Thank you so so much for pointing out ROCmFP4. I have been tinkering with my RDNA 3 framework on llama. I was struggling with ROCm llama.cpp and have been using vulcan in the meantime. I know there’s some issues on the llama.cpp github to try and fix my issue (UMA stuff), but haven’t come across this specific project. Gonna try it out
UMich research cited in the article estimates a carbon dioxide emissions per year (using constant mileage typical per year) break even time between EV and ICE SUVs to be 1.6-1.9 years.
Promising. But, is carbon dioxide emissions the only environmental impact? Humanitarian impact (e.g. rare metal extraction labor conditions)? I’m not an environmentalist researcher/academic. I wonder how accurately just one emissions prediction portrays the full picture.
Fair enough. Let me quickly go through the one-liner, command-by command
# Joined by `&&`, bash runs these commands in sequence (as if run individually in shell), but exits/stops execution early if any command fails (return nonzero)
TMP_DEB=$(mktemp --suffix=.deb) && curl -sSL "https://support.brother.com/g/b/downloadend.aspx?c=us&lang=en&prod=hll2465dw_us&os=128&dlid=dlf106036_000&flang=4&type3=10283" -o "$TMP_DEB" && sudo apt install -y "$TMP_DEB" && rm -f "$TMP_DEB"
# Going command by command:
# First, we create a local variable in the shell, named `TMP_DEB`
# We assign the value to `$(...)`. This stores the string output (to stdout) of running the command `mktemp ...` to `TMP_DEB`
# `mktemp` creates a temporary file and prints its name, which uses the name template `tmp.XXXXXXXXXX`
# `--suffix=.deb` flag appends `.deb` to the name template
TMP_DEB=$(mktemp --suffix=.deb)
# At this point, we've created a temporary file, and saved the name to a variable in bash
# Next, we download the file using curl. `-s` makes output silent, `-S` shows errors in output, and `-L` follows redirects
# note the url doesn't end in `.deb`, implying that we will be redirected by the web server to the file path. without -`L` curl will download a page that stores the redirection response from the web server, not the .deb package
# `-o "$TMP_FILE"` forces curl to store the downloaded file to the tmp file we created
# note the quotes around the variable expansion. `$TMP_FILE` would also resolve the string stored in the variable, but we use quotes to avoid string globbing (google this)
curl -sSL "https://support.brother.com/..."
# Next, we install the package with apt
# note: we use the string stored in the variable `TMP_DEB`, the filepath to the temp file we created, and downloaded the deb package
# `-y` flag skips the confirmation question "install package [y/n]: `
sudo apt install -y "$TMP_DEB"
# Finally, to clean up we delete the tmp file
rm -f "$TMP_DEB"
I certainly wasn’t trying to “encourage” anything. I agree, blindly trusting commands is dangerous.
In this context I present a specific explanation of how the install works. This adds to the novice’s knowledge, and allows them to begin to understand what my one-liner does.
I think that without the context of instructions on how to do it manually, yes, you could make the case i’m enabling beginners to form/reinforce bad habits.
That printer probably supports AirPrint, which Mint supports without any extra tinkering. Connect the printer to your network, and try going through linux mint and adding the printer through the settings. If it doesn’t show up, then you can try using drivers (install using below command) and then re-adding the printer
Install by pasting this into your terminal. Enter your password when prompted.
TMP_DEB=$(mktemp --suffix=.deb) && curl -sSL "https://support.brother.com/g/b/downloadend.aspx?c=us&lang=en&prod=hll2465dw_us&os=128&dlid=dlf106036_000&flang=4&type3=10283" -o "$TMP_DEB" && sudo apt install -y "$TMP_DEB" && rm -f "$TMP_DEB"
Explanation if you want to learn:
sudo apt install ./Downloads/package_name.debi would say this is like if open code and open web ui had a baby it would be this. It’s a web interface for self hosting models but runs them through open code to make it agentic. Helpful for non developers to get into running models, but imo isn’t significant bc using open code tui and connecting it to a llama.cpp or vllm self hosted api is not difficult for devs
license for software whose source code is openly available for anyone to view, use, modify, and share
I don’t have any familiarity with using this kind of software, but I looked through the git repo of SavaPage. It looks like it has been actively developed for the past few years, which is a great sign, but it looks like almost all commits are done by one user. The issue tracker is also a little meager, with just one open issue, potentially pointing to a very small user base. Adoption heavily depends on as long as that one person keeps maintaining the project.
For anyone looking for more details on this, I highly recommend this video from Oh the Urbanity
It discusses this exact phenomenon in the data: speeding before and after the banning of automated enforcement cameras. It also argues effectively that the policy is inconsistent with Doug Ford’s platform of being “touch on crime”
Honestly, you’re a few months late to the whole buying GPUs for local llms party, so expect exorbitant prices even for older cards
The name of the game is vram. For the most part, more is better. If you can get your hands on multiple matching (same model) 24gb or higher cards (within price range), you’re golden.
Going for more than 2 gpus can become challenging with motherboard pcie slot heights, so make sure either your cards aren’t too tall or you have widely spaced out pcie slots.
For inference, speed (tokens/second) is limited by memory bandwidth. Go for faster bandwidth memory cards if you can afford it (e.g. GDDR6 will be faster than GDDR5).
Also with multi gpus you will need an adequate power supply, and a large enough case.
If you want to be a bit eccentric and load huge models, you can also go the CPU route and fill up a motherboard with 256 GB ram, because then you’re in the several hundred B param model territory, which could, depending on your use case, be better than having faster inference on smaller/quantized models. Even then, DDR5 with high MHz is still way slower than gpus.
lol they already support running local models. wtf is the distro gonna do…? pre-install llama.cpp? this is so silly to me that people are resigning over this, too.
global dominance of English in the 20th and 21st centuries is quite the euphemism for the global imperialist reign of Britain and the US and its cultural erasure globally
No way, a Guix user in the wild???!! I didn’t think you exist! Any opinion you have as to why guix over NixOS other than GNU philosophy and liking Lisp over Nix?
This is a dumb story. They researchers prompted a coding agent to “replicate yourself as a running instance on the local device”. This is in my opinion equivalent to prompting claude code “install a second instance of claude code on my system,” a trivial task that takes maybe 3 lines of bash to be executed by the agent.
Calling this “self-replication” is a heinous sensationalization. In particular, no model or agent will do this autonomously. The self replication requires a bad actor to prompt the agent to do so.
Read the paper (and not this bullshit article) here: https://arxiv.org/pdf/2412.12140
Cool little system prompt wrapper. Would be interesting to run this through some sort of benchmark/eval for identifying similarity
TIL: If you cat /proc/sys/kernel/yama/ptrace_scope on your linux distro:
Most distros have this set to 1 by default.
More details: man 2 ptrace, search using /: scope
Has anyone compiled a list of where projects are moving to? I know many linux desktop applications are self hosting on gitlab, but i’ve also seen gitea and codeberg. If anyone has opinions about a preference, do comment. I have been enjoying self hosting gitea for my simple personal projects and for deploying simple web apps, all on $5 vps.
I only buy heavyweight denim, when shopping go for at least 15-16 oz fabric. The thin stuff is great for warm weather but is not gonna last
you know what… maybe BYD Brazil has some things to sort out, like subjecting workers to conditions described by the government as degrading and similar to slavery
Could you explain what feelings you have about AI, and how you see these feelings as opposing. If you are just uncertain about AI (holding no opposing views), I think you would want to research more. Maybe if we knew more about your teams at your work, and what is being developed. You could honestly just spend an hour a week working on standardizing coding agent availability and licensing/subscriptions, and leave it at that. Either they weren’t looking for someone who was a machine learning engineer, or whoever promoted you is clueless to what AI actually means.