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SectorC: A C Compiler in 512 bytes

https://xorvoid.com/sectorc.html
96•valyala•4h ago•16 comments

The F Word

http://muratbuffalo.blogspot.com/2026/02/friction.html
43•zdw•3d ago•7 comments

Brookhaven Lab's RHIC concludes 25-year run with final collisions

https://www.hpcwire.com/off-the-wire/brookhaven-labs-rhic-concludes-25-year-run-with-final-collis...
23•gnufx•2h ago•19 comments

Speed up responses with fast mode

https://code.claude.com/docs/en/fast-mode
55•surprisetalk•3h ago•54 comments

Software factories and the agentic moment

https://factory.strongdm.ai/
97•mellosouls•6h ago•174 comments

Stories from 25 Years of Software Development

https://susam.net/twenty-five-years-of-computing.html
100•vinhnx•7h ago•13 comments

Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
143•AlexeyBrin•9h ago•26 comments

OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
850•klaussilveira•1d ago•258 comments

I write games in C (yes, C)

https://jonathanwhiting.com/writing/blog/games_in_c/
138•valyala•4h ago•109 comments

First Proof

https://arxiv.org/abs/2602.05192
68•samasblack•6h ago•52 comments

Show HN: A luma dependent chroma compression algorithm (image compression)

https://www.bitsnbites.eu/a-spatial-domain-variable-block-size-luma-dependent-chroma-compression-...
7•mbitsnbites•3d ago•0 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
1093•xnx•1d ago•618 comments

Al Lowe on model trains, funny deaths and working with Disney

https://spillhistorie.no/2026/02/06/interview-with-sierra-veteran-al-lowe/
64•thelok•6h ago•10 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
235•jesperordrup•14h ago•80 comments

Start all of your commands with a comma (2009)

https://rhodesmill.org/brandon/2009/commands-with-comma/
519•theblazehen•3d ago•191 comments

Reinforcement Learning from Human Feedback

https://rlhfbook.com/
94•onurkanbkrc•9h ago•5 comments

Show HN: I saw this cool navigation reveal, so I made a simple HTML+CSS version

https://github.com/Momciloo/fun-with-clip-path
31•momciloo•4h ago•5 comments

Selection Rather Than Prediction

https://voratiq.com/blog/selection-rather-than-prediction/
13•languid-photic•3d ago•4 comments

Coding agents have replaced every framework I used

https://blog.alaindichiappari.dev/p/software-engineering-is-back
258•alainrk•8h ago•425 comments

The AI boom is causing shortages everywhere else

https://www.washingtonpost.com/technology/2026/02/07/ai-spending-economy-shortages/
186•1vuio0pswjnm7•10h ago•264 comments

A Fresh Look at IBM 3270 Information Display System

https://www.rs-online.com/designspark/a-fresh-look-at-ibm-3270-information-display-system
48•rbanffy•4d ago•9 comments

France's homegrown open source online office suite

https://github.com/suitenumerique
614•nar001•8h ago•272 comments

72M Points of Interest

https://tech.marksblogg.com/overture-places-pois.html
36•marklit•5d ago•6 comments

We mourn our craft

https://nolanlawson.com/2026/02/07/we-mourn-our-craft/
348•ColinWright•3h ago•413 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
124•videotopia•4d ago•39 comments

Where did all the starships go?

https://www.datawrapper.de/blog/science-fiction-decline
99•speckx•4d ago•115 comments

Show HN: Kappal – CLI to Run Docker Compose YML on Kubernetes for Local Dev

https://github.com/sandys/kappal
33•sandGorgon•2d ago•15 comments

Learning from context is harder than we thought

https://hy.tencent.com/research/100025?langVersion=en
211•limoce•4d ago•119 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
288•isitcontent•1d ago•38 comments

History and Timeline of the Proco Rat Pedal (2021)

https://web.archive.org/web/20211030011207/https://thejhsshow.com/articles/history-and-timeline-o...
20•brudgers•5d ago•5 comments
Open in hackernews

Meta Segment Anything Model 3

https://ai.meta.com/blog/segment-anything-model-3/?_fb_noscript=1
178•alcinos•2mo ago

Comments

trevorhlynn•2mo ago
This was front page for a while last week

https://news.ycombinator.com/item?id=45982073

stronglikedan•2mo ago
what is old is new again
dang•2mo ago
Thanks! Macroexpanded:

Meta Segment Anything Model 3 - https://news.ycombinator.com/item?id=45982073 - Nov 2025 (133 comments)

p.s. This was lobbed onto the frontpage by the second-chance pool (https://news.ycombinator.com/item?id=26998308) and I need to make sure we don't end up with duplicate threads that way.

Workaccount2•2mo ago
I do a test on multimodal LLMs where I show them a dog with 5 legs, and ask them to count how many legs the dog has. So far none of them can do it. They all say "4 legs".

Segment anything however was able to segment all 5 dog legs when prompted to. Which means that meta is doing something else under the hood here, and may lend itself to a very powerful future LLM.

Right now some of the biggest complaints people have with LLMs stems from their incompetence processing visual data. Maybe meta is onto something here.

jampekka•2mo ago
Segmentation doesn't need to count legs. I'd guess something like YOLO could segment 5 legged dogs too.
chompychop•2mo ago
YOLO is not a segmentation model.
jampekka•2mo ago
https://docs.ultralytics.com/tasks/segment/
lucasban•2mo ago
I thought it was a joke about YAML
chompychop•2mo ago
Thanks! TIL there's a class of segmentation models with the YOLO naming scheme.
Der_Einzige•2mo ago
Lol you obviously haven't seen what cheats for FPS games look like in the last 3 years.

https://github.com/Babyhamsta/Aimmy

PunchTornado•2mo ago
I doubt that gemini 3 cannot do it.
nerdsniper•2mo ago
You don’t need segmentation to count legs. Object detection can do that. DeepLabCut from 2020 perhaps.
the_duke•2mo ago
Side question: what are the current top goto open models for image captioning and building image embeddings dbs, with somewhat reasonable hardware requirements?
NitpickLawyer•2mo ago
Try any of the qwen3-vl models. They have 8, 4 and 2B models in this family.
Glemkloksdjf•2mo ago
I would suggest YOLO. Depending on your domain, you might also finetune these models. Its relativly easy as they are not big LLMs but either image classification or bounding boxes.

I would recommend bounding boxes.

smallerize•2mo ago
Which YOLO?
Glemkloksdjf•2mo ago
Any current one. they are easy to use and you can just benchmark them yourself.

I'm using small and medum.

Also the code for using it is very short and easy to use. You can also use ChatGPT to generate small exepriments to see what fits your case better

throwaway314155•2mo ago
There aren’t any YOLO models for captioning and the other models aren’t robust enough to make for good embedding models.
Glemkloksdjf•2mo ago
You can get labels out of the classifier and bounding box models.

They are super fast.

Its just an alternative i'm mentioning. I would assume a person knowing a little bit of that domain.

Otherwise the first option would be CLIP i assume. llm-vl is just super slow and compute intensive.

jabron•2mo ago
What do you mean "bounding boxes"? They were talking about captions and embeddings, so a vision language model is required.
Glemkloksdjf•2mo ago
I suggested YOLO and non llm-vl as a lot faster alternative.

Of course CLIP would be otherwise the other option than a big llm-vl one.

daemonologist•2mo ago
For pure image embedding, I find DINOv3 to be quite good. For multimodal embedding, maybe RzenEmbed. For captioning I would use a regular multimodal LLM, Qwen 3 or Gemma 3 or something, if your compute budget allows.
vessenes•2mo ago
Released last week. Looks like all the weights are now out and published. Don’t sleep on the SAM 3D series — it’s seriously impressive. They have a human pose model which actually rigs and keeps multiple humans in a scene with objects, all from one 2D photo (!), and their straight object 3D model is by far the best I’ve played with - it got a really very good lamp with translucency and woven gems in usable shape in under 15 seconds.
nl•2mo ago
https://ai.meta.com/blog/sam-3d/ for those interested.
Fraterkes•2mo ago
Are those the actual wireframes they're showing in the demos on that page? As in, do the produced models have "normal" topology? Or are they still just kinda blobby with a ton of polygons
seanw265•2mo ago
I haven’t tried it myself, but if you’re asking specifically about the human models, the article says they’re not generating raw meshes from scratch. They extract the skeleton, shape, and pose from the input and feed that into their HMR system [0], which is a parametric human model with clean topology.

So the human results should have a clean mesh. But that’s separate from whatever pipeline they use for non-human objects.

[0]: https://github.com/facebookresearch/MHR

daemonologist•2mo ago
For the objects I believe they're displaying Gaussian splats in the demo, but the model itself can also produce a proper mesh. The human poses are meshes (it's posing and adjusting a pre-defined parametric model).
vessenes•2mo ago
I’ve only used the playground. But I think they are actual meshes - they don’t have any of the weird splat noise at the edge of the objects, and they do not seem to show similar lighting artifacts to a typical splat rendering.
Qwuke•2mo ago
Between this and DINOv3, Meta is doing a lot for the SOTA even if Llama 4 came up short compared to the Chinese models.
visioninmyblood•2mo ago
you can download them at https://github.com/facebookresearch/sam3. for 3d https://github.com/facebookresearch/sam-3d-objects
retinaros•2mo ago
I looked quickly but it does not generate a 3d model file right?
phkahler•2mo ago
Which (if any) of these models could run on a RaspberryPi for object recognition at several FPS?
enoch2090•2mo ago
Surprisingly, SAM3 works bad on engineering drawings while SAM2 kinda works, and VLMs like Qwen3-VL works as well
retinaros•2mo ago
yeah I tried too. Im trying a fine tuning on PIDs.
enoch2090•2mo ago
Looking forward to your progress! Just checked the paper and it says the underlying backbone is still DETR. My guess would be that SAM3 uses more video frames during the training process and caused the dilution of sparse engineering-paper-like data.
zubiaur•2mo ago
Had good luck with Gemini 2.5, SAM3 failed miserably with PIDs.
shashanoid•2mo ago
Miss the old segment anything page, used it a lot. This UI I found very complex to use
bradyriddle•2mo ago
Same.

Checkout https://github.com/MiscellaneousStuff/meta-sam-demo

It's a rip of the previous sam playground. I use it for a bunch of things.

Sam 3 is incredible. I'm surprised it's not getting more attention.

stronglikedan•2mo ago
> I'm surprised it's not getting more attention.

Remember, it's not the idea, it's the marketing!

colkassad•2mo ago
Been waiting days to get approval to download this from huggingface. What's up with that?
knicholes•2mo ago
I was approved within about 10 minutes for "Segment Anything 3"
observationist•2mo ago
Alternative downloads exist. You can find torrents, and match checksums against the HF downloads, but there are also mirrors and clones right there in HF which you can download without even having to log in.
colkassad•2mo ago
Thanks, got it and it's working wonders for my use case.
tschellenbach•2mo ago
same here, didn't get approval
cheesecompiler•2mo ago
This would be convenient for post-production and editing of video, e.g. to aid colour grading in Davinci Resolve. Currently a lot of manual labour goes into tracking and hand-masking in grading.
aliljet•2mo ago
I wonder how effective this is medical scenarios? Segmenting organs and tumors in cat scans or MRIs?
maelito•2mo ago
I wonder if this can be used to track an object's speed. E.g. a vehicle on a road. It would need to recognize shapes, e.g. car model or average size of a bike, to guess a speed.
vanjoe•2mo ago
For a long time I've wanted to use something like this to remove advertisements from hockey games.The moving ads on the boards are really annoying. Maybe I'll get around to actually doing that one of these days.