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CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication Through RL

https://github.com/deepreinforce-ai/CUDA-L2
14•dzign•40m ago•2 comments

Multivox: Volumetric Display

https://github.com/AncientJames/multivox
168•jk_tech•4h ago•21 comments

Plane crashed after 3D-printed part collapsed

https://www.bbc.com/news/articles/c1w932vqye0o
78•toss1•48m ago•56 comments

Transparent leadership beats servant leadership

https://entropicthoughts.com/transparent-leadership-beats-servant-leadership
313•ibobev•8h ago•150 comments

Why are 38 percent of Stanford students saying they're disabled?

https://reason.com/2025/12/04/why-are-38-percent-of-stanford-students-saying-theyre-disabled/
299•delichon•3h ago•464 comments

It’s time to free JavaScript (2024)

https://javascript.tm/letter
599•pavelai•12h ago•317 comments

Hammersmith Bridge – Where did 25,000 vehicles go?

https://nickmaini.substack.com/p/hammersmith-bridge
33•tobr•2h ago•22 comments

PyTogether: Collaborative lightweight real-time Python IDE for teachers/learners

https://github.com/SJRiz/pytogether
40•indigodaddy•4h ago•2 comments

How elites could shape mass preferences as AI reduces persuasion costs

https://arxiv.org/abs/2512.04047
421•50kIters•13h ago•440 comments

Django 6 Released

https://docs.djangoproject.com/en/6.0/releases/6.0/
33•wilhelmklopp•34m ago•8 comments

I ignore the spotlight as a staff engineer

https://lalitm.com/software-engineering-outside-the-spotlight/
363•todsacerdoti•10h ago•160 comments

Show HN: Onlyrecipe 2.0 – I added all features HN requested – 4 years later

https://onlyrecipeapp.com/?url=https://www.allrecipes.com/turkish-pasta-recipe-8754903
85•AwkwardPanda•6h ago•75 comments

Feynman vs. Computer

https://entropicthoughts.com/feynman-vs-computer
47•cgdl•5h ago•18 comments

The RAM shortage comes for us all

https://www.jeffgeerling.com/blog/2025/ram-shortage-comes-us-all
228•speckx•2h ago•254 comments

Converge (YC S23) is hiring a martech expert in NYC

https://www.runconverge.com/careers/technical-customer-success-manager
1•janhenr•4h ago

Autism should not be treated as a single condition

https://www.economist.com/science-and-technology/2025/12/03/why-autism-should-not-be-treated-as-a...
139•bookofjoe•5h ago•202 comments

Fighting the age-gated internet

https://www.wired.com/story/age-verification-is-sweeping-the-us-activists-are-fighting-back/
113•geox•8h ago•99 comments

Launch HN: Browser Buddy (YC W24) – A recommendation system for Internet writing

https://www.browserbuddy.com/
29•alien0006•4h ago•24 comments

Microsoft drops AI sales targets in half after salespeople miss their quotas

https://arstechnica.com/ai/2025/12/microsoft-slashes-ai-sales-growth-targets-as-customers-resist-...
294•OptionOfT•6h ago•221 comments

Functional Quadtrees

https://lbjgruppen.com/en/posts/functional-quadtree-clojure
101•lbj•8h ago•37 comments

Yawning abyss of the decimal labyrinth

https://oh4.co/site/numogrammaticism.html
11•austinallegro•1w ago•0 comments

Who Hooked Up a Laptop to a 1930s Dance Hall Machine?

https://www.chrisbako.com/posts/2025-12-04-speelkok-museam
18•ChrisbyMe•2h ago•4 comments

PGlite – Embeddable Postgres

https://pglite.dev/
456•dsego•10h ago•98 comments

CJEU has made it effectively impossible to run a user-generated platform legally

https://www.techdirt.com/2025/12/04/eus-top-court-just-made-it-literally-impossible-to-run-a-user...
51•alsetmusic•1h ago•14 comments

A Most Important Mustard

https://www.asimov.press/p/arabidopsis
8•surprisetalk•3d ago•0 comments

A lost Amazon world just reappeared in Bolivia

https://www.frontiersin.org/news/2025/11/06/landscapes-that-remember-indigenous-peoples-thrived-a...
84•ashishgupta2209•3d ago•17 comments

Uncloud - Tool for deploying containerised apps across servers without k8s

https://uncloud.run/
325•rgun•15h ago•135 comments

RAM is so expensive, Samsung won't even sell it to Samsung

https://www.pcworld.com/article/2998935/ram-is-so-expensive-samsung-wont-even-sell-it-to-samsung....
320•sethops1•8h ago•295 comments

Tunnl.gg

https://tunnl.gg
137•klipitkas•11h ago•84 comments

Show HN: Chess on a Donut/Torus and Deep-Dive

https://mchess.io/donut
18•mannymakes•5d ago•5 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?