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Fun things to do with your VM/370 CE machine – Fun with big computers

https://rbanffy.github.io/fun-with-big-computers/fun-with-vm370/
20•rbanffy•56m ago•2 comments

Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

https://arxiv.org/abs/2610.14162
96•theanonymousone•3h ago•13 comments

Unlocking any car from X brand in most of the world

https://shubs.io/unlocking-any-car-from-x-brand-in-most-of-the-world/
392•infosecau•10h ago•158 comments

KetchUp – Open-source SketchUp alternative built with Rust and WebGPU

https://ketchup3d.github.io/app/
521•dcoulmbe•12h ago•150 comments

I'm not convinced the AI bubble exists

https://matteoraso.github.io/im-not-convinced-the-ai-bubble-exists.html#im-not-convinced-the-ai-b...
317•matteoraso•11h ago•543 comments

Psalm 7 release: PHP security&static analysis software

https://psalm.dev/articles/psalm-7
29•danogentili•1d ago•12 comments

Is Opus 5.5 nerfed? Thinking patterns changed on November 3

https://twitter.com/shanemelaugh/status/2119192075505893695
197•rzk•4h ago•126 comments

Declarative Dragging

https://declarative-dragging.github.io/
566•smusamashah•4d ago•74 comments

Chimera Vocal Synth

https://chimera-vocal-synth.vercel.app/
238•nmstoker•12h ago•35 comments

The French Cake Cooked on a Spit (2018) [video]

https://www.youtube.com/watch?v=havcACdx0Y0
9•NaOH•1d ago•4 comments

Outlook.com is rejecting email from domains without DMARC

https://mailroute.net/blog/outlook-rejecting-email-without-dmarc
420•xmddmx•15h ago•297 comments

Dux: Free, open-source Wayland desktop shell with file manager and theming

https://duxlabs.dev/
296•indigodaddy•15h ago•97 comments

Show HN: Flide: Make Jev-like decision models up to 9.5x faster

https://github.com/OmniJev/Flide
38•unikcc•6h ago•10 comments

Quasi-Logarithmic Kitchen Timer

https://blog.coredump.cx/p/quasi-logarithmic-kitchen-timer
35•surprisetalk•4d ago•9 comments

Ask HN: What are you working on? (November 2026)

221•david927•13h ago•739 comments

ChatGPT Desktop forwards your SSH agent to remote machines

33•DenGorbachev•2h ago•9 comments

Nvidia CEO Jensen Huang's letter to staff about affair

https://nvidianews.nvidia.com/news/a-message-to-our-company
702•karimf•12h ago•773 comments

A Critique of GPUI

https://blog.zortax.de/posts/a-critique-of-gpui
112•ByteAtATime•7h ago•68 comments

Nvidia was in 1 in 11 startup rounds over $100M last year

https://datahyena.com/research/a-chipmaker-was-in-one-of-every-eleven-100m-rounds/
3•ghostfoxgod•2d ago•0 comments

Ur-Nammu Founder of the Sumerian Renaissance

https://www.worldhistory.org/Ur-Nammu/
31•Bluestein•1d ago•3 comments

370 Books in 20 months: South African author defends her use of AI

https://www.enca.com/lifestyle/370-books-20-months-sa-author-defends-her-use-ai
14•theanonymousone•3h ago•2 comments

Llama-modchip: 284B DeepSeek on 64GB RAM, no GPU

https://github.com/synchopate/llama-modchip
429•joshcsimmons•1d ago•193 comments

Goldman Sachs is pulling Claude Code from its bankers and traders

https://www.thestateofai.com/news/goldman-sachs-claude-code-traders-bankers
790•TheWiggles•16h ago•417 comments

How I Fight AI Brain Fry

https://sergeykuhne.com/blog/fighting-ai-brain-fry
264•kyunez•15h ago•176 comments

Writing as a thinking tool

http://muratbuffalo.blogspot.com/2026/11/writing-as-thinking-tool.html
372•jruohonen•1d ago•92 comments

RIP, Harvest

https://aphyr.com/posts/427-rip-harvest
363•zdw•9h ago•111 comments

The Qlobe: Rotating Quine (2010)

http://mamememo.blogspot.com/2010/09/qlobe.html
31•niceguitars•7h ago•0 comments

Ask HN: Do you still enjoy coding in C++?

18•hasley•1h ago•12 comments

Show HN: JavaScript web apps with WASM layout and GPU rendering in 280 KB

https://github.com/rkaehn/uniform
31•rkaehn•2d ago•13 comments

When a language's creator and its owners strongly disagree [pdf]

https://isocpp.org/files/papers/P4454R0.pdf
131•acossta•11h ago•129 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?