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Apple reveals new AI architecture built around Google Gemini models

https://www.macrumors.com/2026/06/08/apple-reveals-new-ai-architecture/
355•unclefuzzy•7h ago•321 comments

Hermes Agent – Open-source AI agent with persistent memory

https://hermes-agent.org/
35•SeriousM•3d ago•6 comments

Siri AI

https://www.apple.com/apple-intelligence/
423•0xedb•8h ago•372 comments

Show HN: Performative-UI – A react component library of design tropes

https://vorpus.github.io/performativeUI/
799•lizhang•12h ago•156 comments

MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per second

https://mimo.xiaomi.com/blog/mimo-tilert-1000tps
503•gainsurier•10h ago•350 comments

Looking Forward to Postgres 19: Query Hints

https://www.pgedge.com/blog/looking-forward-to-postgres-19-query-hints
65•jjgreen•3d ago•6 comments

Anti-social: It's fads, not friends, which now dominate social media feeds

https://www.bbc.com/worklife/article/20260520-how-social-media-ceased-to-be-social
556•1vuio0pswjnm7•14h ago•413 comments

EU-banned pesticides found in rice, tea and spices

https://www.foodwatch.org/en/eu-banned-pesticides-found-in-rice-tea-and-spices
248•john-titor•10h ago•90 comments

Apple Core AI Framework

https://developer.apple.com/documentation/coreai/
205•hmokiguess•7h ago•44 comments

Show HN: Gitdot – a better GitHub. Open-source, written in Rust

https://gitdot.io/
157•baepaul•9h ago•125 comments

We Think the SpaceX IPO Is Overvalued

https://www.morningstar.com/stocks/why-we-think-spacex-ipo-is-overvalued?content_id=20768396545
40•0xedb•29m ago•10 comments

Why are cells small?

https://burrito.bio/essays/what-limits-a-cells-size
110•mailyk•7h ago•52 comments

xAI is looking more like a datacentre REIT than a frontier lab

https://martinalderson.com/posts/xais-new-rental-business/
406•martinald•11h ago•322 comments

Surveillance is not safety: A statement on the UK's latest threat to privacy [pdf]

https://signal.org/blog/pdfs/2026-06-08-uk-surveillance-is-not-safety.pdf
434•g0xA52A2A•6h ago•159 comments

FrontierCode

https://cognition.ai/blog/frontier-code
104•streamer45•5h ago•20 comments

Confidential submission of draft S-1 to the SEC

https://openai.com/index/openai-submits-confidential-s-1/
302•hackerBanana•5h ago•218 comments

Ask HN: What are tools you have made for yourself since the advent of AI?

155•aryamaan•8h ago•286 comments

Launch HN: Intuned (YC S22) – Build and run reliable browser automations as code

https://intunedhq.com
102•fkilaiwi•12h ago•44 comments

AI is slowing down

https://www.wheresyoured.at/ai-is-slowing-down/
409•crescit_eundo•10h ago•434 comments

Doing something that’s never been done before (2025)

https://talglobus.com/p/doing-something-thats-never-been-done-before/
29•surprisetalk•3d ago•20 comments

1worldflag: A blue dot on a transparent background

https://1worldflag.com/
174•davidbarker•1d ago•148 comments

Apple bets cheaper AI will woo small developers

https://techcrunch.com/2026/06/08/apple-bets-cheaper-ai-will-woo-small-developers/
17•jbernardo95•5h ago•7 comments

Games Between Programs: The Ruliology of Competition

https://writings.stephenwolfram.com/2026/06/games-between-programs-the-ruliology-of-competition/
10•andromaton•3d ago•0 comments

Show HN: Mach – A compiled systems language looking for contributions

https://github.com/octalide/mach
17•octalide•3h ago•5 comments

Asus GB300 NVL72 Test Lab Tour

https://www.lttlabs.com/articles/2026/06/06/asus-test-server-tour
5•LabsLucas•2d ago•0 comments

The Grate Cheese Robbery

https://longreads.com/2026/05/28/the-cheese-theft-food-crime/
9•RickJWagner•1d ago•0 comments

OCaml Onboarding: Introduction to the Dune build system

https://ocamlpro.com/blog/2025_07_29_ocaml_onboarding_introduction_to_dune/
142•andrewstetsenko•4d ago•20 comments

Massachusetts bans sale of precise location data in new privacy rights bill

https://techcrunch.com/2026/06/08/massachusetts-votes-to-pass-new-privacy-rights-bill-that-bans-s...
288•01-_-•9h ago•49 comments

Switzerland wil have a referendum to cap population at 10M

https://www.admin.ch/en/sustainability-initiative
249•napolux•7h ago•506 comments

Show HN: Command Center, the AI coding env for people who care about quality

https://www.cc.dev/
37•Darmani•4h ago•11 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?