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11 year old unsoundness bugs found in Rust borrow checker

https://github.com/rust-lang/rust/issues/164250
112•formerly_proven•1h ago•31 comments

An hour of audio transcribed in about 13s on MacBook Air

https://eg2.haku.sh/
15•amrrs•10m ago•1 comments

Show HN: Use your OpenAI subscription to create audiobooks

https://pdftomp3.com/connect-ai/
28•janpmz•1h ago•20 comments

Hittite royal archive found in Turkey

https://www.thehistoryblog.com/archives/77107
95•benbreen•5h ago•8 comments

The baffling intelligence of a single cell (2024)

https://jsomers.net/e-coli-chemotaxis/
313•jsomers•2d ago•84 comments

GLM-Legal

https://z.ai/blog/glm-legal
586•ilreb•19h ago•330 comments

CFTC Staff Were Told to Retract Analysis of Suspicious Oil Trades

https://www.bloomberg.com/news/features/2026-10-13/cftc-staff-told-to-retract-analysis-of-suspici...
58•helsinkiandrew•1h ago•9 comments

Intel D270 GPU AI Accelerator–Up to 480 GB LPDDR5X

https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/d-series.html
243•hurricanepootis•14h ago•116 comments

Hackers activate automatic defrosting in supermarket fridges across Europe

https://www.tomshardware.com/tech-industry/cyber-security/unprecedented-cyberattack-cripples-supe...
736•Zeekaas•23h ago•851 comments

A Modern Web App in C

https://prophitt.me/writing/a-modern-web-app-in-c
594•prophittcorey•19h ago•250 comments

Document Review with Unsiloed and TypeSafe Jev

https://www.unsiloed.ai/blog/document-review-unsiloed-typesafe-jev
15•ritzaco•3h ago•2 comments

Who is vfmaddrnd231pd?

https://purplesyringa.moe/blog/who-is-vfmaddrnd231pd/
220•pngmangi•14h ago•21 comments

Janas: Run LLMs larger than RAM by streaming experts from SSD

https://github.com/prabanta-dev/janas
162•khalidkhair•13h ago•54 comments

Making big downloads resumable in Firefox

https://lunarwatcher.codeberg.page/til/firefox/resumable-big-downloads.html
224•speckx•16h ago•105 comments

Crypto thieves sell hardware wallets with secret eSIM

https://www.heise.de/en/news/Crypto-thieves-sell-hardware-wallets-with-secret-eSIM-11485188.html
48•qwertox•3h ago•30 comments

AWS Lambda Web Functions

https://aws.amazon.com/blogs/aws/announcing-aws-lambda-web-functions-for-fast-consistent-web-app-...
33•HatchedLake721•1h ago•8 comments

Turn a WiFi 7 Router into a 320Msps Software Defined Radio Receiver

https://github.com/h0m3us3r/w1700k-sdr
361•djfergus•22h ago•100 comments

Citroen revives the 2CV for an electric age

https://www.bbc.com/news/articles/c620r33plgppo
356•scrlk•23h ago•401 comments

AI is a tool and using it well takes skill

https://yyhh.org/blog/2026/10/ai-is-a-tool/
440•layer8•13h ago•355 comments

Launch HN: Agent37 (YC F26) – Low-cost agent sandboxes for running agents

137•vishnukool•18h ago•98 comments

A look at the math that OpenAI claims computes faster Fourier transforms

https://www.argmin.net/p/faster-fourier-transforms
160•mochomocha•8h ago•107 comments

Auto Research: Integer multiplication below n log n

https://app.getsupers.com/auto-research
66•swesnow•1d ago•30 comments

Writing a Demoscene Intro for the ZX Spectrum

https://www.markround.com/blog/2026/zx-spectrum-intro
139•zdw•15h ago•26 comments

Solar panels that plug into your wall

https://www.nationalgeographic.com/environment/article/balcony-plug-in-solar-panels-renewable-energy
200•speckx•21h ago•212 comments

AI models can provably hide arbitrary capabilities

https://arxiv.org/abs/2610.13928
222•sbulaev•9h ago•112 comments

AI models may soon self-replicate without access to data centers

https://www.reuters.com/business/ai-models-may-soon-self-replicate-without-access-data-centers-an...
16•samizdis•1h ago•20 comments

Show HN: SolidCraft – Open-Source Parametric CAD in Rust (With MCP Support)

https://github.com/bherbruck/solidcraft
71•bherbruck•11h ago•14 comments

Show HN: An experimental pattern-first DAW that supports MCP

https://github.com/andrewfader/blokkily
65•androsynth89•12h ago•28 comments

Kevin Kelly's 2016 AI Predictions, 10 Years Later

https://taylor.town/kk-ai-2026
193•surprisetalk•20h ago•74 comments

The Making Of Super Mario 64 – full Giles Goddard interview (2001)

https://pixelatron.com/blog/the-making-of-super-mario-64-full-giles-goddard-interview-ngc/
255•gregsadetsky•2d ago•100 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?