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Show HN: Gemini Pro 3 hallucinates the HN front page 10 years from now

https://dosaygo-studio.github.io/hn-front-page-2035/news
2824•keepamovin•21h ago•809 comments

Revisiting "Let's Build a Compiler"

https://eli.thegreenplace.net/2025/revisiting-lets-build-a-compiler/
117•cui•6h ago•13 comments

Rust in the kernel is no longer experimental

https://lwn.net/Articles/1049831/
637•rascul•9h ago•429 comments

PeerTube is recognized as a digital public good by Digital Public Goods Alliance

https://www.digitalpublicgoods.net/r/peertube
573•fsflover•19h ago•111 comments

Putting email in its place with Emacs and Mu4e

https://eamonnsullivan.co.uk/posts-output/email-setup/2025-12-3-putting-email-in-its-place/
56•eamonnsullivan•6d ago•12 comments

Amazon EC2 M9g Instances

https://aws.amazon.com/ec2/instance-types/m9g/
69•AlexClickHouse•4d ago•18 comments

When a video codec wins an Emmy

https://blog.mozilla.org/en/mozilla/av1-video-codec-wins-emmy/
175•todsacerdoti•4d ago•30 comments

Bruno Simon – 3D Portfolio

https://bruno-simon.com/
629•razzmataks•20h ago•148 comments

Mistral releases Devstral2 and Mistral Vibe CLI

https://mistral.ai/news/devstral-2-vibe-cli
638•pember•22h ago•301 comments

If you're going to vibe code, why not do it in C?

https://stephenramsay.net/posts/vibe-coding.html
515•sramsay•19h ago•485 comments

Django: what’s new in 6.0

https://adamj.eu/tech/2025/12/03/django-whats-new-6.0/
309•rbanffy•16h ago•92 comments

Cloth Simulation

https://cloth.mikail-khan.com/
51•adamch•1w ago•8 comments

Italy's longest-serving barista reflects on six decades behind the counter

https://www.reuters.com/lifestyle/culture-current/anna-possi-six-decades-behind-counter-italys-ba...
210•NaOH•5d ago•108 comments

Pebble Index 01 – External memory for your brain

https://repebble.com/blog/meet-pebble-index-01-external-memory-for-your-brain
511•freshrap6•21h ago•489 comments

Are the Three Musketeers allergic to muskets? (2014)

https://www.ox.ac.uk/news/arts-blog/are-three-musketeers-allergic-muskets
43•rolph•6h ago•21 comments

10 Years of Let's Encrypt

https://letsencrypt.org/2025/12/09/10-years
693•SGran•17h ago•284 comments

Running Linux on a RiscPC – why is it so hard?

https://thejpster.org.uk/blog/blog-2025-12-02/
12•zdw•1w ago•4 comments

Donating the Model Context Protocol and establishing the Agentic AI Foundation

https://www.anthropic.com/news/donating-the-model-context-protocol-and-establishing-of-the-agenti...
247•meetpateltech•19h ago•109 comments

Passing the Torch: James Gross on the Next Chapter of Micromobility Industries

https://micromobility.io/news/how-charging-is-reshaping-the-business-of-shared-scooters-and-e-bikes
10•prabinjoel•6d ago•0 comments

So you want to speak at software conferences?

https://dylanbeattie.net/2025/12/08/so-you-want-to-speak-at-software-conferences.html
188•speckx•18h ago•99 comments

Writing our own Cheat Engine in Rust

https://lonami.dev/blog/woce-1/
83•hu3•5d ago•12 comments

Cloudflare error page generator

https://github.com/donlon/cloudflare-error-page
63•sawirricardo•10h ago•8 comments

The stack circuitry of the Intel 8087 floating point chip, reverse-engineered

https://www.righto.com/2025/12/8087-stack-circuitry.html
120•elpocko•18h ago•54 comments

Linux CVEs, more than you ever wanted to know

http://www.kroah.com/log/blog/2025/12/08/linux-cves-more-than-you-ever-wanted-to-know/
70•voxadam•14h ago•32 comments

Kaiju – General purpose 3D/2D game engine in Go and Vulkan with built in editor

https://github.com/KaijuEngine/kaiju
198•discomrobertul8•22h ago•90 comments

A supersonic engine core makes the perfect power turbine

https://boomsupersonic.com/flyby/ai-needs-more-power-than-the-grid-can-deliver-supersonic-tech-ca...
123•simonebrunozzi•21h ago•196 comments

30 Year Anniversary of WarCraft II: Tides of Darkness

https://www.jorsys.org/archive/december_2025.html#newsitem_2025-12-09T07:42:19Z
240•sjoblomj•1d ago•161 comments

Qt, Linux and everything: Debugging Qt WebAssembly

http://qtandeverything.blogspot.com/2025/12/debugging-qt-webassembly-dwarf.html
76•speckx•15h ago•23 comments

Stop Breaking TLS

https://www.markround.com/blog/2025/12/09/stop-breaking-tls/
115•todsacerdoti•5h ago•78 comments

Operando interlayer expansion of curved graphene for dense supercapacitors

https://www.nature.com/articles/s41467-025-63485-0
28•westurner•5d ago•2 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•6mo 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•6mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•6mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•6mo 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•6mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•6mo 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•6mo 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•6mo 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•6mo 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•6mo 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•6mo 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•6mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•6mo 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•6mo 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•6mo 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•6mo 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•6mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•6mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•6mo 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•6mo 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•6mo 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•6mo 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?