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Run Qwen 3.8 Flash Next (125B) on consumer hardware (RTX 4090) at 100T/s

https://github.com/Niko1221/Strata
694•snehesht•17h ago•320 comments

In the wake of closure, a digital archive of animated materials appears online

https://filmstories.co.uk/news/tippett-studios-in-the-wake-of-its-closure-a-digital-archive-of-an...
92•rdmuser•8h ago•10 comments

Nearly 200 people under observation after Irkutsk lab worker dies from plague

https://www.themoscowtimes.com/2026/10/02/nearly-200-people-under-observation-after-irkutsk-lab-w...
159•ericmay•3h ago•115 comments

A 40ms Go garbage collector pause caused by swap

https://frn.sh/go-gc/
40•shellpipe•4h ago•11 comments

Infidel goes wild

https://blog.zarfhome.com/2026/10/infidel-goes-wild
111•tobr•1d ago•16 comments

ArtCraft Apps – open-source Adobe compatible suite written in Rust

https://getartcraft.com/apps
76•aghuang•6h ago•76 comments

Powerless F1 drivers frustrated by Bahrain F1 software glitch

https://www.motorsport.com/f1/news/horrible-totally-unacceptable-powerless-f1-drivers-frustrated-...
162•llm_nerd•4h ago•94 comments

A browser-native classic Visual Basic VB6 IDE

https://wieslawsoltes.github.io/VB6/
150•wiso•11h ago•56 comments

The Tao of Backup

http://www.taobackup.com/index.html
90•vntok•2d ago•19 comments

Turn off Apple Intelligence on macOS 27 and get its disk space back

https://github.com/omlahore/RemoveMacAI
484•privacyisntdead•10h ago•302 comments

Gods in the Classroom: Religion and Education in First Millennium BCE Babylonia

https://www.cambridge.org/core/journals/iraq/article/gods-in-the-classroom-religion-and-education...
9•pseudolus•3d ago•0 comments

Improper redaction reveals Google Data Center water and electricity usage

https://www.1011now.com/2026/09/30/more-questions-than-answers-about-lincolns-google-data-center-...
334•sensanaty•10h ago•447 comments

Tell HN: Bob Cringely has died

850•paveworld•1d ago•181 comments

Self-hosted HTTP tunnels with SSH and Nginx

https://vincent.bernat.ch/en/blog/2026-http-over-ssh
108•renehsz•7h ago•30 comments

Automating my 35mm film scanning pipeline

https://shannadige.com/blog/darkroom/
63•shannadige•1d ago•44 comments

Fixed Points and Strike Mandates

https://pvk.ca/Blog/2012/02/19/fixed-points-and-strike-mandates/
10•luu•4d ago•1 comments

Watson Jr. memo about CDC 6600 (1963)

https://www.computerhistory.org/revolution/supercomputers/10/33/62
34•mooreds•1d ago•18 comments

'Neanderthals Among Us' review

https://www.historytoday.com/archive/review/neanderthals-among-us-peter-sahlins-review
64•pepys•1d ago•53 comments

Xray-core concealed a certificate verification bypass vulnerability

https://github.com/net4people/bbs/issues/672
71•timbill•12h ago•9 comments

Interview with Chicken Scheme Maintainer Sjamaan/Peter Bex

https://alexalejandre.com/interviews/peter-bex/
27•veqq•2d ago•5 comments

Demystifying Tufte's data-ink ratio

https://tuftesrazor.scienceux.org/
27•s4074433•2d ago•9 comments

Homa: The end of TCP for AI clusters [video]

https://www.youtube.com/watch?v=eZ8WWZzoaR0
66•signa11•10h ago•30 comments

Show HN: Glashütte Trash Clock – A 30-minute pendulum clock made from trash

https://niklasroy.com/gtc/
181•r0r0•2d ago•26 comments

All I wanted was a custom domain email

https://jacobg.co/emails-at-jacobg-co/
48•jgx0•12h ago•68 comments

How to scale intent, quality, and artistry with AI [video]

https://www.youtube.com/watch?v=GLvFTMtw4Jk
72•simonjgreen•21h ago•22 comments

What is going on with ceiling fans

https://mcmansionhell.com/post/829127919552151552/what-is-going-on-with-ceiling-fans
267•colinprince•4d ago•245 comments

Bill Draper has died

https://www.nytimes.com/2026/09/30/technology/william-draper-dead.html
107•bookofjoe•17h ago•31 comments

Show HN: AI search for every photo and every frame of video on macOS

https://github.com/allenv0/SCM
149•allenleee•20h ago•67 comments

Results from the ASIC puzzle

https://blog.janestreet.com/asic-puzzle-results/
82•eru•2d ago•41 comments

Blindsight (Watts Novel)

https://en.wikipedia.org/wiki/Blindsight_(Watts_novel)
72•mooreds•13h ago•71 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?