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What Being Ripped Off Taught Me

https://belief.horse/notes/what-being-ripped-off-taught-me/
110•doctorhandshake•1h ago•56 comments

Germany Doxes "UNKN," Head of RU Ransomware Gangs REvil, GandCrab

https://krebsonsecurity.com/2026/04/germany-doxes-unkn-head-of-ru-ransomware-gangs-revil-gandcrab/
7•Bender•32m ago•2 comments

Show HN: I built a tiny LLM to demystify how language models work

https://github.com/arman-bd/guppylm
682•armanified•14h ago•94 comments

France pulls last gold held in US for $15B gain

https://www.mining.com/france-pulls-last-gold-held-in-us-for-15b-gain/
351•teleforce•6h ago•200 comments

Microsoft hasn't had a coherent GUI strategy since Petzold

https://www.jsnover.com/blog/2026/03/13/microsoft-hasnt-had-a-coherent-gui-strategy-since-petzold/
631•naves•20h ago•416 comments

Gemma 4 on iPhone

https://apps.apple.com/nl/app/google-ai-edge-gallery/id6749645337
736•janandonly•19h ago•210 comments

An open-source 240-antenna array to bounce signals off the Moon

https://moonrf.com/
175•hillcrestenigma•11h ago•27 comments

The 1987 game “The Last Ninja” was 40 kilobytes

https://twitter.com/exQUIZitely/status/2040777977521398151
188•keepamovin•11h ago•124 comments

PostHog (YC W20) Is Hiring

1•james_impliu•1h ago

One ant for $220: The new frontier of wildlife trafficking

https://www.bbc.com/news/articles/cg4g44zv37qo
77•gmays•4d ago•3 comments

Show HN: Real-time AI (audio/video in, voice out) on an M3 Pro with Gemma E2B

https://github.com/fikrikarim/parlor
174•karimf•20h ago•13 comments

Drop, formerly Massdrop, ends most collaborations and rebrands under Corsair

https://drop.com/
79•stevebmark•10h ago•26 comments

LÖVE: 2D Game Framework for Lua

https://github.com/love2d/love
353•cl3misch•2d ago•174 comments

Signals, the push-pull based algorithm

https://willybrauner.com/journal/signal-the-push-pull-based-algorithm
92•mpweiher•2d ago•29 comments

Running Gemma 4 locally with LM Studio's new headless CLI and Claude Code

https://ai.georgeliu.com/p/running-google-gemma-4-locally-with
327•vbtechguy•21h ago•79 comments

Sheets Spreadsheets in Your Terminal

https://github.com/maaslalani/sheets
124•_____k•2d ago•30 comments

Show HN: Gemma Gem – AI model embedded in a browser – no API keys, no cloud

https://github.com/kessler/gemma-gem
111•ikessler•14h ago•18 comments

Show HN: I made a YouTube search form with advanced filters

https://playlists.at/youtube/search/
271•nevernothing•14h ago•170 comments

Case study: recovery of a corrupted 12 TB multi-device pool

https://github.com/kdave/btrfs-progs/issues/1107
95•salt4034•11h ago•43 comments

Music for Programming

https://musicforprogramming.net
257•merusame•20h ago•113 comments

Number in man page titles e.g. sleep(3)

https://lalitm.com/til-number-in-man-page-titles-e-g-sleep-3/
81•thunderbong•4h ago•35 comments

Why Switzerland has 25 Gbit internet and America doesn't

https://sschueller.github.io/posts/the-free-market-lie/
632•sschueller•19h ago•507 comments

Usenet Archives

https://usenetarchives.com
90•myth_drannon•12h ago•30 comments

Is Germany's gold safe in New York ?

https://www.dw.com/en/is-germanys-gold-safe-in-new-york/video-75766873
189•KnuthIsGod•3h ago•171 comments

Employers use your personal data to figure out the lowest salary you'll accept

https://www.marketwatch.com/story/employers-are-using-your-personal-data-to-figure-out-the-lowest...
328•thisislife2•13h ago•185 comments

Show HN: Modo – I built an open-source alternative to Kiro, Cursor, and Windsurf

https://github.com/mohshomis/modo
77•mohshomis•14h ago•17 comments

Tiny Corp's Exabox

https://twitter.com/__tinygrad__/status/2040944508402360592
41•macleginn•2h ago•7 comments

A tail-call interpreter in (nightly) Rust

https://www.mattkeeter.com/blog/2026-04-05-tailcall/
182•g0xA52A2A•23h ago•42 comments

Eight years of wanting, three months of building with AI

https://lalitm.com/post/building-syntaqlite-ai/
849•brilee•1d ago•268 comments

Caveman: Why use many token when few token do trick

https://github.com/JuliusBrussee/caveman
809•tosh•1d ago•344 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?