For the 2nd or 3rd time this week I've seen someone comment on a new data centre build with a stat about how 80% of data is never accessed. Then they talk about the energy and cooling used in modern DCs.
The reality is that data storage is actually incredibly efficient, and uses fuck all power. A hard disk is less than 10w and stores multiple users data.
Storing data, our photos, our memories, our history. Is not the problem.
The thing driving the need for the bigger more power and water hungry data centres is AI. Sparkling autocarrot. Where as a machine in a rack full of hard disks might consume a couple of hundred watts. A machine loaded up with a typical load of 8 "AI accelerators" can be pulling in the region of 5kw. Over an order of magnitude more power than the energy needed to store the lifes photos of hundreds of people.
I've worked in this industry for over a quarter of a century.
At no point have I found myself thinking "I wish I could just ask the computer to write this email for me" "I wish the computer could write my code for me". MS is adding co pilot function to lots of products. Not as opt in. But opt out. And it's a right hassle to turn it off? Why? So someone can ask it to right a longer email from a prompt that the recipient can then ask the AI to summarise for them ?
There are certainly some areas where machine learning (note, I'm not calling it AI) has it's uses. Medical research springs to mind. But a ubiquitous AI assistance rolled into all our products? Why? It's just using too much power, too many resources, and for what ? Sparkling autocarrot.
Encoding the worst of our society in a bit stream. Exacerbating inequality, prejudice, and hate.
In comp sci there's a term. GIGO. Garbage in. Garbage out.
These large language models are being fed on the combined mass of the world's online content. Your tweets, Facebook posts, forum posts, that blog you forgot you started. All of it is being fed into the black box of the LLM. The internet provides us unprecedented access to the world's information. But it is also an unprecedented collection of hate. We've seen this time and time again. From chat bots that start shouting nazi propaganda, to CV vetting systems that won't hire women.
And what makes this even more terrifying is that when you look at a webpage, it's often hard to tell if it's been generated with sparkling autocarrot, or written by a human. If we can't tell, then what hope does the LLM? And so we're gonna end up with the next generation models being fed on the output of the previous. This is going to create feedback loops. Reinforcing the worst the model has to offer. Strengthening the hate. The prejudice.
And because we don't know what has been created how. There's no way to control what feeds the models. It's just gonna enshitify. And fast.
AI has all the hallmarks of a bubble. Like crypto before it, and half a dozen other bubbles before that, that all share their heritage right back to the south sea bubble (no, not tulip mania, but that's something for a different thread).
Except this bubble has gone more mainstream. It's consuming way more resources. Than any before it.
Water is going to become the next big inequality front. As the climate changes. Clean fresh water is going to become harder to come by. More expensive, and more unequal. That same water is being poured over panels I'm data centres to cool the servers. To cool the AI accelerators, generating content noone asked for. Enshitifying the knowledge base of humanity. Just so a few people can make some money.
@quixoticgeek why is fresh water being used to cool data centers? The data center machines could care less if it is clean or not. That seems a big oversight.
(And before someone says salt water corrodes, why the f would you need to put the water right against the machines, it just needs to absorb thermal energy, not make out with it.)
@davidaugust because humans are near the systems. And warm water is a great place for nasty bugs.
The water doesn't go near the machines (except in a few very modern cases). It's used to cool the air con for the room the machines are in. Using evaporative cooling. Use unclean water, and these evaporative coolers become a major biohazard.
@quixoticgeek I see. So using a scarce resource, without which humans cannot exist is the trade off chosen to avoid heating freshwater and making it…something humans cannot exist with.
Seems to me the two curves likely intersect and switch places at some point.
In a wiser world fantasies like harnessing the thermal energy put out by the data center to help power the data center would be entertained. It instead the cheap extraction of money without investing in something that works long term is what we’re left with. Not great.
@quixoticgeek@davidaugust Sorry, but the thermodynamics don't work out. The waste heat from datacenters just isn't hot enough to transfer any distance at all. You can use it to gently warm the building, but that's it. Lots of heat energy, yes - but not a lot of temperature. If you want waste heat for district heating you need something hotter, like certain industrial processes. Generally people don't want to live next to a cement kiln though.
Storing our data, our memories, our photos, on servers in data centres that are built in sensible places isn't inherently a bad thing. And we shouldn't allow ourselves to fall for the trope of 80% of it is never accessed. But building datacentres that use ten times the energy, and need even more water, in deserts, and water stressed areas, to drive sparkling autocarrot that noone asked for. That we should be more vocal about.
@quixoticgeek as a practical matter, don't think we can guilt trip users into pretending a given convenience a) isn't cool after all or b) should not be used. People get into accidents because they're idiots and use their cell phones while they're driving. Even so, cell phones are part of life now.
What we can do is tax/regulate the hell out of large commercial entities that, in making cool new tech convenient, move us 1 cm closer to climate disaster. You don't get to make money for doing that.
I might suggest that we agree to disagree on the question of whether AI is cool. It's an inherently subjective assessment.
Hope you're not suggesting that users don't find applications that incorporate AI useful. That's what determines whether it's useful or not. Whether people use it.
Consumer markets, which is what we're talking about, make subjective lurches like this all the time. We don't expect markets to be logical.
@quixoticgeek
two questions from non tech person
1
Isn't it possible new tech, quantum computers or whatever, will reduce the energy need for AI by 10x, 100x, whatever ?
2
given the mind bending progress in computers over the last 40 years, how on earth can one feel confident about predicting where AI will be in 10, 20 years?
I mean, are you really saying you know what AI will be in 10 years ?
@failedLyndonLaRouchite@quixoticgeek 1) Planning as if a theoretical and unresearched future technology (in your question, quantum computing for machine learning, specifically) will fix the problems we are currently creating is not a plan, it's wishful thinking. Should that tech come to pass, we can consider how to use it. Not the other way round.
Specifically text or image generation, "GenAI" is limited by the underlying theory, such as it is, to more or less what it's doing now. /cont
@failedLyndonLaRouchite@quixoticgeek ... There are various tweakable parameters around the training and the use pieces, but there is no actual theory for how this works, all of this is basically a massive brute-force attempt to describe human language and art (both as such, not specific instances) as math equations. Which kinda explains why it takes so incredibly much computing power. Research in this area is predominantly funded to find "better tweaks", not "a theoretical basis". /cont
@failedLyndonLaRouchite@quixoticgeek Such a theoretical basis, where we could describe how and mathematically prove why this works at all, might allow a major leap. But there are no indications that significant earnest work is even being attempted.
So that's why many of us in tech are convinced that this currently hyped branch of machine learning is already dead, it just doesn't know it yet (and will be incredibly wasteful until it does).
@quixoticgeek Clear and compelling warning about natural consequences of current round of commercialization of AI research!
The threat to drinking water might be less severe -- Microsoft (and maybe others?) have been researching "underwater datacenters" in deep sea water to manage the cooling needs,
@bobhy underwater datacentres are unfortunately still a gimmick. They are too difficult to service the content. And sticking stuff in the sea is not a panacea. The heat still goes somewhere. You heat up the water around the DC, that changes the ecosystem. We see this with the vents for the cooling water at nuclear power stations. The warm water changes the wildlife there.
@quixoticgeek I'd like to highlight that "AI" isn't actually anything new, its just larger than ever now. Which is why this serverfarm issue isn't new. Before it mostly came in the form of surveillance advertising & personalized recommendations.
Our need for an income is what drives waste!
The legit value of serverfarms (though I am sympathetic to arguments that we over-rely on this) is near-entirely in data storage/publishing. And message routing.
@quixoticgeek There's this great paper where the researcher tried to train a ML to identify serious Covid cases, and what it learned was that the seriously ill patents were all scanned lying down, so lying down was flagged as a major indicator
In spite of, or perhaps also because of, all the carping and contentions in the comments, many of which have good points, as does this thread of posts, I think it is all, posts and comments, well worth reading.
I would wish for better tone in some of the comments; I think more "yes, and" than "no, but" would be more appropriate.
@quixoticgeek
And if we store our memories on our own hard drives and our backups on our own external drives they cannot be stolen and used to train LLMs and ..... (OK not stolen because some cryptic language in the TOS nobody reads says they can)
@quixoticgeek The problem isn't storing the data. The problem is finding it again!
A lot of organisations end up with terabytes of rubbish accumulating because storage is dirt cheap and it's not worth spending valuable employee-hours having someone rummage through it and make the decisions of which files are worth keeping.
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