I think it’s important for progressives to support this kind of signal in the conservative party, because the alternative is regressive back-sliding into bigotry. If we can reinforce a baseline of acceptance in Canada, that’s always going to be a good thing, because it means that we can reach even higher as progressives.
I would have been happy about this, since I generally support nuclear over the fossil fuel alternative, but I fear they’re only doing this to satisfy the AI data centre craze. Though I suppose when the bubble pops, we’ll be left with cheap abundant energy. The question then becomes; how much damage will data centres do before the pop.
Bernie has good intentions, but he was AI-pilled by Geoffrey Hinton, who ironically also has good intentions. However, they are both out of touch with reality.
Companies are only shooting themselves in the foot in the long term if they stop hiring junior engineers, and most of that work is not being replaced, it’s being shifted to the senior engineers who now have to babysit AIs that can’t actually do the job for any extended period of time. If you’re accepting AI code into a codebase without thorough review, then you’re also shooting yourself in the foot in the long term, because even the senior engineers won’t know the codebase after a while. If you’re doing thorough reviews in order to catch the AI bugs, well then you’re probably better off coding it yourself correctly in the first place, unless you’ve already allowed your skills to atrophy.
Do you really think AIs are reasoning when you ask them to troubleshoot technical issues? You may be lucky if the issue is already in their training data, but anything even slightly novel, and the AI is just going to bullshit an answer, and I guess you’re going to follow it blindly, since you don’t know enough to come up with an answer yourself.
Besides all that, how is open source AI going to stop junior developers from losing their jobs?
The word “intelligence” is doing a lot of heavy lifting here. LLMs lack any mechanism for true logical reasoning, and they always will by nature. This is why they fail at simple questions like “the car wash test”. It’s also why agents are expensive; They just flail around in token hungry “reasoning loops” until they happen to come across a correct solution. And it’s why Claude Opus 4.8 (High) only scores 1.5% on the ARC-AGI-3 benchmark at a cost of $10,000.
This kind of panic is just part of the hype. Wake me up when real intelligence arrives.
I like Ed, but not a fan of this style of teasing. Reminds me of conspiracy theory communities. We’ll see what he has I guess.
I dunno, seems like an honest editing mistake that is actually more likely to be human than AI generated. Probably should read “In particular in the last six months, but two things have changed dramatically over the last twelve months.”
Not to diminish your frustration, but the scary thing about this is that it’s happening in the workplace by professionals on a daily basis now. People have absolutely just surrendered all of their thinking abilities. What an absurd world. I wish I could be more certain about the bubble bursting, but we may have to live with the AI overview zombies for a while.
I agree. The political stupidity in the US basically forced us into a two-party election where the country was forced to choose between two evils and Carney looked like a reasonable savior at the time. We sacrificed NDP representation to save ourselves from Trump. Carney quickly abandoned any resemblance of environmental concern in the name of economic growth and sovereignty. The same is happening with AI now, where he’s playing to the hype and business interests. Except AI is largely a grift and this strategy will do more harm than good.
people are afraid of losing their jobs to AI.
Nah, it’s more like they’re pissed their bosses will attempt to replace their jobs with AI that can’t actually do their job, and instead shift that work onto the remaining employees. It’s AI-washing to hide cost-cutting.
global Beef production uses around 200 times more fresh water than Global Data Centers
Whataboutism. We’re not the ones using shitty fallacies as arguments. Fuck beef consumption too.
Water cooling can be done in a smaller space with less power, but it requires enormous amount of water. A recent study determined that a single hyper-scaled facility would need 1.5 million liters of water per day to provide cooling and humidification.
AI is typically deployed in 20-30 cabinet clusters at or above 40 KW per cabinet. This represents a fourfold increase in KW/cabinet with the deployment of AI. The difference is staggering.
reasonable jurisdictions like British Columbia in Canada
They’re also not building the damn things right next to millions of residential homes
Hundreds of people marched through Vancouver on Saturday to protest two planned AI data centres in the city, raising concerns about the amount of water and energy such facilities can use as the region faces tighter water restrictions.
The project has the backing of the B.C. government
The City of Vancouver is also throwing its support behind the proposal
The protest comes as Metro Vancouver remains under Stage 2 water restrictions, which bans lawn watering, and prepares for the likely move to Stage 3 restrictions sometime in June.
“I think this is an incredibly inefficient use of land, both in the heart of downtown Vancouver and Mount Pleasant”
The noise thing is… nothing.
Jason Haley, who’s lived in his Southaven home for the last two decades, in August started to hear a whirring, mechanical noise from outside that sounded like a leaf blower.
The noise would go on for days at a time and through the night, he told Mississippi Today. He soon realized the sounds were coming from a cluster of natural gas turbines about a half mile away.
Over the summer, billionaire Elon Musk’s artificial intelligence company set up shop in north Mississippi, erecting dozens of turbines on the site of a former power plant to fuel two data centers just up the road in Memphis.
I’m going to have to start using a browser extension to label trolls like the reddit days.
Yeah, their title is dumb, but they do actually touch on some of that in the article.
The two of you are using the word “generalist” differently. You don’t need your tool-using language model to be able to wax poetic about ancient egyptian burial practices. That’s why ChatGPT will become useless. It’s too large and expensive to continue running without subsidies, and it’s too useless for serious tasks. You can get away with a small local model that knows nothing about ancient egypt if all you need is to translate natural language into tool calls.
Not sure where /u/Canaconda got that text from, but the official release on their website does not mention “female workers”. https://www.ndp.ca/news/ndp-reaction-liberal-government-ai-strategy
Fortunately, I don’t think the judge will ask them to do that.
I don’t understand this form factor. It’s too small for any serious work, both in terms of screen size and typing, and it’s too big to fit in your pocket. So you might as well carry a small laptop around, since it would actually be usable. Feels like a novelty that is just meant to satisfy a cyberpunk aesthetic, if you’ve got the money to burn on something that you’ll probably only use a few times, or occasionally at best.
If you go through with sterilisation then allow yourself to check out, please.
What the fuck?
With high-density computing, like the data centers that run artificial intelligence, comes immense heat that cannot be cooled with a conventional air-cooling system.
The typical cabinet loads have doubled and tripled with the deployment of AI. An air-cooling system simply cannot capture the heat generated by the high KW/cabinet loads generated by AI cabinet clusters.
Water cooling can be done in a smaller space with less power, but it requires enormous amount of water. A recent study determined that a single hyper-scaled facility would need 1.5 million liters of water per day to provide cooling and humidification.
AI is typically deployed in 20-30 cabinet clusters at or above 40 KW per cabinet. This represents a fourfold increase in KW/cabinet with the deployment of AI. The difference is staggering.
A typical Chat-GPT query uses about 10 times more energy than a Google search – and that’s just for a basic generative AI function. More advanced queries require substantially more power
Season 4 Episode 23 https://en.wikipedia.org/wiki/Living_Witness
Alternate holographic recreation of Voyager where the crew is evil. The episode opens with a scene on the “warship Voyager”, an alternate Voyager with a brutal, sadistic crew.
Genuinely considering a trip to Winnipeg to see the exhibit and support this museum. I hope other people do to and that it stays up for a long time. In fact, I’m going to donate to the museum right now.
From another article:
https://www.winnipegfreepress.com/breakingnews/2026/06/26/protesters-denounce-controversial-exhibition-at-rights-museum