De-google-ify Internet
Amazing campaign by the French not-for-profit association Framasoft.
The De-google-ify Internet project offers 26 ethical and alternative online tools that may be used by everyone.
They build open source alternatives to many Google services like Youtube, Agenda, Docs, Forms, Maps etc, as well other services to replace Doodle, Facebook Event, Github, Zoom, Slack and much more!
Check their beautiful website, watch the videos to know more about their work and follow them here in Mastodon:
https://degooglisons-internet.org/
#europe #opensource #europeanalternatives #EUtech #boycott #degoogle #google
Dang, videogame graphics these days are hardcore. I remember being more than satisfied with DOOM back in the day and now each leaf and pebble looks realistic with fancy lighting effects everywhere.
I think I'm warming up to using local LLMs for helping me code. I don't trust them for large scale code generation but it's started saving me some time in looking up syntax and docs via DuckDuckGo. I still need to look up docs for most of the work I do but not so much for common use cases you'd find on stack overflow.
nazi techbro avoidance
Over the past month, I've been doing my best to de-mega-corp my tech ecosystem.
My conclusion: unless you are a skilled tech nerd with money and are willing and able to do it, it's basically impossible to not be exploited by your tech.
Tech's current state is abusive in all the worst ways, and frankly it should be illegal.
Tech professionals should be ashamed by what we have wrought.
#python tips for folks getting started.
Don't use the system-level python as that can update and break dependencies. E.g. Arch uses 3.13 if you update and Tensorflow can't go above 3.12.
Use pyenv to do version management per project. https://github.com/pyenv/pyenv
Don't install pip dependencies globally. Use virtualenv to set up dependencies per project. https://virtualenv.pypa.io/
Python versioning is rough out of the box and these tips can save you some pain.
The appeal of machine learning to me is how clean the actual structure of models can be once you split it up in the right layers.
A lot of "application" code is a tangled web of dependencies and small independent or coupled bits of state that you need to coordinate in bizarre ways to account for the difficulty of state management in distributed systems.
ML on the other hand needs maths knowledge but the blocks fit together in a nice clean linear way of input to output.
I'm seeing a lot of folks making the same suggestion, and now I'll say it too:
Use Amazon like a catalog you browse.
Find a thing you want.
Go to the manufacturer's site (NOT their Amazon "store!").
Buy it there. Often you'll find coupons or discount codes NOT present on Amazon.
[Edit: I live in the so-called UnitedStates. You may not. Even if you do, your experience may differ from mine. Use what you can/choose to from the suggestion and ignore the rest. This is about doing our best, to the best of our ability, under what are becoming uncertain and possibly extraordinary circumstances.]
Found this #techno banger via tiktok. Very cyber.
https://soundcloud.com/nikolachenmusic/nikola-chen-lippo-pippo
Occult Enby that's making local-first software with peer to peer protocols, mesh networks, and the web.
Exploring what a local-first cyberspace might look like in my spare time.