

I have my full setup in github with details of all my various plugins I use here!
I have my full setup in github with details of all my various plugins I use here!
Once I got so used to all my custom keybinds in neovim, it became hard to use anything else.
I’m used to tools like Harpoon for fast jumping around “bookmarked” spots in my code, once i started using the same technique for my writing it’s like something clicked for me, I was like “holy shit I can arbitrarily jump to spots so fast now…”
I use neovim a lot for coding.
Over time though I discovered it had tonnes of amazing features as a prose editor too, so many powerful plugins for editing prose that blew me away.
Stuff like “warn me if I use tthe same word too much” and whatnot.
And of course telescopes fuzzy find made jumping around to edit my text way faster, and being able to bulk change stuff with a simple :%s/.../.../g
feels real good.
I highly recommend folks try out nvim for this use case :3
The 1 seat they got was in the green party stronghold (co leaders home town)
I have zero clue what her platform is, prolly environmentalist tho.
If any vote ever fails in our government, it triggers an instant re-election. It’s called the Vote of Non Confidence
It’s probably one of the most key parts of why our government is a little bit more resistant to clown-showing, because even a small crack in the parliament triggers a new election.
So bills can only be tabled if the gov is 100% confident it will have the votes.
Which means the conservatives could table a bill if they knew the NDP + Bloc would side with them on it, as then they have the votes to pass it.
But since it’s the NDP, a very progressive party, it means they actually hold that fine balance of mediating power between liberals and conservatives.
It’s pretty solid actually, and makes it so everyone the entire term could pass a reasonable bill.
Pretty sure this last term the conservatives and liberals did agree on some stuff and some bills passed with both approving it, iirc.
I think forcing them to occasionally work together like that helps temper the fascism lol.
Bloc have endorsed the liberals already, Quebec is extremely anti trump.
Bloc aligning with conservatives would be political suicide lol.
Atm we got it, this is the magic sweet spot where we want to be
172 seats exactly with lib+ndp+green
and conservatives can’t even threaten a vote of non confidence with bloc’s help. (1 vote short)
But they could trigger it with that 1 green seat’s help, which means liberals have to stay on the good side of that 1 green seat XD
The big key is gonna be if we get that sweet 172 seats with Lib+Green+NDP, we are only 1 seat short
If we hit that mark it means, hilariously, the one single green seat is needed to form a majority government without bloc’s help needed
Which will force liberal party to play ball with NDP and Green Party’s more progressive policies.
That’s our ideal scenario, conservatives are told to go kick rocks, and green/ndp get an actual voice on decision making to push the country in a progressive direction.
One. More. Seat!
Wow, that sure is something else.
This genuinely made me do an IRL spit take, holy shit.
Same, but they did set up a self hosted instance for us to use and, tbh, it works pretty good.
I think it’s s good tool specifically for helping when you dunno what’s going on, to help with brainstorming or exploring different solutions. Getting recommended names of tools, finding out “how do other people solve this”, generating documentation, etc
But for very straightforward tasks where you already know what you are doing, it’s not helpful, you already know what code you are going to write anyways.
Right tool for the right job.
I’m sorry they put tarrifs on uninhabited islands lol
I primarily use GPT style tools like ChatGPT and whatnot.
The key is, rather than asking it to generate code, specify that you dont want code and instead want it to help you work through the solution. Tell it to ask you meaningful questions about your problem and effectively act as a rubber duck
Then, after you’ve chosen a solution with it, ask it to generate code based on all the above convo.
This will typically produce way higher quality results and helps avoid potential X/Y problems.
Humans are “trained” with maybe ten thousand “tokens” per day
Uhhh… you may wanna rerun those numbers.
It’s waaaaaaaay more than that lol.
and take only a couple dozen watts for even the most complex thinking
Mate’s literally got smoke coming out if his ears lol.
A single Wh
is 860 calories…
I think you either have no idea wtf you are talking about, or your just made up a bunch of extremely wrong numbers to try and look smart.
Humans will encounter hundreds of thousands of tokens per day, ramping up to millions in school.
An human, by my estimate, has burned about 13,000 Wh by the time they reach adulthood. Maybe more depending in activity levels.
While yes, an AI costs substantially more Wh
, it also is done in weeks so it’s obviously going to be way less energy efficient due to the exponential laws of resistance. If we grew a functional human in like 2 months it’d prolly require way WAY more than 13,000 Wh
during the process for similiar reasons.
Once trained, a single model can be duplicated infinitely. So it’d be more fair to compare how much millions of people cost to raise, compared to a single model to be trained. Because once trained, you can now make millions of copies of it…
Operating costs are continuing to go down and down and down. Diffusion based text generation just made another huge leap forward, reporting around a twenty times efficiency increase over traditional gpt style LLMs. Improvements like this are coming out every month.
For sure, much like how a cab driver has to know how to drive a cab.
AI is absolutely a “garbage in, garbage out” tool. Just having it doesn’t automatically make you good at your job.
The difference in someone who can weild it well vs someone who has no idea what they are doing is palpable.
Good, fire 2 devs out of 3.
Companies that do this will fail.
Successful companies respond to this by hiring more developers.
Consider the taxi cab driver:
With the invention if the automobile, cab drivers could do their job way faster and way cheaper.
Did companies fire drivers in response? God no. They hired more
Why?
Because they became more affordable, less wealthy clients could now afford their services which means demand went way way up
If you can do your work for half the cost, usually demand goes up by way more than x2 because as you go down in wealth levels of target demographics, your pool of clients exponentially grows
If I go from “it costs me 100k to make you a website” to “it costs me 50k to make you a website” my pool of possible clients more than doubles
Which means… you need to hire more devs asap to start matching this newfound level of demand
If you fire devs when your demand is about to skyrocket, you fucked up bad lol
We are having massive exponential increases in output with all sorts of innovations, every few weeks another big step forward happens
Wait til you realize that’s just what art literally is…
You skipped possibility 3, which is actively happening ing:
Advancements in tech enable us to produce results at a much much cheaper cost
Which us happening with diffusion style LLMs that simultaneously cost less to train, cost less to run, but also produce both faster abd better quality outputs.
That’s a big part people forget about AI: it’s a feedback loop of improvement as soon as you can start using AI to develop AI
And we are past that mark now, most developers have easy access to AI as a tool to improve their performance, and AI is made by… software developers
So you get this loop where as we make better and better AIs, we get better and better at making AIs with the AIs…
It’s incredibly likely the new diffusion AI systems were built with AI assisting in the process, enabling them to make a whole new tech innovation much faster and easier.
We are now in the uptick of the singularity, and have been for about a year now.
Same goes for hardware, it’s very likely now that mvidia has AI incorporating into their production process, using it for micro optimizations in its architectures and designs.
And then those same optimized gpus turn around and get used to train and run even better AIs…
In 5-10 years we will look back on 2024 as the start of a very wild ride.
Remember we are just now in the “computers that take up entire warehouses” step of the tech.
Remember that in the 80s, a “computer” cost a fortune, took tonnes of resources, multiple people to run it, took up an entire room, was slow as hell, and could only do basic stuff.
But now 40 years later they fit in our pockets and are (non hyoerbole) billions of times faster.
I think by 2035 we will be looking at AI as something mass produced for consumers to just go in their homes, you go to best buy and compare different AI boxes to pick which one you are gonna get for your home.
We are still at the stage of people in the 80s looking at computers and pondering “why would someone even need to use this, why would someone put one in their house, let alone their pocket”
As a Canadian, all I can say is “hey wait a minute, I’ve seen this one before!”
I’m shocked this sorta shit still happens in 2025, how did this come into being? Thus might be a rabbit hole I go down, who founded this program, who vetted it, etc