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GrapheneOS has been ported to Android 17

https://discuss.grapheneos.org/d/36469-grapheneos-has-been-ported-to-android-17-and-official-rele...
656•Cider9986•10h ago•288 comments

Running local models is good now

https://vickiboykis.com/2026/06/15/running-local-models-is-good-now/
1222•jfb•16h ago•487 comments

Humiliating IIS servers for fun and jail time

https://mll.sh/humiliating-iis-servers-for-fun-and-jail-time/
207•denysvitali•8h ago•49 comments

Wolfram Language and Mathematica Version 15, AI Assistant, Symbolic Music, More

https://writings.stephenwolfram.com/2026/06/launching-version-15-of-wolfram-language-mathematica-...
147•alok-g•7h ago•64 comments

TIL: You can make HTTP requests without curl using Bash /dev/TCP

https://mareksuppa.com/til/bash-dev-tcp-http-without-curl/
377•mrshu•14h ago•173 comments

Calvin and Hobbes and the price of integrity

https://therepublicofletters.substack.com/p/calvin-and-hobbes-and-the-price-of
382•pseudolus•15h ago•168 comments

GPT‑NL: a sovereign language model for the Netherlands

https://www.tno.nl/en/digital/artificial-intelligence/gpt-nl/
190•root-parent•13h ago•173 comments

Has AI already killed self-help nonfiction books?

https://tim.blog/2026/06/12/has-ai-already-killed-nonfiction/
260•imakwana•14h ago•270 comments

Subterranean fungi networks more than 100 quadrillion km in length

https://www.theguardian.com/science/2026/jun/11/arbuscular-mycorrhizal-fungi-plant-life-climate-g...
27•tosh•5d ago•2 comments

Stop Using JWTs

https://gist.github.com/samsch/0d1f3d3b4745d778f78b230cf6061452
348•dzonga•14h ago•200 comments

Stop Killing Games fails to secure EU law despite 1.3M signatures

https://www.dexerto.com/gaming/stop-killing-games-fails-to-secure-eu-law-despite-1-3m-signatures-...
157•slymax•5h ago•49 comments

But yak shaving is fun (2019)

https://parksb.github.io/en/article/32.html
247•parksb•16h ago•71 comments

Chameleon Ultra: a flashdrive sized NFC toolkit

https://github.com/RfidResearchGroup/ChameleonUltra
9•elisaado•2d ago•0 comments

SpaceX to buy Cursor for $60B

https://www.reuters.com/legal/transactional/spacex-buy-anysphere-60-billion-2026-06-16/
981•itsmarcelg•20h ago•1480 comments

The Amphibious Villagers of Indonesia

https://www.economist.com/interactive/1843/2026/06/12/the-amphibious-villagers-of-indonesia
19•haritha-j•2d ago•4 comments

A brief tour of the PDP-11, the most influential minicomputer of all time (2022)

https://arstechnica.com/gadgets/2022/03/a-brief-tour-of-the-pdp-11-the-most-influential-minicompu...
69•jensgk•2d ago•28 comments

Working in Glass

https://www.asimov.press/p/glass
21•bookofjoe•5d ago•1 comments

10Gb/s Ethernet: switching to a Broadcom SFP+ module

https://www.gilesthomas.com/2026/06/10g-ethernet-switching-to-broadcom-sfp-plus
127•gpjt•13h ago•120 comments

A Nipkow Disk Mechanical TV Simulator

https://analogtv.net/mechanical-lab
39•ambanmba•2d ago•5 comments

NetNewsWire Status

https://inessential.com/2026/06/15/netnewswire-status.html
45•droidjj•2h ago•6 comments

Show HN: cuTile Rust: Safe, data-race-free GPU kernels in Rust

https://github.com/nvlabs/cutile-rs
63•melihelibol•10h ago•12 comments

Qwen-Robot Suite: A Foundation Model Suite for Physical World Intelligence

https://qwen.ai/blog?id=qwen-robotsuite
162•ilreb•17h ago•27 comments

All about the IBM 1130 Computing System

http://ibm1130.org/
29•jruohonen•2d ago•11 comments

Semiclassical Gravity Efficiently Solves NP-Complete Problems

https://arxiv.org/abs/2606.14806
9•ascarshen•3h ago•3 comments

Apple's weird anti-nausea dots cured my car sickness

https://www.theverge.com/tech/942854/apple-vehicle-motion-cues-review-really-work
710•neilfrndes•14h ago•215 comments

Mechanical Watch (2022)

https://ciechanow.ski/mechanical-watch/
676•razin•19h ago•115 comments

Is Meta destroying its engineering organization?

https://newsletter.pragmaticengineer.com/p/why-is-meta-destroying-its-engineering
546•throwarayes•14h ago•480 comments

Frood, an Alpine Initramfs NAS (2024)

https://words.filippo.io/frood/
46•ethanpil•10h ago•12 comments

Apple is about to make Hide My Email useless

https://arseniyshestakov.com/2026/06/16/apple-is-about-to-make-hide-my-email-useless/
470•SXX•12h ago•288 comments

A backdoor in a LinkedIn job offer

https://roman.pt/posts/linkedin-backdoor/
1551•lwhsiao•1d ago•295 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•1y 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•1y ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•1y ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•1y 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•1y ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•1y 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•1y 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•1y 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•1y 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•1y 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•1y 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•1y ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•1y 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•1y 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•1y 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•1y 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•1y ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•1y ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•1y 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•1y 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•1y 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•1y 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?