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Deutsche Telekom is violating Net Neutrality

https://netzbremse.de/en/
194•tietjens•3h ago•101 comments

This paper has been cited more than 6k times. It's fatally flawed.

https://statmodeling.stat.columbia.edu/2026/01/22/aking/
85•timr•2h ago•16 comments

BirdyChat becomes first European chat app that is interoperable with WhatsApp

https://www.birdy.chat/blog/first-to-interoperate-with-whatsapp
615•joooscha•16h ago•365 comments

Jurassic Park - Tablet device on Nedry's desk? (2012)

https://www.therpf.com/forums/threads/jurassic-park-tablet-device-on-nedrys-desk.169883/
23•exvi•2h ago•4 comments

Adoption of EVs tied to real-world reductions in air pollution: study

https://keck.usc.edu/news/adoption-of-electric-vehicles-tied-to-real-world-reductions-in-air-poll...
405•hhs•11h ago•346 comments

Google confirms 'high-friction' sideloading flow is coming to Android

https://www.androidauthority.com/google-sideloading-android-high-friction-process-3633468/
235•_____k•5d ago•162 comments

Introduction to PostgreSQL Indexes

https://dlt.github.io/blog/posts/introduction-to-postgresql-indexes/
20•dlt•3h ago•0 comments

A Lament for Aperture

https://ikennd.ac/blog/2026/01/old-man-yells-at-modern-software-design/
92•firloop•4d ago•23 comments

David Patterson: Challenges and Research Directions for LLM Inference Hardware

https://arxiv.org/abs/2601.05047
70•transpute•8h ago•4 comments

Two Weeks Until Tapeout

https://essenceia.github.io/projects/two_weeks_until_tapeout/
119•client4•9h ago•6 comments

BU-808: How to Prolong Lithium-based Batteries (2023)

https://www.batteryuniversity.com/article/bu-808-how-to-prolong-lithium-based-batteries/
7•eswat•2d ago•0 comments

Show HN: AutoShorts – Local, GPU-accelerated AI video pipeline for creators

https://github.com/divyaprakash0426/autoshorts
20•divyaprakash•3h ago•8 comments

Postmortem: Our first VLEO satellite mission (with imagery and flight data)

https://albedo.com/post/clarity-1-what-worked-and-where-we-go-next
176•topherhaddad•15h ago•59 comments

Intrinsically stretchable 2D MoS2 transistors

https://www.nature.com/articles/s41467-026-68504-2
8•bookofjoe•4d ago•0 comments

Accept_language 2.2 – RFC 7231/4647 compliant Accept-Language parsing for Ruby

https://github.com/cyril/accept_language.rb
5•cyrilllllll•1h ago•0 comments

Claude Code's new hidden feature: Swarms

https://twitter.com/NicerInPerson/status/2014989679796347375
422•AffableSpatula•20h ago•287 comments

I built a 2x faster lexer, then discovered I/O was the real bottleneck

https://modulovalue.com/blog/syscall-overhead-tar-gz-io-performance/
29•modulovalue•4d ago•8 comments

We X-Rayed a Suspicious FTDI USB Cable

https://eclypsium.com/blog/xray-counterfeit-usb-cable/
151•aa_is_op•11h ago•57 comments

Typography on Pencils (2023)

https://www.presentandcorrect.com/blogs/blog/typography-on-pencils-1-5
77•NaOH•4d ago•6 comments

Raspberry Pi Drag Race: Pi 1 to Pi 5 – Performance Comparison

https://the-diy-life.com/raspberry-pi-drag-race-pi-1-to-pi-5-performance-comparison/
175•verginer•17h ago•81 comments

Second Win11 emergency out of band update to address disastrous Patch Tuesday

https://www.windowscentral.com/microsoft/windows-11/windows-11-second-emergency-out-of-band-updat...
164•speckx•8h ago•105 comments

Memory layout in Zig with formulas

https://raymondtana.github.io/math/programming/2026/01/23/zig-alignment-and-sizing.html
118•raymondtana•19h ago•25 comments

Small Kafka: Tansu and SQLite on a free t3.micro

https://blog.tansu.io/articles/broker-aws-free-tier
92•rmoff•4d ago•20 comments

Ask HN: Gmail spam filtering suddenly marking everything as spam?

175•goopthink•19h ago•114 comments

Hands-On with Two Apple Network Server Prototype ROMs

http://oldvcr.blogspot.com/2026/01/hands-on-with-two-apple-network-server.html
4•todsacerdoti•3h ago•0 comments

Nvidia-smi hangs indefinitely after ~66 days

https://github.com/NVIDIA/open-gpu-kernel-modules/issues/971
172•tosh•7h ago•41 comments

Maze Algorithms (2017)

http://www.jamisbuck.org/mazes/
137•surprisetalk•1d ago•31 comments

Show HN: Sightline – Shodan-style search for real-world infra using OSM Data

https://github.com/ni5arga/sightline
5•ni5arga•3h ago•0 comments

Understanding Rust Closures

https://antoine.vandecreme.net/blog/rust-closures/
58•avandecreme•16h ago•26 comments

Poland's energy grid was targeted by never-before-seen wiper malware

https://arstechnica.com/security/2026/01/wiper-malware-targeted-poland-energy-grid-but-failed-to-...
235•Bender•13h ago•111 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•8mo 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•8mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•8mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•8mo 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•8mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•8mo 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•8mo 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•8mo 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•8mo 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•8mo 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•8mo 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•8mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•8mo 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•8mo 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•8mo 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•8mo 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•8mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•8mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•8mo 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•8mo 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•8mo 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•8mo 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?