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Bonsai 27B: A 27B-Class model that runs on a phone

https://prismml.com/news/bonsai-27b
345•xenova•5h ago•130 comments

Dependabot version updates introduce default package cooldown

https://github.blog/changelog/2026-07-14-dependabot-version-updates-introduce-default-package-coo...
50•woodruffw•2h ago•34 comments

Financing the AI boom: from cash flows to debt [pdf]

https://www.bis.org/publ/bisbull120.pdf
37•1vuio0pswjnm7•1h ago•2 comments

The Tower Keeps Rising

https://lucumr.pocoo.org/2026/7/13/the-tower-keeps-rising/
298•cdrnsf•6h ago•150 comments

Cursor 0day: When Full Disclosure Becomes the Only Protection Left

https://mindgard.ai/blog/cursor-0day-when-full-disclosure-becomes-the-only-protection-left
193•Synthetic7346•5h ago•77 comments

How I use HTMX with Go

https://www.alexedwards.net/blog/how-i-use-htmx-with-go
68•gnabgib•3h ago•12 comments

Your 'app' could have been a webpage (so I fixed it for you)

https://danq.me/2026/07/09/your-app-could-have-been-a-webpage/
672•MrVandemar•3d ago•419 comments

QR-Swastika-Avoider

https://crates.io/crates/qr-swastika-avoider
16•gregsadetsky•35m ago•1 comments

The Estranged Worlds of J. G. Ballard

https://lareviewofbooks.org/article/jg-ballard-illuminated-man-christopher-priest-nina-allan/
23•Caiero•1d ago•5 comments

The largest available Minecraft world, totalling 15 TB

https://2b2t.place/1million
135•_____k•3d ago•41 comments

Microsoft deleted my account and OneDrive

https://twitter.com/JoshuaKhane/status/2076918699248803977
32•nixass•4h ago•27 comments

How to stop Claude from saying load-bearing

https://jola.dev/posts/how-to-stop-claude-from-saying-load-bearing
402•shintoist•11h ago•460 comments

Guardian Angels: LLM Personalization for Productivity and Security

https://gwern.net/guardian-angel
46•andsoitis•10h ago•3 comments

Mathematical texts from a Maya site in Guatemala identify an ancient astronomer

https://www.nature.com/articles/d41586-026-02170-8
9•homarp•11h ago•1 comments

The zero-cost fallacy: open-source software in the agentic era

https://www.thoughtworks.com/insights/blog/open-source/zero-cost-fallacy-open-source-agentic-era
92•backlit4034•4d ago•73 comments

I'm a USB-C Maximalist

https://shkspr.mobi/blog/2026/07/im-a-usb-c-maximalist/
123•speckx•8h ago•220 comments

The Second Life of Sanskrit

https://openthemagazine.com/india/the-second-life-of-sanskrit
44•bookofjoe•3d ago•30 comments

Human Canaries: Remembering the Munitionettes

https://www.historytoday.com/archive/great-debates/human-canaries-remembering-munitionettes
9•Thevet•23h ago•0 comments

Kontigo (YC S24) Is Hiring (Head of Security)

https://www.ycombinator.com/companies/kontigo/jobs/uNttrlv-head-of-security
1•jecastillof•6h ago

Are we offloading too much of our thinking to AI?

https://www.artfish.ai/p/offloading-thinking-to-ai
346•yenniejun111•8h ago•347 comments

Show HN: Opening lines of famous literary works

https://www.verbaprima.com/
136•plicerin•7h ago•78 comments

Launch HN: Agnost AI (YC S26) – Extract user feedback from agent conversations

https://agnost.ai
37•laalshaitaan•7h ago•23 comments

Banter

https://homosabiens.substack.com/p/banter
11•surprisetalk•4d ago•2 comments

Accretive Editing

https://justindfuller.com/programming/accretive-editing
13•iamjfu•4d ago•5 comments

Measuring Input Latency on Linux: X11 vs. Wayland, VRR, and DXVK

https://marco-nett.de/blog/measuring-input-latency-on-linux-x11-vs-wayland-vrr-dxvk/
333•hoechst•6h ago•211 comments

Show HN: Juggler – an open-source GUI coding agent, by the creator of JUCE

https://github.com/juggler-ai/juggler
158•julesrms•2d ago•77 comments

StubHub, CEO hit with ‘deceptive practices’ class action over mass scalping

https://www.cbc.ca/news/world/stubhub-ceo-class-action-scalping-9.7268987
84•b112•3h ago•45 comments

LeMario: Training a JEPA World Model on Super Mario Bros

https://www.benjamin-bai.com/projects/lemario
4•kevinjosethomas•51m ago•0 comments

Punch yourself in the face with reality

https://adi.bio/reality
202•AdityaAnand1•11h ago•98 comments

Demis Hassabis has a plan to harness AI safely

https://twitter.com/demishassabis/status/2076957440109625718
132•asiergoni•14h ago•173 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?