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A recent experience with ChatGPT 5.5 Pro

https://gowers.wordpress.com/2026/05/08/a-recent-experience-with-chatgpt-5-5-pro/
353•_alternator_•8h ago•195 comments

Google broke reCAPTCHA for de-googled Android users

https://reclaimthenet.org/google-broke-recaptcha-for-de-googled-android-users
1100•anonymousiam•16h ago•382 comments

Using Claude Code: The unreasonable effectiveness of HTML

https://twitter.com/trq212/status/2052809885763747935
178•pretext•6h ago•96 comments

OpenAI’s WebRTC problem

https://moq.dev/blog/webrtc-is-the-problem/
341•atgctg•1d ago•85 comments

Mythical Man Month

https://martinfowler.com/bliki/MythicalManMonth.html
185•ingve•2d ago•123 comments

Making Julia as Fast as C++ (2019)

https://flow.byu.edu/posts/julia-c++
15•d_tr•2d ago•2 comments

What causes lightning? The answer keeps getting more interesting

https://www.quantamagazine.org/what-causes-lightning-the-answer-keeps-getting-more-interesting-20...
76•Tomte•2d ago•13 comments

David Attenborough's 100th Birthday

https://www.bbc.com/news/articles/cp3pww9g0p5o
669•defrost•23h ago•136 comments

America's carpet capital: an empire and its toxic legacy

https://apnews.com/projects/pfas-forever-stained/
28•rawgabbit•2d ago•7 comments

AI is breaking two vulnerability cultures

https://www.jefftk.com/p/ai-is-breaking-two-vulnerability-cultures
347•speckx•17h ago•136 comments

Wi is Fi: Understanding Wi-Fi 4/5/6/6E/7/8 (802.11 n/AC/ax/be/bn)

https://www.wiisfi.com/
261•homebrewer•2d ago•62 comments

AWS North Virginia data center outage – resolved

https://www.cnbc.com/2026/05/08/aws-outage-data-center-fanduel-coinbase.html
228•christhecaribou•1d ago•152 comments

Cartoon Network Flash Games

https://www.webdesignmuseum.org/flash-game-exhibitions/cartoon-network-flash-games
349•willmeyers•19h ago•108 comments

The React2Shell Story

https://lachlan.nz/blog/the-react2shell-story/
154•mufeedvh•18h ago•10 comments

An Introduction to Meshtastic

https://meshtastic.org/docs/introduction/
459•ColinWright•1d ago•159 comments

You gave me a u32. I gave you root. (io_uring ZCRX freelist LPE)

https://ze3tar.github.io/post-zcrx.html
189•MrBruh•15h ago•110 comments

Can LLMs model real-world systems in TLA+?

https://www.sigops.org/2026/can-llms-model-real-world-systems-in-tla/
91•mad•19h ago•22 comments

Teaching Claude Why

https://www.anthropic.com/research/teaching-claude-why
175•pretext•17h ago•83 comments

Serving a website on a Raspberry Pi Zero running in RAM

https://btxx.org/posts/memory/
227•xngbuilds•20h ago•91 comments

Light without electricity? Glowing algae could make it possible

https://www.colorado.edu/today/2026/05/06/light-without-electricity-glowing-algae-could-make-it-p...
78•geox•2d ago•24 comments

The soul of maintaining a new machine

https://books.worksinprogress.co/book/maintenance-of-everything/communities-of-practice/the-soul-...
59•akkartik•3d ago•5 comments

Vladimir Putin is losing his grip on Russia

https://www.economist.com/by-invitation/2026/05/06/vladimir-putin-is-losing-his-grip-on-russia
7•bazzmt•38m ago•4 comments

Roadside Attraction

https://theoffingmag.com/essay/roadside-attraction/
23•aways•15h ago•3 comments

PortalVR Motion – use any VR content in 2D with 3D tracked Joy-Cons

https://portalvr.io/motion
23•gfodor•2d ago•1 comments

US Government releases first batch of UAP documents and videos

https://www.war.gov/UFO/
304•david-gpu•23h ago•442 comments

All means are fair except solving the problem

https://yosefk.com/blog/all-means-are-fair-except-solving-the-problem.html
62•akkartik•2d ago•47 comments

Bitter Lessons from the ISSpresso

https://mceglowski.substack.com/p/bitter-lessons-from-the-isspresso
105•zdw•2d ago•29 comments

How to Optimize MongoDB Query Performance with Indexes

https://visualeaf.com/blog/mongodb-query-optimization-indexes/
13•RoxiHaidi•2d ago•2 comments

When is your birthday? The math behind hash collisions

https://0xkrt26.github.io/math_behind_security/2026/05/08/birthday-problem.html
50•denismenace•15h ago•11 comments

EU calls VPNs "a loophole that needs closing" in age verification push

https://cyberinsider.com/eu-calls-vpns-a-loophole-that-needs-closing-in-age-verification-push/
252•muse900•5h ago•185 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•11mo 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•11mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•11mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•11mo 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•11mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•11mo 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•11mo 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•11mo 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•11mo 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•11mo 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•11mo 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•11mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•11mo 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•11mo 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•11mo 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•11mo 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•11mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•11mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•11mo 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•11mo 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•11mo 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•11mo 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?