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Show HN: To Honor Sir Patrick Stewart, Enjoy the TNG Episode Guessing Game

https://tng.episodle.com/
145•francisofascii•6h ago•42 comments

My favourite PowerMac is a Nintendo Wii

https://virtuallyfun.com/2026/10/29/my-favourite-powermac-is-a-nintendo-wii/
275•DHowett•12h ago•77 comments

Tell HN: Scribd Breached

113•x______________•3h ago•36 comments

Cloudflare Turnstile solver library (no headless browser required)

https://github.com/chris124567/cfsolve
148•costco•2d ago•42 comments

Northflank Breached

https://status.northflank.com
405•js4ever•14h ago•299 comments

OpenAI raises less than half of $30B target

https://www.wsj.com/tech/ai/openai-raises-less-than-half-of-30-billion-target-in-latest-round-91a...
114•timr•2h ago•66 comments

The $6.3B Binance hack was pulled off in just 20 minutes

https://www.wired.com/story/the-dollar63-billion-binance-hack-was-pulled-off-in-just-20-minutes/
392•domhudson•17h ago•267 comments

Breaking the open web won't stop the bad bots

https://www.techpolicy.press/breaking-the-open-web-wont-stop-the-bad-bots/
229•raybb•3d ago•104 comments

Show HN: A working Nintendo in ~1GB of Qwen weights

https://github.com/dbreunig/nesformer
227•dbreunig•13h ago•118 comments

The oldest ice disappears and the Stone Age emerges from it

https://www.sciencenorway.no/archaeology-climate-culture/the-oldest-ice-is-disappearing-the-stone...
123•dxs•10h ago•51 comments

Longitudinal Changes InWearable-Captured PhysiologyBefore Sudden Cardiac Death

https://www.jacc.org/doi/epdf/10.1016/j.jaccas.2026.110397
11•brandonb•2d ago•4 comments

sanstun: A sans-IO, parallel-friendly WireGuard implementation in Rust

https://www.firezone.dev/blog/introducing-sanstun
100•wh33zle•8h ago•17 comments

Infinite Mac: BeOS

https://blog.persistent.info/2026/10/infinite-mac-beos.html
136•ecliptik•10h ago•56 comments

Florilegium: Procedural Flowers in LaTeX

https://github.com/kevinraymond/florilegium
241•nanna•14h ago•44 comments

Flock camera searches fell 95% after a dispatcher's misconduct was caught

https://www.wkyc.com/article/news/investigations/flock-camera-searches-fall-95-percent-highland-h...
66•MilnerRoute•3h ago•6 comments

Brief History of PDP Computers

https://entropicthoughts.com/history-of-pdp-computers
6•ibobev•1d ago•0 comments

The federated code forge

https://tangled.org/blog/forge/
259•zlliang•14h ago•82 comments

Jules Verne's Lost Novel

https://blue-continuum.com/verne-paris
96•dnetesn•10h ago•19 comments

Double Buffering with Cloudflare Queues

https://bellone.com/technical/double-buffering-with-cloudflare-queues
19•b_llc•2d ago•2 comments

Backdoor in Claude Code for VS Code extension on the Cursor Marketplace

https://phorion.io/blog/offical-claude-code-vsx-compromise/
858•_chall•22h ago•512 comments

Azure's Weakest Link – Five Full Cross-Tenant Compromises

https://www.binarysecurity.no/posts/2026/10/one-root-case
291•swq115•19h ago•56 comments

Through Captain Jean-Luc Picard, Patrick Stewart taught us the measure of a man

https://www.bostonglobe.com/2026/10/29/metro/patrick-stewart-picard-star-trek-the-next-generation/
272•apress•9h ago•148 comments

Cisco gives engineer unlimited AI tokens to rewrite legacy code

https://fortune.com/2026/10/30/cisco-president-jeetu-patel-gen-z-27-year-old-unlimited-ai-tokens-...
144•taubek•15h ago•184 comments

Turning a solar power system into its own backup

https://arstechnica.com/science/2026/10/turning-a-solar-power-system-into-its-own-backup/
44•PaulHoule•1d ago•15 comments

Trapped in the Technologist Factory

https://ideolalia.com/essays/trapped-in-the-technologist-factory.html
21•luu•2d ago•8 comments

Building an AI-native engineering org

https://twitter.com/sgondala2/status/2115832070274723875
132•sgondala_ycapp•1d ago•168 comments

Tree-mounted machines connect to web app to let users knock on wood remotely

https://www.designboom.com/technology/tree-mounted-machines-web-app-users-knock-on-wood-remotely/
80•surprisetalk•3d ago•33 comments

Sleep framework: A new way for LLMs to retain knowledge in continual learning

https://research.google/blog/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-contin...
200•acossta•2d ago•22 comments

AI isn't replacing SREs, it's deskilling them

https://newsletter.signoz.io/p/ai-isnt-replacing-sres-its-deskilling
550•dorianniemiec•14h ago•410 comments

Wonderful Weather: Floods and Foreboding in 17th-Century Britain

https://publicdomainreview.org/essay/wonderful-weather/
16•Thevet•2d ago•0 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?