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More than half of adults in U.S. say they lack basic statistical understanding

https://www.psu.edu/news/research/story/more-half-adults-us-say-they-lack-basic-statistical-under...
41•giuliomagnifico•1h ago•44 comments

Apple introduces M6 and M5 Ultra

https://www.apple.com/newsroom/2026/08/apple-introduces-m6-and-m5-ultra-for-a-big-leap-in-perform...
1079•interpol_p•18h ago•1027 comments

FDA authorizes first wearable device that monitors ketone and blood sugar levels

https://www.fda.gov/news-events/press-announcements/fda-authorizes-first-wearable-device-continuo...
355•sunnynagra•11h ago•174 comments

Stalking the Wily Hacker: 40 years later – Cliff Stoll [video]

https://www.youtube.com/watch?v=656058JxTM0
35•zoenolan•4d ago•12 comments

OpenAI Jalapeño: Better than Nvidia Blackwell

https://newsletter.semianalysis.com/p/openai-jalapeno-better-than-nvidia
431•bmulholland•16h ago•282 comments

Queryable Executables

https://fzakaria.com/2026/08/24/actually-queryable-executables
116•rguiscard•6h ago•18 comments

Secret Cold War IBM Supercomputer Was Built for One Job

https://spectrum.ieee.org/cold-war-codebreaker-nsa-ibm
8•jnord•1h ago•0 comments

New Mac Studio with M5 Max and M5 Ultra

https://www.apple.com/newsroom/2026/08/apple-introduces-new-mac-studio-with-m5-max-and-m5-ultra/
750•interpol_p•18h ago•492 comments

Maiao: Gerrit-style code review workflow for GitHub, GitLab, Gitea, others

https://github.com/runetes/maiao
64•zdw•8h ago•34 comments

Black hole singularity is a surface not a point

https://arxiv.org/abs/2608.21590
225•raattgift•14h ago•167 comments

New Mac mini, featuring M6 and M5 Pro

https://www.apple.com/newsroom/2026/08/apple-unveils-a-more-powerful-mac-mini-featuring-the-all-n...
480•runako•17h ago•297 comments

Agentic Context Management: Memory and Cost as Architecture Problems

https://arxiv.org/abs/2607.21503
25•gdad•4h ago•13 comments

C2PA Cameras Do Not Survive Contact with Reality

https://www.da.vidbuchanan.co.uk/blog/android-c2pa.html
130•Retr0id•11h ago•75 comments

When str.lower() is a security vulnerability in Python

https://sethmlarson.dev/when-str-lower-is-a-security-vulnerability
99•rbanffy•10h ago•44 comments

Nitter and XCancel receive cease and desist notices

https://github.com/zedeus/nitter/issues/1442
818•Banditoz•13h ago•686 comments

Building a backyard office, the build and cost breakdown

https://www.imkylelambert.com/articles/building-a-backyard-office-the-build-and-cost-breakdown
321•surprisetalk•16h ago•209 comments

Bomb fishing is wreaking havoc on Indonesia's coral reefs

https://e360.yale.edu/digest/bomb-fishing-coral-reefs
303•speckx•16h ago•155 comments

Run OpenBSD on DigitalOcean for $4/month

https://nil.wallyjones.com/run-openbsd-on-digitalocean-for-4month/
150•speckx•13h ago•69 comments

Tooltips need a delay, and then they need to skip it

https://blog.master.dev/tooltips-need-a-delay-and-then-they-need-to-skip-it/
155•ibobev•14h ago•39 comments

Don't Wordle

https://dontwordle.com/
338•Hbruz0•19h ago•120 comments

Show HN: TeXbrain, a LaTeX editor that runs pdfTeX in the browser via WASM

https://github.com/swimmingbrain/texbrain
77•swimmingbrain•8h ago•16 comments

Show HN: I made a Raspberry with Qwen my local car AI

https://github.com/ThinkOffApp/CarWatch
127•petruspennanen•15h ago•35 comments

Dolly Parton has died

https://www.theguardian.com/music/2026/aug/25/dolly-parton-country-singer-dead
1405•helsinkiandrew•13h ago•212 comments

Show HN: LatticeDB – Like SQLite but for graph databases

https://github.com/jeffhajewski/latticedb
137•smiths1999•14h ago•37 comments

A brief history of federal lift ticket regulation

https://zakpodmore.substack.com/p/a-brief-history-of-federal-lift-ticket
58•CGMthrowaway•11h ago•11 comments

My Friend Aaron

https://rorz.io/writing/my-friend-aaron
523•sarreph•14h ago•143 comments

Firefox 157 will include JPEG XL by default on all platforms

https://groups.google.com/a/mozilla.org/g/dev-platform/c/3YMV4MS34KA?pli=1
346•yboris•13h ago•89 comments

Clara (YC P26) is hiring a growth engineer to bring AI doctors to market

https://www.ycombinator.com/companies/clara-2/jobs/8snci6k-founding-full-stack-growth-engineer
1•gfavvas•13h ago

Visualizing Binary Files

https://movq.de/blog/postings/2026-08-05/0/POSTING-en.html
101•zdw•1d ago•18 comments

Tracking Costco gas prices

https://www.jack.bio/blog/costco-gas-tracking
108•lafond•1d ago•101 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•1y 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•1y ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•1y ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•1y 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•1y ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•1y 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•1y 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•1y 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•1y 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•1y 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•1y 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•1y ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•1y 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•1y 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•1y 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•1y 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•1y ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•1y ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•1y 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•1y 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•1y 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•1y 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?