Addressing AI’s energy cost
numenta.com
numenta.com
I'm a huge fan of energy efficieny, but this figure isn't all that much. Let's put things into perspective using some (probably somewhat inaccurate but probably somewhere in the ballpark) random internet sources, showing that this is less energy than a single long haul Boeing 747 flight. (CO2 footprint is probably different but somewhere in the ballpark.)
https://science.howstuffworks.com/transport/flight/modern/qu...
> A plane like a Boeing 747 uses approximately 1 gallon of fuel (about 4 liters) every second. Over the course of a 10-hour flight, it might burn 36,000 gallons (150,000 liters). According to Boeing's Web site, the 747 burns approximately 5 gallons of fuel per mile (12 liters per kilometer).
(I didn't find the right type of gallon where 36000 gallons == 150000 liters, but let's go with the liter figure anyway.)
According to https://en.wikipedia.org/wiki/Energy_density, 1 liter of kerosene has an energy content of 35 MJ. 150000 liters of kerosene have an energy content of 5250000 MJ. 5250000 MJ is 1458.333333 MWh.
Add another dubious source just to check our calculations (this one uses a larger fuel tank, but we'll re-use the previous figure):
https://www.withouthotair.com/c5/page_35.shtml
> And fuel’s calorific value is 10 kWh per litre. (We learned that in Chapter 3.)
150000 l * 10 kWh/l = 1500000 kWh = 1500 MWh, so about the same.
Considering the way AI can potentially bring benefits to humanity, i see it more like an investment.
For comparison, Bitcoin in 2021 used 110 TWh, solving a problem we've either solved millenea ago, or could be solved using much less power with premined coins.
Inference is still done on GPUs, and is not cheap by any means. The number of GPUs you need to run the full 175B GPT-3 model in inference is vastly inferior to what you need during training, but the numbers of replicas of the model running in the backend to serve all customer's requests is vastly superior.
So it's more akin to a 747 being bought by OpenAI and kept continuously running than just one transatlantic flight.
Their “Ada” tier is 75 times cheaper, with corresponding upper-bounds assumptions if they are not making a loss.
[0] https://www.wolframalpha.com/input?i=1500+MWh+*+%2460%2FMWh+...
What CPU did you benchmark on that gave you a cheaper inference price than GPU? In my experience, for GPT like transformers, they don’t come anywhere near what you can squeeze out of something like a Nvidia T4 in terms of either performance or $/token.
How? mining new coins doesn't cost energy, preventing double-spends does. Premining wouldn't make any difference
Proof of stake or some other non proof of work consensus mechanism could reduce the energy usage
Oh wait, most mining operations are in the millions of dollars range, nevermind the fact that 84% of all BTC is held by .3% of addresses with > 100 BTC...
Both PoW and PoS have centralisation, but PoS vastly increases this centralisation, does it at a far faster rate, and "locks it in" (there is no feasible way to overcome the most powerful node in PoS, this is not the case thankfully in PoW)
Cardano Solana Polkadot Tron Avalanche
Ethereum is also on a roadmap to migrate to proof of stake
[1] https://blog.ethereum.org/2016/12/04/ethereum-research-updat...
you are right, but never underestimate the collective stupidity of large software departments where they retrain every time someone makes a commit into their CI/CD pipelines.
As for the glorified chatbot is of course one of the applications of AI, but i refuse to believe it has a very complex model, and the computational power required to use the model is also modest enough that most smartphones can execute it without any noticeable impact on battery life.
On the smaller scale, most of Apple's AI stuff is running on-device[4]. From iOS 15 all of Siri's "voice to text" happens on-device as well. While it's probably still a glorified chatbot, i for one enjoy being able to enter "pet autumn 2019" into my photo search bar, and be shown pictures of pets taking during autumn 2019, regardless of location.
[1]: https://engineering.berkeley.edu/news/2021/08/using-machine-...
[2]: https://medium.com/mlearning-ai/machine-learning-in-fraud-de...
[3]: https://www.sciencedirect.com/science/article/pii/S026840121...
Besides, in my part of the world at least, i haven't carried cash in a decade or more, and most people i know don't either. Money is increasingly only a digital thing that exists in your (also digital) bank account.
Even "micro payments" between individuals is being handled here, for a decade or so, by MobilePay[1] on the domestic side, and PayPal on the international side, with Apple Pay looking to be a close contestant to both, at least for the 55-60% of the population using iPhones.
Crypto is nowhere as anonymous as everybody appears to believe. Every single transaction is on the blockchain, and can be traced from acquisition to being spent. Considering that all European exchanges are now obliged to report their customer details to the authorities (under the KYC of AMLD-V EU directive), it becomes a relatively simple matter to trace your money to crypto transactions.
Fortunately, Europe isn’t hit as hard with the customer profiling as the US is, and the EU is rather intent on protecting privacy, so your data purchase history is available only to youths relevant parties.
In case of MobilePay, the service provider can of course see the details, but all my bank sees is a text I’ve input when sending money, or what the sender has input. It still gets reported to the tax authorities.
How was this estimated? Is that for the final model run, how about all the testing runs, funs that failed, parameter tuning runs etc. are those included?
Not an attack on your figures or your claims, just saying you've not addressed the point you set out to address.
Some flights run totally empty (airlines need to keep their precious routes) which uses a marginally smaller amount of fuel than a full plane, but provides no real value (nobody was transported to a location they wanted to be in). Other flights are normal, but also carry an individual of great importance, or play a strategic role.
Some training runs waste a bunch of power and then get thrown away. Others go on to serve users and make billions of dollars.
The energy cost is only a proxy for the fully loaded "value" of what you create with your energy consumption. That's why it's not comparable.
The one issue is that translating electricity usage into fossil fuel equivalents for this specific application, without contextual information about similar energy demands, such as streaming video, data collection/storage/processing (be it at Google or the NSA), total router energy consumption in the global Internet, etc. might result in a distorted view of the relative importance of energy demand for their particular issue (training complex models).
Furthermore, it's not necessary to generate electric power with fossil fuels, is it? My view is that solar/wind/storage is the optimal global-scale solution, but placing energy-hungry steady-load data centers near baseload nuclear power plants is arguably an efficient solution (ask the insurers first, however). Hydropower is region-specific and as the drought shows, subject to going offline when needed most to run AC etc. It's not inevitable that power demands equate to fossil carbon emissions, in other words.
I got into AI after a grad school career split between mathematical signal processing and computational neuroscience. I knew folks back in the early 2010's looking at joining Numenta. The ideas are absolutely good to explore, it's the execution that's lacking. Maybe their big breakthrough is just around the corner, but how long do you wait for product 1 alpha build 1 before calling out vaporware?
The article is marketing to folks who care about the environment, but have limited background on modern ML (and perhaps also energy economics).
[1] https://ai.googleblog.com/2021/03/accelerating-neural-networ... [2] https://ai.googleblog.com/2022/03/robust-graph-neural-networ... [3] https://ai.googleblog.com/2021/04/multi-task-robotic-reinfor... [4] https://cloud.google.com/tpu/docs/tpus
A biological neuron has two kinds of dendrites: distal and proximal. Only proximal dendrites are modeled in the artificial neurons we see today.
Nerve cells in the brain also have what, ~20 different chemical neurotransmitters modulating the state of the neuron in question, and this looks a lot more analog than digital... any kind of one-to-one correspondence between biological brains and digital learning networks never seemed all that realistic to me.
Can I build a Google photos competitor using spiking neural nets for content recognition? Can i train GPT-4 with 50% of the power bill of GPT-3? Can i dare hope for better accuracy or robustness for some production task? Or better compressed nets for edge computing? I'm not seeing anything like that. We've known a long time that ANNs as implemented today are very crude compared to biological neurons; they really just share a name. What's supposed to differentiate a company from a lab is taking that insight and doing something concrete with it.
Having said that, in Crypto it's a much more compelling argument because it's like "Here are some obvious, big costs that are fundamental to the system, and there are almost no benefits" whereas in AI the nature of these algorithms is that we're likely to improve them, so comparing training GPT-3 is kind of like measuring the power draw of the LHC. It's certainly big and it's certainly something we can talk about, but no one thinks we're going to be building 100,000 LHCs.
For AI, sure, for crypto (if PoW), no.
If energy was a tenth of the cost, PoW crypto would use 10 times more.
Supply of energy is limited, and so there is a market effect: overconsumption by some players can increase the cost to other consumers.
Market economics should mean that the resulting increase in profit margin turns into an opportunity for more-cost-effective competitive entrants.
Most of this assumes no collusion between players in the market. If, for example, company A provides a product that is knowingly energy-inefficient and half of their board members also sit on the board of energy company B that is experiencing record profits -- and could easily acquire company C that theoretically has a cheaper energy production solution -- then perhaps problems could occur.
0: https://www.smithsonianmag.com/smart-news/five-percent-power...
https://www.enerdata.net/publications/executive-briefing/bet...
The more reliable government resources dont even seem to bother to list IT as a major energy consumer, although its obviously embedded in most / all traditionally recognized sectors.
https://www.enerdata.net/publications/executive-briefing/bet...
I'd love to know more about all this but thats about as far as my late night googling had taken me.
Whatever specific idea you have in mind is either not commonly held, not sensible, or both uncommon and non-sensible. If it was both common and sensible, we’d already be doing it.
https://www.nytimes.com/2021/05/28/business/energy-environme...
https://davidsuzuki.org/living-green/air-travel-climate-chan...
etc.
There is a grassroots campaign for more restrictive legislation on air travel, but it's early there's lots of progress for us to make still.
It seems to assume a disembodied "brain in a vat" model, as if brains aren't ordinarily attached to a large clump of flesh that typically attempts to accumulate as many resources as it can, and often enjoys combusting large quantities of fossil fuels hurtling around in various metal enclosures.
I suppose we could be very efficient at image classification once AWS announces their new h5.large "MT bare human" instances, where gigantic banks of people are set to work solving CAPTCHAs with their incredible performance per watt specs.
Or we could redo the analysis with other cherry-picked measures and find the "human architecture" is orders of magnitude less efficient at multiplying large integers, and come to the conclusion that we should replace all babies (which have a wasteful decades-long training period) with ARM chips.
Amazon already did that, it is called mechanical turk.
It costs a lot of money because we think those computers should have rights. But under more permissive legislations it would be so cheap and accessible that we wouldn't need to do much of the modern AI research. I assume this is what they meant, with slavery there would be much less need to do AI research, self driving cars is hard but slave driven cars is easy, the whole point of AI is that it lets us create slaves that we don't feel bad about abusing.
That's what the "MT" stands for :)
> the whole point of AI is that it lets us create slaves that we don't feel bad about abusing.
Yes, that's exactly right. The article glibly compares the energy efficiency of AI with the human brain, completely ignoring any other concerns, and pretends it means something.
Playing by those sets of rules would enable the sorts of analyses I outlined above.
But I think the article's specific claims about image recognition (they use the example of identifying pictures of cats) are completely false:
- The article claims models must be retrained from scratch if they are to identify cartoon cats instead of real cats. This is absolutely false and transfer learning is old hat by machine learning standards.
- The article cites the fact that an image recognition model "requires many weights and lots of multiplication", as an example of inefficiency, as if human brains don't encode trillions of weights in the connections between their billions of neurons.
- If AI models could only identify a few hundred photos per hour, this would undoubtedly be used as evidence of inefficiency. By the same token, if we consider the cost of training amortized over the subsequent cost of image identification, image recognition models are are far more efficient at scale than humans, even if we grant massively overstated estimates of training costs.
- All humans must go through an incredibly expensive, labor-intensive training process, before which they will completely fail to reliably identify a cat.
- Humans required billions of years, the death and suffering of trillions of organisms, the terraforming of an entire planet, and vast amounts of energy to run a stupidly inefficient Monte Carlo "pretraining" phase.
I can't help but come away with the feeling that I've been trolled. They managed to pick image recognition, an area where efficient AI models approach or exceed human performance, to prop up an absurdly myopic comparison that wouldn't make sense even if they got any of the details right.
We humans don't start from a blank/random slate like ANNs when we are born.
We might be efficient in some regards but we surely didn't get there efficiently.
I bet YouTube/Facebook/Instagram/TikTok/NetFlix spend orders of magnitude more resources uploading/transcoding/streaming videos than all the AI models training costs put together.
a) Stop using the term carbon footprint. It was invented by BP to scapegoat and market, it defocuses us. b) Blaming tech or civilians doesn't help. Blame countries. China, U.S, Germany etc need to step up. Ban coal power production -- coal industrial power combustion and mining is everything bad including radioactive (https://www.scientificamerican.com/article/coal-ash-is-more-...) -- promote nuclear. c) At this point add serious teeth to treaties. Countries not taking steps are costing future lives and resources. We are going nowhere otherwise.
P.S. Practically, too many powerful countries have serious incentives to offload responsibility, and as this is a prisoners dilemma game in the sense one cheating screws everyone, that there are no peaceful means to achieve this goal. So let's not kid ourselves.
The EU's border-adjustment scheme isn't perfect. But it's in the right direction. Clean up your own act. Assign a broad-brushed adjustment to goods coming from dirty origins and use the proceeds to (a) further clean up your act or (b) incentivise others to clean up theirs.
But that is a step that might, and I say might, with a lot of salt help. The problem is we don't see this happening. Germany, for instance, was increasing their coal mining volume prior to the Russia Ukraine war and were not going to make the independence goal.
P.S. I was going to edit my comment to add the efficacy of sanctions and other similar measures, but yours covers it. Thank you for your comment.
One peaceful way to do it is to develop clean technology that is cheaper than the dirty way.
Then every one will quit the dirty tech, out of greed.
Alongside training AI models, Spaceflight is the other issue that comes to mind. These things look bad because of "big" numbers or plumes of soot coming out of engines, but when added up they account for such a small fraction of emissions that they won't be useful focuses for a long time.
Focusing on them now detracts from places where we can have real impact: human transport, cargo transport, food production, clothing manufacture, carbon capture, and so on.
> Many large companies, which can train thousands upon thousands of models daily, are taking the issue seriously.
No they don't. Because:
> Continuing to build larger and more computationally intensive deep learning networks is not a sustainable path to building intelligent machines.
If they'd care, they would evaluate how they threaten humanity's future by emitting more CO2 versus how they improve humanity's future with the services they provide.
Instead, they start from the idea that their services are a non negotiable absolute net positive (TBH it's obvious since it's their raison d'être)) and that CO2 is a negative that can be managed. Whereas, to me, it's the opposite: CO2 is an absolute non negotiable negative and the services might be changed or removed.
Pretty much all new data centers are powered using renewables. Not because it's cleaner but because it's cheaper. If your main consumable is a lot of electricity, you are going to want to source it cheaply. Which these days means the same as using renewables. Mostly that's a mix of them generating their own power and supplementing that with renewable energy on the local market. That has been the case for quite a few years, which is why companies like Google and Amazon figured out that they were also helping themselves financially by pushing hard for carbon neutral well over a decade ago.
So, whatever goes on in those newer data centers is pretty much not emitting any co2. Aside of course from manufacturing of hardware and construction of the site, which would be a separate topic.
Some of the older data centers are still powered via coal/gas plants, especially in the US. Those will likely clean up their act in the next few years. All the big cloud providers have announced roadmaps for becoming carbon neutral. Once that is done, data centers will use a lot of energy that is generated sustainably.
That doesn't mean that there aren't issues around this. E.g. the Netherlands is reluctant to host more data centers because they are claiming all the sustainable energy that is available in the local market and they have to worry about powering the rest of the country in a sustainable way too. And since that costs a lot of money, having Facebook or Google then get subsidized to use all of the newly available wind power looks a bit bad.
But all that means is that there's a lot of healthy demand for clean power that short term outstrips supply. Lots of companies are working to tap into that rapidly growing market. Which is good news for our planet. Any market that supplies a lot of clean & cheap energy can expect to see businesses trying to make use of that. Especially energy intensive businesses like data centers. So, there's a great incentive for governments around the world to make that happen.
So, perhaps the wrong reflex is to argue that we should all become Luddites to reduce demand on renewable energy. The right response is to argue for sourcing your cloud services sustainably. Most cloud providers can probably tell you which of their data centers are clean and which aren't. They might not be very vocal about dirtier ones but you can choose which regions you host in and which ones you skip and make some educated guesses. Interesting way to nudge them a little harder. That's on you, not them. Not a lot of companies do that yet. But they could. And IMHO they should.
So easy to trigger anybody, much fun.
the stuff about inspiration from the brain confuses me too... it reads a bit like neither ai nor neuroscience is particularly deeply understood. its very basic stuff.
Or, and hear me out, using energy to push society forward isn't necessarily bad.
Maybe instead of vilifying every new technology that uses energy for the last 20 years, including the internet: (Dig more coal the PCs are coming https://www.forbes.com/forbes/1999/0531/6311070a.html?sh=56f...), perhaps the impetus should be on incentivizing green energy production.
Anything less than producing more energy more cleanly is missing the point. Long term energy usage trends do not go down.
I should note that I am not against fusion and absolutely think we should be doing it. However, it's my feeling and something that I'm trying to learn about that we should also be doing many other things. For example, conservation of land and habitats is no longer viable. We have got to be restoring these things as best we can if we have a chance against climate change. I think it should be renamed environmental change, because that's more accurate and paints the more serious picture. Climate change seems to phrase it in very human-centric terms. We also need another economic system whose end goal isn't corporate world domination. We need an economic model that drives innovation but also redistributes and is sustainable. What's interesting is that this is exactly what nature accomplishes. But humans have gone off the rails in terms of consumption. However, with our adaptability and technology, we have been able to continually consume more and more, whereas other animals (e.g., rabbit populations) cannot continually exist outside of some bounds and are checked. What's interesting is trying to understand where our bound or what our check is going to be. I have a feeling that our destruction will eclipse our adaptability and technology at some point. It will not be pretty when that happens.
There has got to be a nice graph that correlates power usage with these things, but I have yet to find it.
Do you have any resources on those topics? I'd like to learn more about that how cheap electrical energy enables those.
Here’s his channel: https://youtube.com/channel/UCZFipeZtQM5CKUjx6grh54g
The TLDR summary for your quotation is: Complete recycling — with enough energy you can break everything into atoms; Very land efficient agriculture — the cost of glass and metal for greenhouses and desalination is mostly energy, likewise most of the stuff needed to make vertical farming worth considering.
(I don’t remember Isaac Arthur mentioning ocean cleanup, but that may just be flawed memory).
These are all the things which allow us to live in a modern society with a high quality of life. More power is a more modern higher quality of life for more people, citing the last few hundred years.
As for everything else, we've barely even scratched the surface of this rock we're standing on - to say nothing of the rest of the dist system.
> More power is a more modern higher quality of life for more people, citing the last few hundred years.
Nor do I think that is a given fact. More people starve today than there were people alive a few hundred years ago.
>Nor do I think that is a given fact. More people starve today than there were people alive a few hundred years ago
So no credit for feeding the billions who eat on the back of modern, energy intensive, fertilizer production?
One of the very things destroying the environment and negatively affecting public health?
> So no credit for feeding the billions
This isn't school and human lives and people are not statistics. The question to ask is "at what cost?". Does feeding those billions suddenly do anything to help the 800 million or so starving in a world that has enough to feed them? What about the illions of animals and plants humans have destroyed over the past few hundred years? Again, at what cost?
A related aside: when humans originally started to utilize agriculture in the beginning of human history, the overall affect was a net negative in health, life expectancy, and efficiency (i.e., time spent working).
The world population in 1820 was about 1093 million.
I'm not against fusion at all, but it is important to remember that carbon dioxide isn't the only problem harming the planet.
We have economic democracy, participatory economics and good old Freiwirtschaft (can be translated as free (as in freedom) economics by Silvio Gesell.
>What's interesting is that this is exactly what nature accomplishes
Capitalism only allows for growth, whenever the economy isn't growing, people get fired and you have an economic recession or depression. Freiwirtschaft simply allows for both growth and decay. There is no discontinuity i.e. recession and no unemployment when the economy isn't growing. People will keep working to maintain their existing capital, that includes restoring nature.
https://www.statista.com/statistics/201794/us-electricity-co... https://www.statista.com/statistics/183457/united-states--re...
3887 TWH in 2010 / 309.3 million people = 12.57 MWH per person.
3954 TWH in 2019 / 328.3 million people = 12.04 MWH per person.
3930 TWH in 2021 / 331.9 million people = 11.84 MWH per person.
And that’s with over a million electric cars added. 2000: 98.7 quadrillion BTU / 281.4 million people = 350 million BTU/person/year
2019: 100.5 quadrillion BTU / 328.3 million people = 306 million BTU/person/year.
On the other hand, increased use of global manufacturing and reliance on ocean transport is concealed by this metric. Still, it doesn't look like overall things are getting worse.For the CO2 metric:
2000: 20.9 tonnes per capita
2019: 15.7 tonnes per capita
https://www.eia.gov/totalenergy/data/monthly/pdf/sec1_19.pdf> Global electricity consumption continues to increase faster than world population, leading to an increase in the average amount of electricity consumed per person
https://www.eia.gov/todayinenergy/detail.php?id=44095#:~:tex....
Note that I really want electricity usage to go up a lot, too. It's just overall primary energy usage that we want to stay level or go down. That's why I used the primary energy usage metric. After all, moving to an electric car or replacing natural gas heating with a heat pump "increases electricity usage."
- "China's modern cities far outshine Cold War Europe-- Wtf is with these misconceptions?"
- "A whole lot of China is rural and undeveloped. You think it's like Cold War Europe-- Wtf is with these misconceptions"
Maybe make an argument instead of just being unkind to other commenters.
I'm installing rooftop solar. It makes me feel good.
Its output is an order of magnitude more expensive than utility-scale solar behind the meter. The solution has to be renewables + storage + zero-carbon baseload, i.e. nuclear. Everything else, including calls for rooftop solar, is a distraction.
Edit: (You might say, isn't cost-efficient yet. For all I know parking shade structures could have turned the corner already; they used to require tax incentives to break even.)
Walmart has more parking lot space than roof space, and parking lot solar doubles as covered parking, which itself has value.
Even if both were cost effective, it makes sense to do parking lot first (with accompanying PR) and then rooftop later (with another round of PR).
I live in a highrise and when I look down, almost every single building, residential, office space, government, even schools, they all have solar on the roof. Almost every home owner has solar on their roof as well. It’s basically just rental properties without.
Like I said, the problem is policy.
Clearly you never talked with any Austrian. Mention nuclear energy and you will be compared to Hitler.
EU is on the bring to mark nuclear energy as non-green, what then?
Yes we need other forms of energy production, but it's suicidal to try to just use them in this supply-pushing way, we don't have time to faff around with that.
We'll get it right eventually though.
This will work just as well as nuclear disarmament: the ones complying would see the most disadvantages therefore nobody does it.
A game-theory-aware solution must be found. For example, a worldwide agreement with meaningful penalties for those who breach it.
And those who don't obey should be intimidated into compliance. After all, this is a fight to save the planet and your casualty is a small price to pay
There are other Ai possibilities, for example military-grade Ai: https://www.reddit.com/r/conspirFBeyesWideShut/comments/v74i...
And THEN ... "asteroid" is an anagram for "Ai do rest" ... that would just automatically plug into the Earth's natural electro-magnetic field as both an energy source and a means of subtly influencing "evolution" of lifeforms that could be influenced via their nervous systems ...
Saying something "harms the planet" these days is just code for pointing out targets for subversion, subjugation, and governance. The next best they can do is be bullying and disagreable. I'm tired of this bullshit narrative stuff. What's doing the most harm to our planet is putting up with it.