frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

Ntsc-rs – open-source video emulation of analog TV and VHS artifacts

https://ntsc.rs/
271•gregsadetsky•6h ago•60 comments

Harness engineering: Leveraging Codex in an agent-first world

https://openai.com/index/harness-engineering/
60•pramodbiligiri•1d ago•23 comments

Introducing Boron Buckyballs: Theory that B80 cages can’t be made is disproved

https://cen.acs.org/materials/nanomaterials/buckyballs-boron-buckminster-fullerene-nanomaterials/...
26•crescit_eundo•2d ago•1 comments

Moving beyond fork() + exec()

https://lwn.net/SubscriberLink/1076018/16f01bbbb8e0d1f0/
254•jwilk•11h ago•259 comments

Meta confirms 1000s of Instagram accounts were hacked by abusing its AI chatbot

https://this.weekinsecurity.com/meta-confirms-thousands-of-instagram-accounts-were-hacked-by-abus...
434•speckx•7h ago•152 comments

Zeroserve: A zero-config web server you can script with eBPF

https://su3.io/posts/introducing-zeroserve
194•losfair•11h ago•49 comments

Public Domain Image Archive

https://pdimagearchive.org/
12•davidbarker•1h ago•1 comments

Nvidia is proposing a beast of a CPU system for Windows PCs

https://twitter.com/lemire/status/2062880075117113739
232•tosh•13h ago•430 comments

Sem: New primitive for code understanding – not LSPs, but entities on top of Git

https://ataraxy-labs.github.io/sem/
55•rohanucla•5h ago•24 comments

Show HN: DomainTasker – avoid losing domains and surprise renewals

https://domaintasker.com/
9•si_164•1h ago•5 comments

Show HN: Keybench – Scriptable, extensible performance tool for key value stores

https://github.com/guycipher/keybench
8•alexpadula•2h ago•0 comments

You Can Run

https://magazine.atavist.com/2026/mccann-cocaine-fugitives
101•bryanrasmussen•10h ago•57 comments

Google to pay SpaceX $920M a month for compute capacity at xAI data centers

https://www.cnbc.com/2026/06/05/google-to-pay-spacex-920-million-a-month-for-xai-compute-capacity...
151•toephu2•1d ago•717 comments

Pokemon Emerald Ported to WebAssembly (100k FPS)

https://pokeemerald.com/
277•tripplyons•14h ago•78 comments

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk

https://uonr.github.io/poincake/
124•uonr•4d ago•23 comments

Unicode Fonts and Tools for X11

https://www.cl.cam.ac.uk/~mgk25/ucs-fonts.html
15•kristianp•2d ago•3 comments

Computex 2026: Are We Heading for the Agentic PC Era Yet?

https://www.eetimes.com/computex-2026-are-we-heading-for-the-agentic-pc-era-yet/
24•rbanffy•5h ago•27 comments

How Other Link Checkers Do Recursion

https://endler.dev/2026/how-other-link-checkers-recurse/
3•zdw•3d ago•0 comments

Ask HN: What was your "oh shit" moment with GenAI?

549•andrehacker•2d ago•947 comments

Home alone: Remote work, isolation, and mental health

https://www.science.org/doi/10.1126/science.aec7671
126•speckx•6h ago•117 comments

Benchmarks in Leipzig

https://arxiv.org/abs/2606.05818
124•root-parent•11h ago•44 comments

The new bibliomaniacs

https://engelsbergideas.com/notebook/the-new-bibliomaniacs/
67•RickJWagner•13h ago•57 comments

Pentagon raised threat of Israeli spying on U.S. to highest level, sources say

https://www.nbcnews.com/politics/national-security/pentagon-raised-threat-israeli-spying-us-highe...
409•MilnerRoute•7h ago•307 comments

Motorola effectively bricked its entire line of WiFi routers without explanation

https://mashable.com/tech/motorola-wifi-routers-stop-working-motosync-plus-app-down
65•thisislife2•11h ago•25 comments

Running Python code in a sandbox with MicroPython and WASM

https://simonwillison.net/2026/Jun/6/micropython-in-a-sandbox/
80•theanonymousone•11h ago•25 comments

Context Sculpting

https://perceptiontheory.bearblog.dev/context-sculpting/
9•perceptronblues•2h ago•2 comments

Summer of '85: DOSBOS is rejected by ANALOG Computing

https://www.goto10retro.com/p/summer-of-85-dosbos-is-rejected-by
50•ibobev•2d ago•11 comments

Trees to Flows and Back: Unifying Decision Trees and Diffusion Models

https://arxiv.org/abs/2605.00414
44•rsn243•12h ago•8 comments

Mbodi AI (YC P25) Is Hiring Founding Machine Learning Engineer (Robotics)

https://www.ycombinator.com/companies/mbodi-ai/jobs/WYAcNkX-founding-machine-learning-engineer
1•chitianhao•13h ago

How LLMs work

https://www.0xkato.xyz/how-llms-actually-work/
848•0xkato•3d ago•236 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?