“There’s no way to get there without a breakthrough,” OpenAI CEO Sam Altman said, arguing that AI will soon need even more energy.
Optimizing power consumption? Why?!
In fairness the computing world has seen unfathomable efficiency gains that are being pushed further with the sudden adoption of arm. We are doing our damnedest to make computers faster and more efficient, and we’re doing a really good job of it, but energy production hasn’t seen nearly those gains in the same amount of time. With the sudden widespread adoption of AI, a very power hungry tool (because it’s basically emulating a brain in a computer), it has caused a sudden spike in energy needed for computers that are already getting more efficient as fast as we can. Meanwhile energy production isn’t keeping up at the same rate of innovation.
The problem there is the paradox of efficiency, making something more efficient ends up using more of it not less as the increase in use stimulated by the greater efficiency outweighs the reduced input used.
It’s not so much the hardware as it is the software and utilisation, and by software I don’t necessarily mean any specific algorithm, because I know they give much thought to optimisation strategies when it comes to implementation and design of machine learning architectures. What I mean by software is the full stack considered as a whole, and by utilisation I mean the way services advertise and make use of ill-suited architectures.
The full stack consists of general purpose computing devices with an unreasonable number of layers of abstraction between the hardware and the languages used in implementations of machine learning. A lot of this stuff is written in Python! While algorithmic complexity is naturally a major factor, how it is compiled and executed matters a lot, too.
Once AI implementations stabilise, the theoretically most energy efficient way to run it would be on custom hardware made to only run that code, and that code would be written in the lowest possible level of abstraction. The closer we get to the metal (or the closer the metal gets to our program), the more efficient we can make it go. I don’t think we take bespoke hardware seriously enough; we’re stuck in this mindset of everything being general-purpose.
As for utilisation: LLMs are not fit or even capable of dealing with logical problems or anything involving reasoning based on knowledge; they can’t even reliably regurgitate knowledge. Yet, as far as I can tell, this constitutes a significant portion of its current use.
If the usage of LLMs was reserved for solving linguistic problems, then we wouldn’t be wasting so much energy generating text and expecting it to contain wisdom. A language model should serve as a surface layer – an interface – on top of bespoke tools, including other domain-specific types of models. I know we’re seeing this idea being iterated on, but I don’t see this being pushed nearly enough.[1]
When it comes to image generation models, I think it’s wrong to focus on generating derivative art/remixes of existing works instead of on tools to help artists express themselves. All these image generation sites we have now consume so much power just so that artistically wanting people can generate 20 versions (give or take an order of magnitude) of the same generic thing. I would like to see AI technology made specifically for integration into professional workflows and tools, enabling creative people to enhance and iterate on their work through specific instructions.[2] The AI we have now are made for people who can’t tell (or don’t care about) the difference between remixing and creating and just want to tell the computer to make something nice so they can use it to sell their products.
The end result in all these cases is that fewer people can live off of being creative and/or knowledgeable while energy consumption spikes as computers generate shitty substitutes. After all, capitalism is all about efficient allocation of resources. Just so happens that quality (of life; art; anything) is inefficient and exploiting the planet is cheap.
For example, why does OpenAI gate external tool integration behind a payment plan while offering simple text generation for free? That just encourages people to rely on text generation for all kinds of tasks it’s not suitable for. Other examples include companies offering AI “assistants” or even AI “teachers”(!), all of which are incapable of even remembering the topic being discussed 2 minutes into a conversation. ↩︎
I get incredibly frustrated when I try to use image generation tools because I go into it with a vision, but since the models are incapable of creating anything new based on actual concepts I only ever end up with something incredibly artistically compromised and derivative. I can generate hundreds of images based on various contortions of the same prompt, reference image, masking, etc and still not get what I want. THAT is inefficient use of resources, and it’s all because the tools are just not made to help me do art. ↩︎
It’s emulating a ridiculously simplified brain. Real brains have orders of magnitude more neurons, but beyond that they already have completely asynchronous evaluation of those neurons, as well as much more complicated connecting structure, as well as multiple methods of communicating with other neurons, some of which are incredibly subtle and hard to detect.
To really take AI to the next level I think you’d need a completely bespoke processor that can replicate those attributes in hardware, but it would be a very expensive gamble because you’d have no idea if it would work until you built it.
This dude al is the new florida man, wonder if it’s the same al from married with children
Unity developers be like.
Some of the smartest people on the planet are working to make this profitable. It’s fucking hard.
You are dense and haven’t taking even a look at simple shit like hugging face. Power consumption is about the biggest topic you find with anyone in the know.
Some of the smartest people on the planet are working to make this profitable. It’s fucking hard.
[Take a look at] hugging face. Power consumption is about the biggest topic you find with anyone in the know.
^ fair comment
The human brain uses about 20W. Maybe AI needs to be more efficient instead?
Perfect let’s use human brains as CPUs then. Not the whole brain just the unused bits.
I’ve seen that film
It’s what matrix would’ve been if the studios didn’t think people would too dumb to get it, so we ended with the nonsense about batteries.
They also thought we wouldn’t understand how Switch could be a woman in the matrix but a man in the real world. So they just made the character a butch woman because apparently that’s easier somehow. So many little changes like this were made.
Holy fuck now her name makes so much more sense. God dammit, why are we so fucking stuck up as a society that we couldn’t even keep that
Flubber!
We use all of our brain. Well, some of us try to anyway.
I would love it (if there exists a FOSS variant of that) imagine being able to run a LLM, or even LAM in your head,
wait…
🤔
FOSS Neuralink
That would require a revolutionary discovery in material science and hardware.
And yet we have brains. This brute force approach to machine learning is quite effective but has problems scaling. So, new energy sources or new thinking?
We just run the AI for a gazillion epochs and then it’s
overfittedevolved intelligence. Thanks Darwin we did it again.
It’d be way easier to just grow brains instead
We invented computers to do things human brains either couldn’t do, or couldn’t do fast enough.
If only we could convert empty hype into energy.
Well we can, we had a “jumpstyle” wave going on in the Netherlands a couple of years ago. No clue if it ever got off the ground anywhere else seeing as it was a techno thing or something.
It’s like crypto but sliiiighly better
It’s so, so, so much better. GenAI is actually useful, crypto is gambling pretending to be a solution in search of a problem.
So AI can’t exist without stealing people’s content and it can’t exist without using too much energy. Why does it exist then?
Because the shareholders need more growth. They might create Ultron along the way, but think of the profits, man!
There’s no way these chatbots are capable of evolving into Ultron. That’s like saying a toaster is capable of nuclear fusion.
Thats if you set the toaster to anything above 3
It’s the further research being done on top of the breakthrough tech enabling the chat bots applications people are worried about. It’s basically big tech’s mission now to build Ultron, and they aren’t slowing down.
What research? These bots aren’t that complicated beyond an optimisation algorithm. Regardless of the tasks you give it, it can’t evolve beyond what it is.
I think we’ve got a bit before we have to worry about another major jump in AI and way longer for an Ultron. The ones we have now are effectively parsers for google or other existing data. I personally still don’t see how we feel like we can get away with calling that AI.
Any AI that actually creates something ‘new’ that I’ve seen still requires a tremendous amount of oversight, tweaking and guidance to produce useful results. To me, they still feel like very fancy search engines.
The models get more efficient and smaller very fast if you look just a year back. I bet we’ll run some small LLMs locally on our phones (I don’t really believe in the other form factors yet) sooner as we believe. I’d say prior 2030.
I can already locally host a pretty decent ai chatbot on my old M1 Macbook (llama v2 7B) which writes at the same speed I can read, its probably already possible with the top of the line phones.
Lol, “old M1 laptop” 3 to 4 years is not old, damn!
(I have running macbookpro5,3 (mid 2009) on Arch, lol)
But nice to hear that M1 (an thus theoretically even the iPad, if you are not talking about M1 pro / M1 max) can already run llamma v2 7B.
Have you tried the mistralAI already, should be a bit more powerful and a bit more efficient iirc. And it is Apache 2.0 licensed.
3 to 4 years is not old
Huh, nice. I got the macbook air secondhand so I thought it was older. Thanks for the suggestion, I’ll try mistralAI next, perhaps on my phone as a test.
Because it’s a miracle technology. Both of those things are also engineering problems - ones that have been massively mitigated already. You can run models almost as good as gpt3.5 on a phone, and individuals are pushing the limits on how efficiently we can train every week
It’s not just making a chatbot or a new tool for art - it’s also protein folding, coming up with unexpected materials, and being another pair of eyes that will assist a person do anything.
They literally promise the fountain of youth, autonomous robots, better materials, better batteries, better everything. It’s a path for our species to break our limits, and become more.
The downside is we don’t know how to handle it. We’re making a mess of it, but it’s not like we could stop… The AI alignment problem is dwarfed by the corporation alignment problem
🙄 iTS nOt stEAliNg, iTS coPYiNg
By your definition everything is stealing content. Nearly everything in human history is derivative of others work.
How about an efficiency breakthrough instead? Our brains just need a meal and can recognize a face without looking at billions of others first.
I mean, we can only do that because our system was trained for hundreds of thousands, millions of years into being able to recognise others of same species
Almost all of our training was done without requiring burning fossil fuels. So maybe ole Sammy can put the brakes on his shit until it’s as fuel efficient as a human brain.
Food production and transport is famously a zero emission industry.
We’ve been around for hundreds of thousands of years as homosapiens. Food production and transport emissions were practically 0% until the last 100 years. So, yes, that’s right.
While that is true, a lot of death and suffering was required for us to reach this point as a species. Machines don’t need the wars and natural selection required to achieve the same feats, and don’t have our same limitations.
They are nowhere NEAR achieving the same feats as humans.
But the training has already been done, no?
Erm.
I recall a study about kids under a specific age that cannot get scared of looking at pictures of demons and other horror stuff because they don’t know yet what your everyday default person looks like.
So I’d argue that even people need to get accustomed to a thing before they could recognise or have an opinion about anything.
We still need to look at quite a few. And the other billions have been pre-programmed by a couple of billion years of evolution.
“recognize a face”
Who’s? Can the human brain just know what someone looks like without prior experience?
Your ability to do anything is based on decades of “data sets” that you’re being constantly fed, it’s no different than an AI they just get it all at once and we have to learn by individual experience.
Neurolink plus AI in 10 years is basically the matrix then.
Great right from coin miners to the “AI” fad. Tons of carbon shot into the sky and for what? A more unequal society on both counts.
At least AI has the potential to do something useful unlike coin mining. Although its not doing much currently so not to wild about it. Maybe real ai that could actually find new energy sources.
Or we could stop this ridiculous llm “ai” trend and move towards sustainable living like our hyper-waste society
These comments often indicate a lack of understanding about ai.
Ml algorithms have been in use for nearly 50 years. They certainly become much more common since about 2012, particularly with the development of CUDA, It’s not just some new trend or buzz word.
Rather, what we starting to see are the fruits of our labour. There are so many really hard problems that just cannot be solved with deductive reasoning.
It’s simultaneously possible to realize that something is useful while also recognizing the damage that a tech trend is causing from a sustainability standpoint.
Humans very rarely take sustainability into account when money can be made.
The lack of knowledge comes from thinking the damage is outpacing it’s usefulness. It simply isn’t.
Highly debatable
All it costs is power, one of the easiest things to make sustainable until we can make a computer that runs on beans.
AI is already too useful to give up, it’s not “ridiculous”
Why is it ridiculous?
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So is AI the new Blockchain?
Unlike the Blockchain it has an actual use tho.
I bought pizza with bitcoin, haven’t bought anything with AI yet.
I get daily use out of LLMs but haven’t done anything with Bitcoin.
I want to use Bitcoin to buy cannabis and Soylent and have it arrive at my door via drone. Give me my better future
Give an LLM to a high school student and they could do something with it.
Try to explain block chain to an adult and watch them pretend to understand.
Always was.
Exactly. This is why the AI hype train is overblown. Stop shoving “AI” everywhere when they know it’ll cost a lot in electricity.
The real path forwards with AI will be specialized super advanced models costing hundreds per run (business use case) and/or locally run AI using NPUs, especially the latter.
I love when people invent something then complain about how dangerous it is. It really hits you in the feels.
In the end, as always, it will only benefit the companies. And all the people get is put out of a job because they have been replaced by some piece of software no one even understands anymore.
This is a silly take, people have benefitted hugely from all the big tech developments in the past and will do from ai also - just as you have a mobile phone that can save and improve your life in a myriad of ways so you’ll have access to various forms of ai which will do similar. GPS is a good example, functionally free and making navigation far safer, faster, and better.
Here’s a genuine already happened use case for ai benefitting you, an open source developer was able to add a whole load of useful features to their free software by using AI to help code - I know because it was me, among many many others.
I know people making open source ai tools too and they’re all using AI coding assistants - mostly the free ones. I’ve seen a lot of academic researchers using AI tools also generally built using open source tools like pytorch and with help from ai coding tools. Even if you don’t use ai yourself you’re already benefitting from it, even if you don’t use open source software the services you rely on do.
Imagine being able to implement the most advanced and newest methodologies in your design process or get answers to complex and niche questions about new technology instantly. You buy a printer for example and say to your computer ‘I’ve plugged in a printer make it work’ and it says ‘ok, there isn’t a driver available that’ll work with your pc but I’ve written one based on the spec in the datasheet, do you want me to print a test page?’
Imagine being able to say ‘talk me through diagnosing a fault on my washing machine’ and it guides you through locating and fixing the fault, possibly by designing a replacement part and giving you fabrication options.
Or being able to say ‘this website is annoying, change it so that I only see the video window’ or ‘make a playlist in release order of all abba songs that charted’ or ‘check on currently available archives to see if there’s a mirror of this deleted post’ or ‘check all the sites and see if anyone posted a sub version of the next episode of this anime’ or ‘Keep an eye on this lemmy community and add any popular memes involving fish to my feed but don’t bother with any meta stuff or aquatic mammals’ or ‘this advert says I can make free money, is it ligit?’
The use cases that will directly benefit your life are almost endless, natural language computing is a huge deal even without task based solvers and physical automation but we also have those too so the increased ability of people to make community projects and freely shared designs is huge.
wasn’t the same thing said about ATM’s? and then it created the need for banks to hire more employees?
iirc, technology/robots has only been able to create more jobs, right? or am I misinformed?
The difference is the type of the job. Do we want to make jobs available for the general population and requiring minimal training, or do we want to make jobs available only for those with very difficult-to-get engineering degrees?
So much for hoping ai was going to solve energy breakthroughs.
Got to spend energy breakthroughs to make energy breakthroughs?
Nvidia Execs: Did you say the price of GPUs should go up?
Just don’t forget the BIG circuit breakers.
Some day we are going to need them.We must disassemble the solar system and make
paperclipsAI server farmsYes we will build a massive nursing home and use the old people as batteries.
