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car

4,092 karmajoined 19 years ago

Submissions

Nicotine pouches, tobacco's latest ploy

med.stanford.edu
4 points·by car·2 days ago·0 comments

Generative AI creates delicious, sustainable, and nutritious burgers

nature.com
1 points·by car·3 days ago·1 comments

Forge – Code-Quality Guardrails for AI Agents

github.com
3 points·by car·18 days ago·0 comments

Bootimus – A Self-Contained PXE and HTTP Boot Server

bootimus.com
125 points·by car·21 days ago·50 comments

An AI Co-Scientist for Hypothesis Generation from Google DeepMind

doi.org
4 points·by car·2 months ago·0 comments

Agentic Memory – The Follow Up

blog.mikiobraun.de
2 points·by car·2 months ago·0 comments

Startup Photreon aims to produce hydrogen with sunlight

heise.de
2 points·by car·3 months ago·0 comments

Criss-Cross Attention

jkobject.com
2 points·by car·3 months ago·0 comments

Bay Area Earthquake Showing Up in Sleep Tracking Data

santacruzworks.org
1 points·by car·3 months ago·0 comments

GPUs vs. TPUs: Decoding the Powerhouses of AI

savvycanary.com
1 points·by car·3 months ago·1 comments

Donald Knuth: Open Letter to Condoleezza Rice (2002)

www-cs-faculty.stanford.edu
13 points·by car·3 months ago·3 comments

Open Source 13" E-Ink Spectra Color Display with ESP32-S3

crowdsupply.com
4 points·by car·3 months ago·0 comments

The Housing Affordability Paradox - wealth transfer from young to old

thetwocents.substack.com
2 points·by car·3 months ago·0 comments

Nvidia DGX Station – The GB300 Grace Blackwell 748 GB VRAM Workstation

nvidia.com
9 points·by car·4 months ago·4 comments

Big Tech's Gulf megaprojects are trapped between two war choke points

restofworld.org
3 points·by car·4 months ago·0 comments

The Looming Taiwan Chip Disaster That Silicon Valley Has Long Ignored

nytimes.com
6 points·by car·4 months ago·1 comments

Semantic grep running locally on Apple Silicon via MLX

github.com
3 points·by car·4 months ago·0 comments

Llama.cpp performance breakthrough for multi-GPU setups

medium.com
1 points·by car·5 months ago·0 comments

[untitled]

1 points·by car·6 months ago·0 comments

Deep Learning Without Training

zenodo.org
3 points·by car·8 months ago·1 comments

comments

car
·21 days ago·discuss
https://stanforddaily.com/2016/07/25/knightscope-issues-repo...

https://incidentdatabase.ai/cite/51/
car
·27 days ago·discuss
Hey, Gabe Newell might be your man here. But it's not for profit.

https://luxurylaunches.com/transport/gabe-newell-explorer-ve...

https://www.forbes.com/sites/deajusufi/2026/06/13/gabe-newel...
car
·last month·discuss
Similar recent posting with optimizations for older Xeon:

High-Performance AI on a Budget: Optimizing llama.cpp for Qwen3.5 Inference on a Dual-GPU HP Z440

https://news.ycombinator.com/item?id=47320244
car
·2 months ago·discuss
Probably easier with Trellis 2 or Meshy.ai
car
·2 months ago·discuss
I don't know if this gets much personal use, seems real cumbersome.

But this is of huge interest to carriers, since it allows them to skip the PSTN/peering cost when the callee endpoint is an IP phone.

There is private ENUM for carrier use I recall, not sure what the current status is, with LTE/VoLTE, RCS etc.pp.

http://dam3d3.free.fr/PFE/Pathfinder/GSMA_PathFinder_WebSite...

Here the list of countries that have ENUM delegated for their country code.

https://www.itu.int/en/ITU-T/inr/enum/Pages/delegations.aspx
car
·2 months ago·discuss
In Germany it is possible to register an ENUM domain for a phone number. This provides a DNS mapping from the E164 number to DNS records, e.g. for IP phones, etc.

Decentralized and under user control, no shitty silos like FaceTime, WhatsApp.

ENUM stands for “Telephone Number Mapping.” It is essentially a bridge between the world of telecommunications and the Internet. With a single ENUM domain, you can combine all your contact options under your familiar phone number:

https://www.denic.de/en/products/enum-domains/
car
·2 months ago·discuss
The hierarchical geographical domains you are remembering must have been the 2000 '.geo' Top Level Domain (TLD) proposal from SRI. It didn't work out, but I remember thinking at the time that it was a cool idea.

It would have provided geographical information based on a domain encoded grid, not for human but machine consumption (e.g. acme.2e5n.10e30n.geo).

https://en.wikipedia.org/wiki/.geo

In a similar vein there is the 'e164.arpa' domain for mapping telephone numbers.

https://en.wikipedia.org/wiki/Telephone_number_mapping
car
·2 months ago·discuss
One of the gems that a publicly funded broadcasting system gave us.
car
·3 months ago·discuss
TPU architecture explained

https://news.ycombinator.com/item?id=47637597
car
·3 months ago·discuss
A 11 year old dupe, I know. But first time I’ve seen it, and it just added to my admiration for him. And, it’s just as applicable today as it was 24 years ago!

https://news.ycombinator.com/item?id=7567159
car
·3 months ago·discuss
Yes, they are listed on huggingface. The instruction trained models have an 'it' in their name.

https://huggingface.co/collections/unsloth/gemma-4

Edit: Sorry, I'm not sure if this is a quant, but it says 'finetuned' from the Google Gemma 4 parent snapshot. It's the same size as the UD 8-bit quant though.
car
·3 months ago·discuss
They explain it here:

https://unsloth.ai/docs/basics/unsloth-dynamic-2.0-ggufs

For the best quality reply, I used the Gemma-4 31B UD-Q8_K_XL quant with Unsloth Studio to summarize the URL with web search. It produced 4.9 tok/s (including web search) on an MacBook Pro M1 Max with 64GB.

Here an excerpt of it's own words:

Unsloth Dynamic 2.0 Quantization

Dynamic 2.0 is not just a "bit-reduction" but an intelligent, per-layer optimization strategy.

- Selective Layer Quantization: Instead of making every layer 4-bit, Dynamic 2.0 analyzes every single layer and selectively adjusts the quantization type. Some critical layers may be kept at higher precision, while less critical layers are compressed more.

- Model-Specific Tailoring: The quantization scheme is custom-built for each model. For example, the layers selected for quantization in Gemma 3 are completely different from those in Llama 4.

- High-Quality Calibration: They use a hand-curated calibration dataset of >1.5M tokens specifically designed to enhance conversational chat performance, rather than just optimizing for Wikipedia-style text.

- Architecture Agnostic: While previous versions were mostly effective for MoE (Mixture of Experts) models, Dynamic 2.0 works for all architectures (both MoE and non-MoE).
car
·4 months ago·discuss
I don't remember where I got them, but I think they could be copied with an EEprom programmer.
car
·4 months ago·discuss
Going down this rabbit hole, I realize that ST hardware for musicians is still huge. And the dongles as still working as intended, apparently.

And then this blew my mind:

https://re-falcon.com

Quite the underground scene:

https://indyclassic.org
car
·4 months ago·discuss
Is the software still attractive to use, after all those years, or why are you going to these extremes? Sounds it's somehow intimately intertwined with the dongle, if the check routines can't simply be patched.
car
·4 months ago·discuss
Didn't know, thanks for pointing that out. Never used GEM outside Atari, just something I read at the time.
car
·4 months ago·discuss
Wow, I just remembered using AES when I wrote an 'accessory' (menu bar app) that converted bitmap to vector for an ST DTP app that supported both. An early form of plugin I suppose. Pretty ahead of the MS mess at the time.
car
·4 months ago·discuss
Dongles were a thing, certainly the expensive MIDI programs used them. Cubase, Steinberg and C-LAB Creator were the big ones.

As I recall, there were tons of books about GEM for the Atari ST, at least in Europe.
car
·4 months ago·discuss
Apple sued DRI, which resulted in the crippling of GEM, the glaring one I remember were static windows. You heard that right, windows were not resizable but had fixed screen locations in the PC version.

Thankfully Atari licensed GEM for their 68000 machines before the lawsuit, and wasn't affected by these changes. The Atari ST (Sixteen/Thirtytwo) was very Mac like at the time. It even ran the Mac OS from Apple ROMs (Spectre 128 and Aladin) on its much cheaper hardware.
car
·4 months ago·discuss
When the Mac and Atari ST first hit the market in the 80's, there were Comics created in this 1-bit "ordered-dither" style. For error-diffusion dithering (Floyd-Steinberg etc.), you needed more bits per pixel, to carry the error.

SHATTER:

https://imgur.com/gallery/shatter-1984-was-first-commerciall...

Robot Empire:

https://www.reddit.com/r/atarist/comments/xgs4rh/comicbook_c...