
197•pbowyer•15h ago•115 comments

Thin desires are eating life

https://www.joanwestenberg.com/thin-desires-are-eating-your-life/
564•mitchbob•1d ago•202 comments

Subsets (YC S23) is hiring engineers in Copenhagen, Denmark

https://www.workatastartup.com/companies/subsets
1•Oliverbrandt•7h ago

Annual Production of 1/72 (22mm) scale plastic soldiers, 1958-2025

https://plasticsoldierreview.com/ShowFeature.aspx?id=27
50•YeGoblynQueenne•3d ago•35 comments

40 percent of fMRI signals do not correspond to actual brain activity

https://www.tum.de/en/news-and-events/all-news/press-releases/details/40-percent-of-mri-signals-d...
466•geox•1d ago•181 comments

Mozilla appoints new CEO Anthony Enzor-Demeo

https://blog.mozilla.org/en/mozilla/leadership/mozillas-next-chapter-anthony-enzor-demeo-new-ceo/
541•recvonline•1d ago•814 comments

VA Linux: The biggest dotcom IPO

https://dfarq.homeip.net/va-linux-the-biggest-dotcom-ipo/
81•giuliomagnifico•6d ago•40 comments

Short-Circuiting Correlated Subqueries in SQLite

https://emschwartz.me/short-circuiting-correlated-subqueries-in-sqlite/
6•emschwartz•3h ago•0 comments

The Coupang data breach that hit two-thirds of South Korea

https://www.ft.com/content/df4042fa-3e56-410f-b905-4aed8fd434ac
3•zdw•4d ago•2 comments

Living Particle System

https://creative-art-points.vercel.app/
22•lovegrenoble•4d ago•0 comments

Show HN: I built a WebMIDI sequencer to control my hardware synths

https://www.simplychris.ai/droplets
30•simplychris•5d ago•13 comments

P: Formal Modeling and Analysis of Distributed (Event-Driven) Systems

https://github.com/p-org/P
21•Davidbrcz•6h ago•4 comments

Introduction to Software Development Tooling (2024)

https://bernsteinbear.com/isdt/
90•vismit2000•13h ago•13 comments

Japan to revise romanization rules for first time in 70 years

https://www.japantimes.co.jp/news/2025/08/21/japan/panel-hepburn-style-romanization/
227•rgovostes•1d ago•195 comments

Ask HN: Has anyone been able to renew their IEEE this month?

19•chrisaycock•5d ago•3 comments

Show HN: Titan – JavaScript-first framework that compiles into a Rust server

https://www.npmjs.com/package/@ezetgalaxy/titan
47•soham_byte•6d ago•25 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•7mo 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•7mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•6mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•7mo 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•6mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•7mo 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•7mo 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•6mo 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•6mo 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•7mo 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•7mo 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•6mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•6mo 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•6mo 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•6mo 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•6mo 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•6mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•6mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•6mo 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•6mo 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•6mo 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•6mo 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?