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Self Propagating NPM Malware Compromises over 40 Packages

https://www.stepsecurity.io/blog/ctrl-tinycolor-and-40-npm-packages-compromised
330•jamesberthoty•3h ago•243 comments

CIA Freedom of Information Act Electronic Reading Room

https://www.cia.gov/readingroom
53•bookofjoe•1h ago•4 comments

FBI couldn't get my husband to decrypt his Tor node so he was jailed for 3 years

https://old.reddit.com/r/TOR/comments/1ni5drm/the_fbi_couldnt_get_my_husband_to_decrypt_his_tor/
713•heavyset_go•2h ago•202 comments

Fifty Things you can do with a Software Defined Radio

https://blinry.org/50-things-with-sdr/
9•mihau•16m ago•1 comments

Implicit Ode Solvers Are Not Universally More Robust Than Explicit Ode Solvers

https://www.stochasticlifestyle.com/implicit-ode-solvers-are-not-universally-more-robust-than-exp...
21•cbolton•1h ago•0 comments

Mother of All Demos

https://wordspike.com/s/5ip0xneiTsc
9•thekuanysh•33m ago•2 comments

Robert Redford Has Died

https://www.nytimes.com/2025/09/16/movies/robert-redford-dead.html
229•uptown•2h ago•63 comments

Hosting a website on a disposable vape

https://bogdanthegeek.github.io/blog/projects/vapeserver/
1256•BogdanTheGeek•20h ago•431 comments

Migrating to React Native's New Architecture

https://shopify.engineering/react-native-new-architecture
56•vidyesh•3d ago•35 comments

Generative AI is hollowing out entry-level jobs, study finds

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5425555
47•zeuch•1h ago•44 comments

60 years after Gemini, newly processed images reveal details

https://arstechnica.com/space/2025/09/60-years-after-gemini-newly-processed-images-reveal-incredi...
151•sohkamyung•3d ago•38 comments

"Your" vs. "My" in user interfaces

https://adamsilver.io/blog/your-vs-my-in-user-interfaces/
338•Twixes•11h ago•157 comments

Scientists uncover extreme life inside the Arctic ice

https://news.stanford.edu/stories/2025/09/extreme-life-arctic-ice-diatoms-ecological-discovery
34•hhs•3d ago•4 comments

Teen Safety, Freedom, and Privacy

https://openai.com/index/teen-safety-freedom-and-privacy
12•meetpateltech•1h ago•2 comments

Learn x86-64 assembly by writing a GUI from scratch (2023)

https://gaultier.github.io/blog/x11_x64.html
183•ibobev•4d ago•21 comments

React is winning by default and slowing innovation

https://www.lorenstew.art/blog/react-won-by-default/
612•dbushell•21h ago•690 comments

William Gibson Reads Neuromancer (2004)

http://bearcave.com/bookrev/neuromancer/neuromancer_audio.html
278•exvi•17h ago•77 comments

Trucker built a scale model of NYC over 21 years

https://gothamist.com/arts-entertainment/this-trucker-built-a-scale-model-of-nyc-over-21-years-it...
42•speckx•1h ago•5 comments

macOS Tahoe

https://www.apple.com/os/macos/
540•Wingy•21h ago•781 comments

When the job search becomes impossible

https://www.jeffwofford.com/wp/?p=2240
43•pertinhower•1h ago•35 comments

Wanted to spy on my dog, ended up spying on TP-Link

https://kennedn.com/blog/posts/tapo/
499•kennedn•22h ago•159 comments

The Mythical Creatures of London

https://londonist.com/london/history/the-mythical-creatures-of-london
29•zeristor•3d ago•10 comments

WordNumbers: Counting letters of number names, alphabetized and concatenated

http://conway.rutgers.edu/~ccshan/wiki/blog/posts/WordNumbers1/
6•lupire•2d ago•1 comments

Just Use HTML

https://gomakethings.com/just-use-html/
95•speckx•2h ago•60 comments

I feel Apple has lost its alignment with me and other long-time customers

https://morrick.me/archives/10137
459•mgrayson•14h ago•438 comments

After escaping Russian energy dependence, Europe is locking itself in to US LNG

https://davekeating.substack.com/p/after-escaping-russian-energy-dependence
61•hunglee2•54m ago•73 comments

PayPal to support Ethereum and Bitcoin

https://newsroom.paypal-corp.com/2025-09-15-PayPal-Ushers-in-a-New-Era-of-Peer-to-Peer-Payments,-...
471•DocFeind•1d ago•359 comments

How big a solar battery do I need to store all my home's electricity?

https://shkspr.mobi/blog/2025/09/how-big-a-solar-battery-do-i-need-to-store-all-my-homes-electric...
369•FromTheArchives•1d ago•445 comments

GPT-5-Codex

https://openai.com/index/introducing-upgrades-to-codex/
358•meetpateltech•21h ago•112 comments

Addendum to GPT-5 system card: GPT-5-Codex

https://openai.com/index/gpt-5-system-card-addendum-gpt-5-codex/
241•wertyk•20h ago•137 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•3mo 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•3mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•3mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•3mo 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•3mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•3mo 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•3mo 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•3mo 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•3mo 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•3mo 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•3mo 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•3mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•3mo 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•3mo 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•3mo 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•3mo 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•3mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•3mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•3mo 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•3mo 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•3mo 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•3mo 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?