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Removable batteries in smartphones will be mandatory in the EU starting in 2027

https://www.ecopv-eu.com/en/blog-en/replaceable-smartphone-batteries-2027-eu-regulation/
447•rdeboo•2h ago•398 comments

Days Without GitHub Incidents

https://www.dayswithoutgithubincident.com/
35•goalieca•24m ago•8 comments

I am worried about Bun

https://wwj.dev/posts/i-am-worried-about-bun/
82•remote-dev•1h ago•36 comments

US healthcare marketplaces shared citizenship and race data with ad tech giants

https://techcrunch.com/2026/05/04/us-healthcare-marketplaces-shared-citizenship-and-race-data-wit...
26•ZeidJ•43m ago•4 comments

Stop big tech from making users behave in ways they don't want to

https://economist.com/by-invitation/2026/04/29/stop-big-tech-from-making-users-behave-in-ways-the...
36•andsoitis•49m ago•11 comments

Does Employment Slow Cognitive Decline? Evidence from Labor Market Shocks

https://www.nber.org/papers/w35117
76•littlexsparkee•2h ago•35 comments

Redis array: short story of a long development process

https://antirez.com/news/164
129•antirez•3h ago•46 comments

GitHub Is Down

https://www.githubstatus.com/incidents/72q3n8yxthcy
330•gen220•2h ago•199 comments

Talking to 35 Strangers at the Gym

https://thienantran.com/talking-to-35-strangers-at-the-gym/
698•thitran•6h ago•347 comments

I tracked 7,700 UK petrol stations every 10 minutes for 3 months

https://www.fuelinsight.co.uk
69•theazureguy•2h ago•33 comments

Pomiferous: The most extensive apples (pommes) database

https://pomiferous.com/
35•Ariarule•3h ago•16 comments

GameStop makes $55.5B takeover offer for eBay

https://www.bbc.co.uk/news/articles/cn0p8yled1do
487•n1b0m•8h ago•428 comments

PyInfra 3.8.0 Is Out

https://github.com/pyinfra-dev/pyinfra/releases/tag/v3.8.0
170•wowi42•5h ago•66 comments

Sierra Raises $950M at $15B Valuation

https://sierra.ai/blog/better-customer-experiences-built-on-sierra
27•doppp•2h ago•33 comments

OpenAI, Google, and Microsoft Back Bill to Fund 'AI Literacy' in Schools

https://www.404media.co/literacy-in-future-technologies-artificial-intelligence-act-adam-schiff-m...
45•cdrnsf•1h ago•36 comments

Alberta voter list leak is a potential public safety disaster

https://globalnews.ca/news/11828244/alberta-voter-list-leak-public-safety-disaster/
53•Teever•2h ago•39 comments

Trillions in Retirement Dollars Flow into Opaque Trusts

https://www.bloomberg.com/news/features/2026-05-03/trillions-in-us-retirement-dollars-flow-into-o...
15•koolhead17•38m ago•1 comments

Newton's law of gravity passes its biggest test

https://www.science.org/content/article/newton-s-law-gravity-passes-its-biggest-test-ever
84•pseudolus•5h ago•58 comments

DAG Workflow Engine

https://github.com/vivekg13186/Daisy-DAG
37•blobmty•5h ago•27 comments

Using “underdrawings” for accurate text and numbers

https://samcollins.blog/underdrawings/
334•samcollins•2d ago•123 comments

Why are neural networks and cryptographic ciphers so similar? (2025)

https://reiner.org/neural-net-ciphers
90•jxmorris12•2d ago•28 comments

Trademark violation: Fake Notepad++ for Mac

https://notepad-plus-plus.org/news/npp-trademark-infringement/
513•maxloh•8h ago•222 comments

Texico: Learn the principles of programming without even touching a computer

https://www3.nhk.or.jp/nhkworld/en/shows/texico/
148•o4c•2d ago•11 comments

BYOMesh – New LoRa mesh radio offers 100x the bandwidth

https://partyon.xyz/@nullagent/116499715071759135
445•nullagent•23h ago•145 comments

Homebridge 2.0 is here, and it speaks Matter

https://www.theverge.com/tech/922877/homebridge-2-0-matter-update-robot-vacuums
24•Brajeshwar•1h ago•2 comments

How Monero's proof of work works

https://blog.alcazarsec.com/tech/posts/how-moneros-proof-of-work-works
120•alcazar•3h ago•101 comments

DeepClaude – Claude Code agent loop with DeepSeek V4 Pro

https://github.com/aattaran/deepclaude
607•alattaran•19h ago•258 comments

1966 Ford Mustang Converted into a Tesla with Working 'Full Self-Driving'

https://electrek.co/2026/05/02/tesla-1966-mustang-ev-conversion-full-self-driving/
44•Brajeshwar•2h ago•32 comments

Discovering hard disk physical geometry through microbenchmarking (2019)

https://blog.stuffedcow.net/2019/09/hard-disk-geometry-microbenchmarking/
150•TapamN•3d ago•6 comments

A treasure trove of fossils rewrites the story of early life

https://www.quantamagazine.org/a-treasure-trove-of-cambrian-fossils-rewrites-the-story-of-early-l...
88•worldvoyageur•3d ago•20 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?