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Tesla Hid Fatal Accidents to Continue Testing Autonomous Driving (French)

https://www.rts.ch/info/monde/2026/article/tesla-dissimule-des-milliers-d-incidents-de-conduite-a...
247•doener•1h ago•109 comments

M 7.4 earthquake – 100 km ENE of Miyako, Japan

https://earthquake.usgs.gov/earthquakes/eventpage/us6000sri7/
88•Someone•3h ago•39 comments

GitHub's Fake Star Economy

https://awesomeagents.ai/news/github-fake-stars-investigation/
297•Liriel•4h ago•181 comments

ggsql: A Grammar of Graphics for SQL

https://opensource.posit.co/blog/2026-04-20_ggsql_alpha_release/
10•thomasp85•28m ago•2 comments

Focused microwaves allow 3D printers to fuse circuits onto almost anything

https://newatlas.com/electronics/meta-nfc-focused-microwaves-circuits/
60•breve•2d ago•12 comments

Up to 8M Bees Are Living in an Underground Network Beneath This Cemetery

https://www.discovermagazine.com/up-to-8-million-bees-are-living-in-an-underground-network-beneat...
95•janandonly•2d ago•12 comments

NSA is using Anthropic's Mythos despite blacklist

https://www.reuters.com/business/us-security-agency-is-using-anthropics-mythos-despite-blacklist-...
157•Palmik•3h ago•115 comments

SDF Public Access Unix System

https://sdf.org/?ssh
106•neehao•1d ago•45 comments

Vercel April 2026 security incident

https://www.bleepingcomputer.com/news/security/vercel-confirms-breach-as-hackers-claim-to-be-sell...
789•colesantiago•23h ago•451 comments

What if database branching was easy?

https://xata.io/blog/what-if-database-branching-was-easy
15•tee-es-gee•2d ago•5 comments

Why macOS27 won't be supporting Intel anymore

https://twitter.com/Lina_Hoshino/status/2046112493320458649
32•tasoeur•1h ago•37 comments

Stop trying to engineer your way out of listening to people

https://ashley.rolfmore.com/stop-trying-to-engineer-your-way-out-of-listening-to-people/
297•walterbell•17h ago•143 comments

Claude Token Counter, now with model comparisons

https://simonwillison.net/2026/Apr/20/claude-token-counts/
147•twapi•12h ago•59 comments

I Made the "Next-Level" Camera and I love it

https://thelibre.news/i-made-the-next-level-camera-and-i-love-it/
101•ndr•3d ago•18 comments

Zero-copy protobuf and ConnectRPC for Rust

https://medium.com/@iainmcgin/zero-copy-protobuf-and-connectrpc-for-rust-69bda8ac0f02
86•PaulHoule•3d ago•24 comments

Stripe's Payment APIs: the first 10 years (2020)

https://stripe.dev/blog/payment-api-design
71•tibbar•8h ago•35 comments

A Brief History of Fish Sauce

https://www.legalnomads.com/fish-sauce/
193•vinhnx•1d ago•82 comments

NASA Artemis Posters

https://www.nasa.gov/gallery/artemis/
14•bookofjoe•1h ago•1 comments

Epicycles All the Way Down

https://www.strangeloopcanon.com/p/epicycles-all-the-way-down
3•surprisetalk•3d ago•0 comments

Ben Lerner's Big Feelings

https://www.vulture.com/article/ben-lerner-transcription-interview.html
39•prismatic•4d ago•18 comments

Turtle WoW classic server announces shutdown after Blizzard wins injunction

https://www.pcgamer.com/games/world-of-warcraft/turtle-wow-classic-server-announces-shutdown-afte...
260•Brajeshwar•21h ago•235 comments

The Bromine Chokepoint

https://warontherocks.com/cogs-of-war/the-bromine-chokepoint-how-strife-in-the-middle-east-could-...
207•crescit_eundo•19h ago•121 comments

Monumental ship burial beneath ancient Norwegian mound predates the Viking Age

https://phys.org/news/2026-04-monumental-ship-burial-beneath-ancient.html
69•pseudolus•3d ago•19 comments

IEA: Solar overtakes all energy sources in a major global first

https://electrek.co/2026/04/19/iea-solar-overtakes-all-energy-sources-in-a-major-global-first/
97•Klaster_1•6h ago•70 comments

Who Is Blake Whiting?

https://theamericanscholar.org/who-is-blake-whiting/
21•Caiero•2d ago•4 comments

Mechanical Keyboard Sounds – A listening Museum

https://sheets.works/data-viz/keyboard-sounds
154•akashwadhwani35•4d ago•46 comments

A cache-friendly IPv6 LPM with AVX-512 (linearized B+-tree, real BGP benchmarks)

https://github.com/esutcu/planb-lpm
50•debugga•9h ago•18 comments

Figma's woes compound with Claude Design

https://martinalderson.com/posts/figmas-woes-compound-with-claude-design/
55•martinald•2h ago•45 comments

Scientific datasets are riddled with copy-paste errors

https://www.sciencedetective.org/scientific-datasets-are-riddled-with-copy-paste-errors/
126•jruohonen•18h ago•39 comments

A Pascal's Wager for AI Doomers

https://pluralistic.net/2026/04/16/pascals-wager/
15•vrganj•1h ago•18 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?