Save The Planet
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A lot of things are solved, but capitalism means that we need a profit motive to act. World hunger is another good example. We know how to make fertilizer and how to genetically alter crops to ensure we never have a crop failure. We have trains and refrigeration to take food anywhere we want. Pretty much any box that we need to check to solve this problem has been. The places that have food problems largely have to do with poverty, which at this point is a polite way to say "I won't make money, so I am okay with them starving"
Im not sure what's the point here? If we dont like LLMs and data centers using power then we use existing strategies that work like taxing their power use and subsidizing household power use which btw we're already doing almost everywhere around the world in some form or another.
The data centers are actually easier to negotiate and work with than something like factories or households where energy margins are much more brittle. Datacenter employs like 5 people and you can squeeze with policy to match social expectations - you can't do that with factories or households. So datacenter energy problem is not that difficult relatively speaking.
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In moderate climates in the US, peak loads are typically the hottest and sunniest hours of the day since condenser units are the most energy-hungry appliance in most homes. Clouds notwithstanding, peak solar generation would typically align (or closely align) with peak load time.
Batteries would also help a lot - they should definitely be subsidizing the installation of those as well but unfortunately they aren't yet (at least not in my state).
Why do you want a subsidy for batteries?
Installing batteries at a large scale at homes is incredibly expensive compared to an off site battery. Especially with regards to the move towards hydrogen. -
Where are you getting your false information. Its certainly not the most used. And, the reason it's used at all is from advertising and ownership of the media by the billionaire class to shove the gibbity in our faces at every waking moment so people use it. They're losing money like never before on ai.
wrote on last edited by [email protected]This level of collective delusion is crazy. I don't think any amount of stats will change your mind so you're clearly argueing in bad faith but sure:
https://explodingtopics.com/blog/chatgpt-users says 5.2B monthly visits compared to Facebook 12.7 and Instagram's 7.5. Chatgpt is literally bigger than X.com already. Thats just one tool and LLM's have direct integrations in phones and other apps.
I really don't understand what's the point of purposefully lying here? We can all hate billionaires together without the need for this weird anti-intellectual bullshit.
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I mean, continued use of AI encourages the training of new models. If nobody used the image generators, they wouldn't keep trying to make better ones.
you are correct, and also not in any way disagreeing with me.
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It's closer to running 8 high-end video games at once. Sure, from a scale perspective it's further removed from training, but it's still fairly expensive.
really depends. You can locally host an LLM on a typical gaming computer.
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You underestimate the number of people you wouldn't class as intelligent. If no one wanted massive trucks, they would have disappeared off the market within a couple of years because they wouldn't sell. They're ridiculous, inefficient hulks that basically no one really needs but they sell, so they continue being made.
It's actually because small trucks were regulated out of the US market. Smaller vehicles have more stringent mileage standards that trucks aren't able to meet. That forces companies to make all their trucks bigger, because bigger vehicles are held to a different standard.
So the people who want or need a truck are pushed to buy a larger one.
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This curve has changed somewhat since this study in 2016. More efficient home insulation, remote working, and energy-efficient cooling systems have large impact in this pattern. But assuming you have a well-insulated home, setting your thermostat to maintain a consistent temperature throughout the day will shift this peak earlier and lower the peak load at sunset, when many people are returning home. More efficient heat pumps with variable pressure capabilities also helps this a lot, too.
Given just how many variables are involved, it's better to assume peak cooling load to be mid-day and work toward equalizing that curve, rather than reacting to transient patterns that are subject to changes in customer behavior. Solar installations are just one aspect of this mitigation strategy, along with energy storage, energy-efficient cooling systems, and more efficient insulation and solar heat gain mitigation strategies.
If we're discussing infrastructure improvements we might as well discuss home efficiency improvements as well.
wrote on last edited by [email protected]Do you have a source for the cooling off effect of the duck curve?
Following is a 2 year old article hinting an increase in the effect https://www.powermag.com/epri-head-duck-curve-now-looks-like-a-canyon/ afaik it hasn't changed much but I'm open to news
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79 is like my ideal temp. Cities must love me.
My parents would love you.
I don't even want to go to their house in the summer. I can't even think at that temperature.
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Im not sure what's the point here? If we dont like LLMs and data centers using power then we use existing strategies that work like taxing their power use and subsidizing household power use which btw we're already doing almost everywhere around the world in some form or another.
The data centers are actually easier to negotiate and work with than something like factories or households where energy margins are much more brittle. Datacenter employs like 5 people and you can squeeze with policy to match social expectations - you can't do that with factories or households. So datacenter energy problem is not that difficult relatively speaking.
I am agreeing with you that the solutions exist, but the will to implement them is going to be the hard part. A big dampener is simply going to be the profit motive. There is more money in siding with the data center than a the households. Are households okay with an increasing in price? Data center is likely to manage that better, or even just pay a bribe to someone. I used food as another example of a problem that is solved. We can grow food without fail and build the rail to get it to where it needs. We just don't because need does not match profit expectation. There are talks of building nuclear power for some data centers, but such talk would not happen for normal households.
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I know she's exaggerating but this post yet again underscores how nobody understands that it is training AI which is computationally expensive. Deployment of an AI model is a comparable power draw to running a high-end videogame. How can people hope to fight back against things they don't understand?
wrote on last edited by [email protected]She's not exaggerating, if anything she's undercounting the number of tits.
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really depends. You can locally host an LLM on a typical gaming computer.
You can, but that's not the kind of LLM the meme is talking about. It's about the big LLMs hosted by large companies.
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really depends. You can locally host an LLM on a typical gaming computer.
wrote on last edited by [email protected]Well that's sort of half right. Yes you can run the smaller models locally, but usually it's the bigger models that we want to use. It would also be very slow on a typical gaming computer and even a high end gaming computer. To make it go faster not only is the hardware used in datacenters more optimised for the task, it's also a lot faster. This is both a speed increase per unit as well as more units being used than you would normally find in a gaming PC.
Now these things aren't magic, the basic technology is the same, so where does the speed come from? The answer is raw power, these things run insane amounts of power through them, with specialised cooling systems to keep them cool. This comes at the cost of efficiency.
So whilst running a model is much cheaper compared to training a model, it is far from free. And whilst you can run a smaller model on your home PC, it isn't directly comparable to how it's used in the datacenter. So the use of AI is still very power hungry, even when not counting the training.
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I know she's exaggerating but this post yet again underscores how nobody understands that it is training AI which is computationally expensive. Deployment of an AI model is a comparable power draw to running a high-end videogame. How can people hope to fight back against things they don't understand?
How about, fuck AI, end story.
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really depends. You can locally host an LLM on a typical gaming computer.
Yeh but those local models are usually pretty underpowered compared to the ones that run via online services, and are still more demanding than any game.
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Do you have any data to support this is actually the case? I see this all the time but absolutely zero evidence but a 2015 Axios survey with no methodology or dataset. Nearly every article cites this one industry group with 3 questions that clearly aren't exclusive categorical and could be picked apart by a high school student.
I ask this question nearly every time I see this comment and in 5 years I have not found a single person who can actually cite where this came from or a complete explanation of even hope they got to that conclusion.
The truck owners I know, myself included, use them all the time for towing and like the added utility having the bed as as secondary feature.
The truck owners I know, myself included, use them all the time for towing and like the added utility having the bed as as secondary feature.
Then you put it beside a truck from 30 years ago that's a quarter the overall size but has the same bed capacity and towing power along with much better visibility instead of not being able to see the child you're about to run over. And then you understand what people mean when they say massive trucks - giant ridiculously unnecessary things that are all about being a status symbol and dodging regulations rather than practicality.
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really depends. You can locally host an LLM on a typical gaming computer.
wrote on last edited by [email protected]True, and that's how everyone who is able should use AI, but OpenAI's models are in the trillion parameter range. That's 2-3 orders of magnitude more than what you can reasonably run yourself
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Climate change is unstoppable. Humanity is mostly doomed very, very soon.
So, fuck y'all, my two window units are running 24/7 @ 69F for the foreseeable future.
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Why do you want a subsidy for batteries?
Installing batteries at a large scale at homes is incredibly expensive compared to an off site battery. Especially with regards to the move towards hydrogen.For the same reason we want to subsidize solar production in residential construction even though it's more efficient and cost-productive to do it at-scale. Having energy production and storage at the point of use reduces strain on power infrastructure and helps alleviate the types of load surging ayyy is talking about.
It's not a replacement for modernizing our power grids, too - it simply helps to make them more resilient.
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And I guess they need it to be inefficient and expensive, so that it remains exclusive to them. That's why they were throwing a tantrum at Deepseek, because they proved it doesn't have to be.
wrote on last edited by [email protected]Bingo.
Altman et al want to kill open source AI for a monopoly.
This is what the entire AI research space already knew even before deepseek hit, and why they (largely) think so little of Sam Altman.
The real battle in the space is not AI vs no AI, but exclusive use by AI Bros vs. open models that bankrupt them. Which is what I keep trying to tell /c/fuck_ai, as the "no AI" stance plays right into the AI Bro's hands.
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How about, fuck AI, end story.
how about, fuck capitalism? Have you lost sight of the goal?
