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Microgpt

http://karpathy.github.io/2026/02/12/microgpt/
464•tambourine_man•4h ago•83 comments

We do not think Anthropic should be designated as a supply chain risk

https://twitter.com/OpenAI/status/2027846016423321831
437•golfer•8h ago•189 comments

The Windows 95 user interface: A case study in usability engineering (1996)

https://dl.acm.org/doi/fullHtml/10.1145/238386.238611
212•ksec•8h ago•126 comments

Obsidian Sync now has a headless client

https://help.obsidian.md/sync/headless
440•adilmoujahid•13h ago•152 comments

SQL vs. NoSQL: How to Answer This Interview Question in 2026

https://www.thetrueengineer.com/p/sql-vs-nosql-how-to-answer-this-interview
11•janandonly•3d ago•0 comments

The happiest I've ever been

https://ben-mini.com/2026/the-happiest-ive-ever-been
415•bewal416•3d ago•212 comments

H-Bomb: A Frank Lloyd Wright Typographic Mystery

https://www.inconspicuous.info/p/h-bomb-a-frank-lloyd-wright-typographic
58•mrngm•2d ago•13 comments

Sub-second volumetric 3D printing by synthesis of holographic light fields

https://www.nature.com/articles/s41586-026-10114-5
25•zdw•3d ago•5 comments

Show HN: Xmloxide – an agent made rust replacement for libxml2

https://github.com/jonwiggins/xmloxide
50•jawiggins•6h ago•34 comments

Block the “Upgrade to Tahoe” Alerts

https://robservatory.com/block-the-upgrade-to-tahoe-alerts-and-system-settings-indicator/
182•todsacerdoti•11h ago•83 comments

Microsoft announces new "mini PCs" for Windows 365

https://www.neowin.net/news/microsoft-announces-new-mini-pcs-for-windows-365/
32•mikece•2d ago•31 comments

Addressing Antigravity Bans and Reinstating Access

https://github.com/google-gemini/gemini-cli/discussions/20632
223•RyanShook•16h ago•182 comments

Woxi: Wolfram Mathematica Reimplementation in Rust

https://github.com/ad-si/Woxi
268•adamnemecek•3d ago•111 comments

Verified Spec-Driven Development (VSDD)

https://gist.github.com/dollspace-gay/d8d3bc3ecf4188df049d7a4726bb2a00
166•todsacerdoti•13h ago•87 comments

MCP server that reduces Claude Code context consumption by 98%

https://mksg.lu/blog/context-mode
315•mksglu•20h ago•71 comments

Show HN: Now I Get It – Translate scientific papers into interactive webpages

https://nowigetit.us
219•jbdamask•16h ago•100 comments

Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers

https://venturebeat.com/technology/alibabas-new-open-source-qwen3-5-medium-models-offer-sonnet-4-...
301•lostmsu•10h ago•186 comments

Building a Minimal Transformer for 10-digit Addition

https://alexlitzenberger.com/blog/post.html?post=/building_a_minimal_transformer_for_10_digit_add...
48•kelseyfrog•8h ago•7 comments

Samsung Galaxy update removes Android recovery menu tools, including sideloading

https://9to5google.com/2026/02/27/samsung-galaxy-update-android-recovery-menu-removed/
78•pabs3•4h ago•16 comments

The Science of Detecting LLM-Generated Text

https://dl.acm.org/doi/10.1145/3624725
12•vinhnx•4h ago•1 comments

Werner Herzog Between Fact and Fiction

https://www.thenation.com/article/culture/werner-herzog-future-truth/
71•Hooke•1d ago•14 comments

New evidence that Cantor plagiarized Dedekind?

https://www.quantamagazine.org/the-man-who-stole-infinity-20260225/
117•rbanffy•3d ago•74 comments

SpacetimeDB ThreeJS Support

https://discourse.threejs.org/t/spacetimedb-threejs-support-and-free-tier/90052
11•ryker2000•3d ago•3 comments

Our Agreement with the Department of War

https://openai.com/index/our-agreement-with-the-department-of-war
258•surprisetalk•9h ago•205 comments

The whole thing was a scam

https://garymarcus.substack.com/p/the-whole-thing-was-scam
716•guilamu•13h ago•216 comments

747s and Coding Agents

https://carlkolon.com/2026/02/27/engineering-747-coding-agents/
142•cckolon•1d ago•62 comments

The archivist preserving decaying floppy disks

https://www.popsci.com/technology/floppy-disk-archivist-project/
61•Brajeshwar•3d ago•11 comments

Deterministic Programming with LLMs

https://www.mcherm.com/deterministic-programming-with-llms.html
36•todsacerdoti•3d ago•19 comments

The Eternal Promise: A History of Attempts to Eliminate Programmers

https://www.ivanturkovic.com/2026/01/22/history-software-simplification-cobol-ai-hype/
259•dinvlad•4d ago•173 comments

Running a One Trillion-Parameter LLM Locally on AMD Ryzen AI Max+ Cluster

https://www.amd.com/en/developer/resources/technical-articles/2026/how-to-run-a-one-trillion-para...
53•mindcrime•4h ago•10 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•9mo 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•9mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•9mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•9mo 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•9mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•9mo 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•9mo 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•9mo 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•9mo 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•9mo 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•9mo 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•9mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•9mo 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•9mo 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•9mo 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•9mo 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•9mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•9mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•9mo 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•9mo 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•9mo 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•9mo 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?