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Astra can read and write weights to improve Qwen

https://rikiyat.github.io/blog/weight-space-programming/
2550•dbreunig•14h ago•784 comments

Nvidia – open-source auto-ontology

https://github.com/NVIDIA/auto-ontology
40•campervans•2h ago•4 comments

Show HN: Hacker Times, a New York Times-inspired version of Hacker News

https://hackertimes.ca/
241•polpenn•7h ago•74 comments

DiscImageStudio: burn visible artwork onto CDs, DVDs and Blu-ray discs

https://github.com/JiaFeiMiao-K-Cat/DiscImageStudio
181•bpierre•7h ago•45 comments

European RISC-V Industrial Computing Initiative

https://erici.eu
93•ymz5•1d ago•45 comments

Show HN: Subvocal – Talk to your computer without making noise

680•aarushyadav•15h ago•336 comments

Resisting Cognitive Surrender

https://knlb.dev/essays/surrender
152•knlb•2d ago•63 comments

Toit v2.0.0

https://toit.io/blog/toit-v2-0-0/
43•floitsch•2d ago•16 comments

Efficient algorithms, the Exponential Time Hypothesis, and losing the plot

https://www.argmin.net/p/galactus-the-devourer
34•sebg•2d ago•14 comments

US boy names that became girl names and vice versa

https://namedaisy.com/blog/boy-names-that-became-girl-names
394•xoobdev•16h ago•371 comments

If you love a website, back it up

https://blog.mistys-internet.website/post/2026/10/29/if-you-love-a-website-back-it-up/
535•ingve•19h ago•117 comments

Scaling Git at OpenAI

https://openai.com/index/scaling-git-at-openai/
213•makeramen•9h ago•121 comments

uBlock Origin filter to block autoplay videos in TechCrunch

https://cornfieldlabs.github.io/posts/ublock-stop-techcrunch-autoplay-video/post.html
59•cornfieldlabs•1h ago•14 comments

Self-Employed? Solopreneur? NIST Has a Cybersecurity Guide Just for You

https://www.nist.gov/news-events/news/2026/11/self-employed-solopreneur-nist-has-cybersecurity-gu...
216•tomrod•15h ago•56 comments

Show HN: ReBirth 338 in Browser

https://margeux.com/rb338.html
17•vegnus•2h ago•8 comments

Open-Source 5G Ran Platforms: A Dual Perspective on Performance and Capabilities

https://arxiv.org/abs/2608.25820
29•teleforce•6h ago•2 comments

Launch HN: Momentic (YC W24) – Agents that catch bugs by using your app

https://momentic.ai/
143•wuweiweiwu•16h ago•95 comments

Show HN: Warsaw in voxels – An interactive 3D map of the city centre

https://p.migdal.pl/warsaw-vibe-voxel/
266•stared•16h ago•42 comments

Shrinking NixOS RAM footprint and resource requirements to the bare minimum

https://lowendspirit.com/discussion/11543/shrinking-nixos-ram-footprint-and-resource-requirements...
62•birdculture•1d ago•6 comments

Ask HN: Who is hiring? (November 2026)

216•whoishiring•17h ago•172 comments

Egoless Mathematics in the AI Era

https://terrytao.wordpress.com/2026/11/02/egoless-mathematics-in-the-ai-era/
158•smilelamp•14h ago•114 comments

SLAC researchers find proof of altermagnetism, a new magnetic phase

https://www6.slac.stanford.edu/news/2026-10-29-slac-researchers-find-proof-altermagnetism-new-mag...
73•gmays•11h ago•8 comments

Optical Circuit Switch Technology Built on Low-Loss Silicon Photonics Platform

https://www.psiquantum.com/news-import/psiquantum-unveils-optical-circuit-switch-technology-built...
3•gmays•1d ago•0 comments

Show HN: I built a little browser game to practice Vim commands

https://hjkl.duy.run
27•dh1011•6h ago•24 comments

The SEC Should Block Anthropic's IPO to Protect the Public

https://www.techpolicy.press/the-sec-should-block-anthropics-ipo-to-protect-the-public/
337•cdrnsf•10h ago•249 comments

Cloudflare experiencing multiple active incidents

https://www.cloudflarestatus.com/
45•jp1016•4h ago•4 comments

Polyend releases the Tracker firmware source code

https://polyend.com/whats-up/tracker-the-biggest-update-yet/
127•austinallegro•15h ago•39 comments

Ubuntu still has not released patch for Linux 0day RCE in almost 3 weeks

https://freenode.net/article/ubuntu-lts-kernels-still-unfixed-for-critical-cve-2026-98432
485•majorchord•14h ago•137 comments

WTF Ubuntu?

https://chalmovsky.com/posts/wtf-ubuntu
1500•chalmovsky•18h ago•626 comments

V100 SXM2 pinout and NVLink reference

https://github.com/pigeon-labs-stack/v100-sxm2-reference
37•airhangerf15•10h ago•6 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?