The Week in Green Software: Code Green and Clean Power

Joining host Chris Adams on this episode of TWiGS is Nina Jabłońska, operations coordinator at Energy Tag and a master's student in sustainable energy systems. In this episode, we'll explore insights from the Linux Foundation Energy Summit in Paris, including Microsoft's urgent call for green coding and real-life examples of reducing computing emissions through cloud carbon footprint analysis. We'll also touch on employee activism at AWS, where tech workers stood up for climate action and better work-from-home conditions. Nina also tells us why sometimes she goes by Nina Jab%o%ska, and why Cara Delevingne and Keanu Reeves are the ultimate “carbon-free couple!”

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TRANSCRIPT BELOW:
Nina Jablonska: So it's just a matter of really wrapping your head around how you want to do it and what concrete actions you want to you want to undertake. But in the end, I think it just pays off to be green, and I hope it will only go in this direction.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discussed the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of this Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. In this episode, we have some insights from the recent Linux Foundation Energy Summit in Paris, Microsoft issuing a code red for green coding, concrete examples of using cloud carbon footprint to reduce computing emissions. Before we dive in though, let me introduce my guest today for this episode of this Week in Green Software. Today we have Nina Jabłońska of Energy Tag. Nina, I'll hand over the floor to you to introduce yourself and say what you do.

Go for it.

Nina Jablonska: Hello. So I'm Nina Jabłońska. Nice to hear you Chris again. So I am the operations coordinator at Energy Tag. Super happy to be here. So privately, apart from working at Energy Tag, which is a nonprofit organization, I am also actually finalizing my master's studies in sustainable energy systems, which is why I am currently placed in Stockholm.

And recently I have actually taken up Spanish classes, which makes a lot of sense

Chris Adams: Wow, bueno!

Nina Jablonska: Yeah, my, my masters, the first year I spent actually in Barcelona and I started learning. A bit of Spanish just to be able to do my groceries, and since I found that in Stockholm, everybody speaks English.

So I figured I would just continue this journey of learning a third language online with, with a, um, with a teacher. But it's pretty exciting, a very nice thing to, to do some extra brain exercising in a bit different way than studying and working.

Chris Adams: Cool. All right. Thank you for that, Nina, and I should probably introduce myself as well. My name is Chris Adams. I am the the co-chair of the Policy working group in the Green Software Foundation, and I'm also the executive director at the Green Web Foundation, another nonprofit working towards an entirely fossil free internet by 2030.

If you are new to this show, the format is as follows. We basically have some people come onto the show. We look at some stories in the news that caught arise, and we just talk about them and share some notes and reckons basically. That's largely it, and we have a few stories ahead of us that I've foreshadowed already.

We're gonna start with the first story we have here, a one from the green software report. So what I've been doing for the last few weeks is I've been inviting guests to pick an insight that caught their eye. And Nina, you are no different today. I'm gonna give you an idea of anything that you, that caught your eye when you're looking at this, and it may or may not be related to what you do at work.

So yeah, I'll hand over to you. What looked interesting when you were looking at this?

Nina Jablonska: Mm-hmm. Yeah. It so happens that one of the stories is actually a bit related to what we do at Energy Tag, and that's the fact that the carbon aware software, so a software that would operate in the time and place where the grid carbon intensity is low, or it would optimize its work based on the grid carbon intensity is super important to, to enable further decarbonization. And we also heard a very diff, very interesting presentation from Avanade on this during the LF Energy Summit. I think the whole conversation around having software that really can optimize and choose when and where to operate, depending on what kind of sources are available in the grid is very important.

Chris Adams: It's about, yeah, the underlying kind of how dirty or green the energy is. Okay, so one thing from the actual conference we're both at the LF Energy Summit, was this talk by Dan Bonita and Szymon of- Nina, I think I might need you to help me with this, cuz it's a long polish name that I'm gonna struggle with.

Could you maybe help me with this? It's, is it Szymon Duchniewicz maybe? Okay. One more time, please? Duchniewicz. Okay, great. Szymon, so Szymon that from Avanade, that was the other deck we can share a link to that has them explaining some of the work they were doing and what they were using there. Okay, thank you. That was the only thing. I just wanted to make sure I got it pronounced properly and it sounds better from you than it does from me,

Nina Jablonska: The Polish surnames are, he doesn't have the weird, the weird letters though. You, for

Chris Adams: Diacritics and things.

Nina Jablonska: Exactly. You turned mine into just the regular l and n I can see here, but for example, on my Spanish student id, they just turned that into a percentage sign. initial student Id said that. My name is Nina. Jab.

Percentage sign, o, percentage sign, ska.

Chris Adams: Okay. This is why people should be using Unicode as much as possible instead of Ascii, yeah. Nina. Ya percentage nska is not the correct name. The, the.

Nina Jablonska: It is definitely not, but imagine going to a bar with my friends and they would check the IDs and I would just show my student ID because it was the first card that I got out of my wallet and the guy was just like, are you Elon Musk's daughter? And I just, yeah, I should learn to make a robotic sound of my voice and just try to like say back something funny in Spanish, but I could not just, it was.

Chris Adams: That's, that's probably gonna be easier than explain the problems associated with Unicode and Ascii code and stuff in the middle of a bar. You've mentioned that you're in Stockholm right now, right? So that's in Sweden? Yeah. And that's a relatively green grid by comparison, right? Because that's usually a hydro or wind.

What would it be?

Nina Jablonska: Yeah, yeah. The northern parts of Sweden especially are very clean. They're mostly based on hydro power, as you mentioned. In the south. There is still a bit of. Challenging situation with a bit of leftover gas generation and so on. But overall, yeah, overall Swedish grid is really one of the cleanest ones, which is why most of the challenges present in other countries are not really discussed here so much.

Chris Adams: Ah, I see. Whereas,

Nina Jablonska: could be a good, could be a bad thing, but they're really moving at the forefront of decarbonization every of every single sector, including transport, et cetera.

Chris Adams: I see. Okay. And so I'm in Berlin, so right next to the border, relatively close to the border of Poland. And you know, you are originally from Poland as well, right?

Nina Jablonska: I am hence my complicated surname.

Chris Adams: Ah, I see. Yeah, so that's an example of grid, which is relatively cold, heavy, and somewhat dirty. So the same program run in maybe say Sweden compared to say, uh, Warsaw or somewhere might be much dirtier depending on how you would run that.

Although that may be changing over time because opponent turns out to be one of the fastest decarbonizing countries as of last year. That was one of the stories that I learned of which I was surprised to hear from, given how coal heavy that grid is, for example.

Nina Jablonska: Yeah, it could be surprising, but it could also make a lot of sense just given the fact that decarbonizing the first 10, 20, 30% is way easier than decarbonizing the last. 30, 20 or 10% of energy demand. Of course, a lot of challenges come with balancing the grid supply, with introducing the technologies needed to cover the last really couple of kilowatt megawatt hours of demand in various hours.

So I think it is a good sign. Of course, I wrote from my country, I would love to see coal as soon as possible, but I also think there is still a lot to be done. Partly, it's also nice that maybe the technological development needed to really cover this last piece of demand is going to happen abroad. So let's say maybe people from other countries and the grid operators from other countries will figure it out for ourselves and we will just follow their example in this sense.

But,

Chris Adams: Okay, cool. So that's one of the examples from here. So we spoke a little bit about the difference. The carbon intensity can be different, and this was one of the ideas behind. And kind of carbon wear computing, for example. I guess it's one thing that. It might be worth asking is like, how do we know this is really the case?

And this is something that I found quite interesting that when we were both at the Linux Energy Foundation Summit, there was actually people talking about, okay, this is how you can build open models of understanding what kind of interventions you kind can actually make. This might be a kind of jump off point cuz one of the panels that we saw was specifically related to this.

There was a number of large companies, but there was also some work from, I believe, I think you might know Igor's surname, Dr. Igor. Do you remember? Can you help me with his surname? Yes. So he was talking about some work that the technical University of Berlin had been doing with Google to basically model a kind of way to decarbonize all of their infrastructure between now and 2030.

And the thing that kind of caught my eye was, The use of an open source modeling tool called PyPSA Python Power Systems Analysis. I think that was it. I think that's something you might be a bit more familiar with than I was. And uh, this is the first I've heard of this and maybe you might be able to shed some light on this cuz I didn't know that much about it before coming to this event, this conference.

And I thought the idea that you could essentially talk about this stuff in Python, it was cool actually. Yeah. I'll hand over to you because this is something that I think you mentioned that you've been doing a bit of work with as well yourself. Right.

Nina Jablonska: Yeah. Yeah, so I, as I mentioned, I am also still finalizing my master's degree. And of course, as the last part, I do need to deliver some thesis, some piece of my own work. And I actually decided to do it based on this open software and this openly available piece of code that guys from TU Berlin have written and come up with.

And this is indeed part of a bigger study that they perform, which is studying the effects of 24 7, carbon free electricity procurement on the system level emissions, but also on the emissions for those customers who decide to follow this 24 7 carbon free procurement strategy. And then also on the cost premium of doing this, instead of following the business as usual, let's say energy attribute certificate system.

So of course, the way companies and big consumers source clean energy from the grid is through buying those annual certificates where they match their annual energy consumption with the same amount of energy in those attribute certificates that are coming from, let's say, solar power plants or wind power plants.

And why this system doesn't work, obviously is because it doesn't really send these precise signals. As we mentioned, also, with the carbon aware software, it doesn't really tell you in which time and location. The grid actually has a higher carbon intensity when it has lower carbon intensity, and it also doesn't reflect probably most importantly, the actual cost and the actual effort that you have to put in decarbonizing every single hour of your electricity consumption.

So the study developed by the TU Berlin lab is essentially doing this, assuming that some companies follow this strategy of sourcing electricity in every single hour, but also from deliverable location, meaning for example, from the same country or for the same bidding zone. And also that this energy is going to come from additional assets.

So for example, from newly built solar power plants, instead of competing with the other grid users for the existing assets. And they essentially see how that would impact the grid and the great outcome of the entire LF Energy conference as well. For me, and the great thing that I could do is to meet Igor, who is one of the authors of the study and who has helped me greatly with using their piece of code for my own thesis.

And I just think it's so great, really, that it is available openly and we can just download it literally on our personal computers. I am not even a, an energy system modeler. I never created. Any model similar insights to this one may be a small one during some classes at university. So I think it's really a great thing that anybody could just download it and it is very much, I think, encouraged also to just provide them with feedback to challenge their assumptions, which is essentially what I'm doing for my thesis.

So yeah, it is very nice for me to combine this data and software openness that we discussed also with many other people, both of us, definitely at LF Energy Summit and this kind of new generation of clean energy procurement that is proposed.

Chris Adams: So there's one, there are two things that I found quite interesting when I spoke to Iegor about this. When he gave, when he spoke on this panel, he said one of the ideas from the work that was going on is yes. You can get an idea that basically moving from maybe an annual approach to, to an hourly approach helps address some of the existing problems people have and some of the accusations of kind of greenwash related to green energy wind.

People will say, I'm running all my infrastructure on all my servers on solar power, and they're saying this. Happens at night,

Nina Jablonska: Mm-hmm.

Chris Adams: may be somewhat inconsistent with how most of us understand solar panels to be working, for example. There's some stuff like that. But one thing that caught my eye was he was actually saying that, yeah, by doing this, we're actually ma able to model the impact of whether we can make the infrastructure itself responsive.

So rather than just having to make sure that we've got enough wind and solar or hydro or stuff to do this. They were talking about how they could model reductions in demand to need so much in the first place. And the same if you have maybe 10% of all the compute that's flexible, then you need less generation, which then will impact the kind of cost of actually us moving away from what we currently have right now, which is lots and lots of fossil fuels to something which is greener and more humane on the grid.

So that was cool. But you said something quite interesting just now about like location, like local and deliverable and what was is additional, is that other thing you just mentioned? Yeah.

Nina Jablonska: Yeah. Basically, if we want to put it in short words, hourly matching is not enough. So the entire study, and I think the first concept that comes into mind and that's discussed is how we want to match the supply of clean energy at an hourly basis with the demand. And as you mentioned, what's impossible in the real world to consume solar energy at night if you don't have a battery?

So hourly is the first pillar that we, we now call them the three pillars of carbon free energy. But the other two is, are actually equally as important as it turns out. The second one being the fact that you need to make sure that this electricity is deliverable, which means you not only have an existing interconnection between point of generation and point of consumption, but also that there is enough interconnection capacity to actually allow this electricity to flow instinctively. It doesn't make sense to import electricity when you're in Sweden from, for example, Portugal. The likelihood of

Chris Adams: I see.

Nina Jablonska: of your electrons flowing from a solar power plant in Portugal and actually reaching your, for example, my house in Sweden, if I had one, are extremely low.

And we actually talked to some people who are modeling this as well on l F Energy Summit. I think there's going to be a, a summer of many interesting reports coming. And the third pillar then, is the additionality. So really seeing how it's not only enough if you match hourly and location, but also you need to make sure that if you introduce especially new additional demand, you do need to make sure that you have additional assets to meet this.

And that is a huge thing, for example, with hydrogen, since hydrogen, especially with the ambitious goals that both the EU and the US have right now. It's really. An amount of electricity that you cannot just forget about in the eu. If we want to meet the goals for hydrogen generation by 2030, I think we will need somewhere around the equivalent of the annual consumption of France.

Chris Adams: Okay.

Nina Jablonska: So it's something.

Chris Adams: New generation, like new clean generation that would be coming in,

Nina Jablonska: Exactly, and then exactly nuclear generation. So that's the question. How do you ensure that, that this is actually clean and that it contributes to decarbonization? A study from Princeton University who are performing, we can call them sister studies, to the ones from to Berlin from Europe. So Princeton did a study where they analyzed what would happen if you didn't ensure hourly deliverable and additional electricity, and what they found is that the hydrogen you would end up producing would be twice as intense, twice as high in emissions as the one produced right now using gas.

Chris Adams: So that would be the opposite of what you wanna have. So basically if you, so if I, let me just check if I understand those two things, cuz at the idea of hourly, we kind of understand, like when people say they're running on green energy and they say they're running on power and they're running a server at night, that's very intuitive, easy to understand.

The deliverable thing that was like, When people say, oh, I am running green. I'm running my say websites or running a server on Green Energy. And what they're really doing is they, are basically running it on a normal grid, but they're buying some certificates from somewhere else in the world and then saying, yeah, because I've bought these certificates that my energy is green.

And the example might be if I was to buy the green certificates from Spain, but I was running servers in the Netherlands or Germany, then it's quite difficult to actually shift electricity all the way across that. So it's a bit of a kind of porky pie to say that's a bit, that's green energy, right? Exactly. Okay, cool.

And the final thing was about additionality. This is this idea that when someone's going to be saying they're running on green energy, they need to make sure it's adding new power to the grid. Cuz if they're not doing that, maybe you could expand on that one, because this is one thing that I think is.

Interesting in the world of technology for us, because it looks like the whole discussions about massive new amounts of demand, like AI and stuff like that, it seems somewhat comparable to the discussions people are having about saying, one thing we need to do to replace fossil fuels is have a way to make hydrogen from say, solar or wind, or stuff like that.

And you're saying that you need to be really careful that the power is coming from clean sources. Cause if you just pull it from the grid at certain times, it can be almost worse than basically getting hydrogen in the usual way, which is usually coming from methane gas or something. Is that what you're saying?

Nina Jablonska: Methane reforming. Yeah. Which is a, a process which I, I am not a chemical engineer or hydrogen expert, but this is basically a process where you directly use natural gas to produce hydrogen, which should not be the case anymore. We should really try to use electrolyzers. But if they are grid connected electrolyzers that are going to draw this clean power from the grid. Again, if we allowed them to, in a way, fight or compete with the current consumers in the grid for the clean power that is currently available, that would be a disaster because we wouldn't end up not increasing the clean capacity. We would end up in a way forcing the order grid users to report that their carbon

Chris Adams: there, there is dirty air compared to what they have. I see. Okay, so there's a concrete example I think of that we've seen. So one example this makes me think of is in the Netherlands we saw a bunch of new Microsoft wind turbines installed with some new data centers and you saw quite a lot of pushback from locals because there's this idea that, oh wow, there are these cool wind turbines that are in our neighborhood now does that mean we're gonna be run using green energy?

And if I understand it, that power, it was additional, but it was all additional going just to the data center. So it wasn't materially changing the kind of. Maybe the, uh, the carbon intensity of the power that you could trace to that organization, for example, even though it's forming into the grid, that was one of the things that was, can lead this kind of gap in perception essentially, that people were saying, I thought those wind turbines meant that my use of power is greener.

But no, that's not how it's actually being presented right?

Nina Jablonska: Yeah, that depends on which framework you use because there's, there's essentially two ways of reporting or accounting for the emissions of your electricity consumption. One of them is market based and. The other is location based. If you simply use the location based, you literally only look at the location where you're based and you take the average emission factor.

And then if you do have some additional wind turbines producing clean power, then of course you're going to lower your average emission factor, which is great. But would a lot of companies do, and actually many would argue that it's a good system to implement, is the market based one where. Through the use of those contractual instruments, such as, for example, clean energy certificate, energy attribute certificates, or other -miliar similar instruments in the market, you can buy them in order to influence the amount of carbon emissions that you report, which on one hand, again, allows you to reach 100% renewable or zero emission reporting with the use of annual certificates coming from no matter what, no matter when, no matter from which kind of assets. But on the other hand, this actually does drive additional installations and additional capacity of solar and wind. It's enough to even see what the energy attribute certificates that are existing right now, what they did to the grids they actually did when they were established.

Over two decades ago, they actually did encourage a lot of additions in wind and solar capacity all over the world in, in Europe, in the US and in many other parts. So I don't think we should cancel this entire system, but there is definitely a need right now to do the same, to provide the same extra financial incentive and to provide this extra something that's going to capture the cleanliness

Chris Adams: Get their recognition right?

Nina Jablonska: Exactly. And that's why we would need, for example, the certificates. That would be issued on an hourly basis in order to incentivize energy storage or in order to incentivize other clean firm technologies that are dispatchable, like geothermal, for example, or demand site management. Again, coming back to the carbon aware software, we need a tool that is going to capture the fact that if you choose to not consume one kilowatt hour at night when grid carbon intensity is very high, but you choose to consume the same kilowatt hour during the day when for example, this avoids curtailment of solar power, then that's a great thing to do and you should aim to do so. That's it.

Chris Adams: Oh, why? Okay. Wow. There's a lot to it then. So if I understand that correctly, in the example here, say maybe having giant company. It set up some wind turbines near me. On a location based basis, it might look a little bit greener, but from a market based basis, it might make the electricity that I get to say I get to claim as being somewhat less green while the other organization gets to say, because we've spent a bunch of money to deploying this, we are gonna claim some of the greenness of it.

Okay. That does explain the two different ways of thinking about this and

Nina Jablonska: Then again, just important thing to say is that of course we want the additional capacity, and of course it's going to do good globally for the emissions. That's also important to track what are the global emissions and emissions in the zone, for example, in the country and. It's important also to remember that if a data center purchases, let's say some wind power and additionally some storage, in order to make sure that they have this 24 7 hourly available clean energy, this extra power that's generated by this wind turbine is also going to be injected in the grid.

And then if they would report their carbon emissions at an hourly basis, they would basically. Sell this extra generation to the grid, so that would also globally decrease the emission. So there is a lot of really aspects to consider here. Of course, it's not easy to predict it, but yeah, definitely it's worth to keep in mind that the market and location based systems work a bit differently.

They can trigger different behaviors and trigger different results, and I think it's worth looking at both and really taking the time to understand what they mean and what, what are the rules behind them and what are the equations behind the numbers basically.

Chris Adams: Okay. All right. Thank you for that. We've gone really deep into the rabbit hole

Nina Jablonska: We did.

Chris Adams: of carbon intensity here, so should we look at the next story then, Nina? This one here was about cloud carbon footprint, about a, this is ThoughtWorks talking about how they've been able to use this tool themselves to basically reduce the emissions across a number of services by around, I think 60%.

And that more or less worked out to be around a saving of 46% in terms of actual cash money costs. And that seems largely I think the phrase they're using is identify zombie workloads and switch things off. So like we spoke about before, there's literally just a case of switching things off here, but I think there is some, there's a couple of things that kind of interesting here that might be worth diving into.

There's something about Scope three. Did, did that surprise you as well, Nina?

Nina Jablonska: Yeah, it is very interesting because. Scope three emissions are one of the, I would say, most challenging to track and try to estimate. So I would definitely say it's interesting to, to take a look at the methodology that they took to calculate this since the emissions that we were discussing mainly so far are scope two, so directly from the use of electricity that you consume, but scope three emissions are really the emissions around the final use of your products.

And then the final upstream and downstream activities around this. So I think it is really extremely difficult to, first of all, set targets, but then of course, measure your progress towards these targets. Most companies, when they do have some emission reduction targets, they are focused around scope

Chris Adams: Mm-hmm.

Nina Jablonska: So definitely anything that they, that they use in order to track those and to measure how their net zero goals could be achieved would be very interesting to, to look into.

Chris Adams: Cool. Now, one thing that's also interesting from with my green software hat on right now is that. The cloud carbon footprint has typically used one form of measuring carbon intensity called average carbon intensity rather than just marginal carbon intensity. Cuz the Green Software Foundation has a standard called the software carbon intensity standard, up until recently was primarily just focused on marginal carbon intensity and it's, we probably don't have the time to dive into marginal versus average here cause that's quite a complicated thing.

But essentially the key thing that caught my eye when I was looking at this was that, oh, you've got tools like cloud carbon, footprints. Theoretically, you should be able to use these tools to work out S SCI scores now for particular applications so that you can start tracking some of these and comparing them to each other, for example, in the same way that you might say share like an efficiency score or grading or things like that.

That's one thing that we've got some scope to move towards now for some of this stuff. Okay. Should we look at the next story then? Nina?

Nina Jablonska: Yep. Yeah, absolutely. The next one is about carbon again.

Chris Adams: This is, yeah, Microsoft issuing code green alert. So this one here is, there's two things that are interesting here, really. So one of these was basically about this idea of Microsoft's making a big thing about. Not using water so much in its data centers are trying to move away from this and shifting to this exotic way of calling called adiabatic cooling. And this is interesting in my view because a lot of, there's been a real pushback recently about AI models, not just in terms of carbon, but also about in terms of like water usage as well here. And one thing that surprised me with this is like, There. There was one thing which is hidden away basically saying, yes, Microsoft has its claim to be carbon negative, which is zero waste and be water positive by 2030.

And these were all made before there was a whole discussion about this cut and sudden craze in generative AI and large language models and things like that. And there's a question now like there's suddenly all this new demand coming onto the grid on all these other new discussions, and it feels very similar to the additionality stuff you just mentioned before about, okay, where do we go with this?

How do we fit this in?

Nina Jablonska: Yeah, there is a very interesting analogy between this extra demand from the AI related processes and hydrogen in the regular grid because both of these have this extra feature in them, and again, if we don't account for the extra demand that the data centers will have, I'm not talking about water, but electricity since I'm not an expert on water use here, but this really again, boils down to ensuring that this extra demand, no matter how big it is, which again, how do we estimate this and how do we even predict how much it can blow up in the future?

It is really crucial that it will be covered with clean electricity, and again, the three pillars of hourly deliverability and additionality of these assets will be really important. Again, to not turn this extra demand into a carbon bomb that's just going to blow up in our faces. Because the stakes are really high.

We, as we've seen with, with hydrogen demand, and I think AI and data center uses. Data centers use how much of global electricity right now?

Chris Adams: We can look up the state of carbon waste software to see what figures they have for that. That might be the best way to do it.

Nina Jablonska: it's around 1% maybe, but it's still a lot.

Chris Adams: Yes. That's still gonna be, so that's like half of aviation is the figure spec I've heard people use specifically just for data centers, not the rest of the infrastructure. I'll say networks and things like that. So that's still. That that's a medium sized European country, basically. So that's about uk for example, the UK is about 1% more or less.

Alright. So yeah, that's the kind of ballpark you're looking at basically.

Nina Jablonska: Yeah, so again, if we, if this is the base consumption right now and with AI, we don't really know where it's gonna go and how big it's going to be. And the pace edit at which it has been growing recently is really beyond any estimates and any guesses. So I think we may see a similar discussion actually coming up.

We've had this discussion about hydrogen. We do have the delegated act already requiring these three pillars in the European Union for the definition of in order to produce clean hydrogen and to define hydrogen as green and carbon free, we need to ensure hourly new asset, uh, no more than three year old asset than the electrolyzer, and then also the same bidding zone.

The same discussion right now is happening in the US and there is more and more discussion moving towards. Also implementing those three pillars in the requirements there for the tax credit. And I think we may maybe in a couple of months hear the very same discussion on how to ensure that the data centers and that AI is powered by clean power only.

Chris Adams: You actually raised a good point, Nina, because a few weeks back we looked at one of the stories of reports, uh, by amongst the authors was one, uh, woman, Sasha Luccione. And she was actually in the report that, so in the paper that she shared that we'll share a link to, there was this idea of saying, if you're gonna run AI or if you're gonna have these models, Then what you should probably be doing is actually figure out how many hours are you gonna be using this for, and then find a way to attract that because these are kinds of models which are not latency sensitive this way other the way other things might be.

So if we're gonna have a model that's gonna use this much power then and we realize it's gonna create this much value, then yes, we should find ways to make sure we can run that on an hourly basis. For example, always using green energy and because these kind of things are plausible. There are scenarios where if you are gonna take maybe 20,000 hours of compute to use this, you could plausibly put them at certain times where.

The sun's in the sky, or there's really easy access to green energy so that you can work out what the cumulative carbon footprint of that might actually be. That's quite similar to what you just said actually about the whole hourly thing that you mentioned with hydrogen there. I guess the question that we might have when we look at these two things is that.

With hydrogen, there's a whole discussion about we need to get our fossil fuels, so we're gonna need to have this much hydrogen. But we haven't really had that discussion about saying, do we need to have this much ai or do we need to, how much compute is enough for this?

Nina Jablonska: How much AI do we need?

Chris Adams: yeah, because there is, there's gonna be all these assumptions about do we just need to do less or do we need to meet these massive targets that we might actually have?

Cuz the ones you mentioned before was for hydrogen was what a another France worth of electricity, for example.

Nina Jablonska: Yeah, around around 500 terrawatt hours of electricity, which is more or less the annual consumption of France.

Chris Adams: Okay. That's a significant amount. Wow. All right, so that's, I guess we need to have maybe some of those discussions with data centers and talk about how some of that work, how, what the priorities might be for some of that then as well. Okay.

Nina Jablonska: Exactly. And also one more thing that just popped into my mind is I remember there were some people even pushing against the development of AI, and I remember one of the ideas was to tax AI companies like 98% or something from the revenues. In order to just really limit, I'm sorry, I don't remember who exactly said that, but there was an idea that if AI is going to really develop at this pace and gain so much revenue, then maybe they should just pay ridiculously high tax in order to limit this in a way. And this gets me to think that if AI is going to be a business where you can make a lot of money, why don't you make sure that this money actually goes in a good place and in this sense, and the same conversation again, goes into hydrogen. With hydrogen, you are going to have subsidies. You're not going to just generate hydrogen and pay 100% of the price on your own.

There is going to be large subsidies in both EU and US, and therefore there really is no excuse to not make sure that you have this additional deliverable, hourly clean power, and that you really don't use only clean power from the grid because you have the money, you have the technology. The technologies are available largely.

We do have, we do know how to do it. So the question is, yeah, where is the

Chris Adams: priorities that you want to have for this?

Nina Jablonska: and where either the legislation or the push maybe from the society is going to be to really make sure that it's doing way more good than it's going to do bad.

Chris Adams: I see. So that's like a discussion about, okay, if there is all the value being created, how is that distributed? That's the discussion that you, that needs to be happening there. Okay. Alright. Speaking of this, we've just got one more story I think to look into before we wrap up with a couple of, with a, the little question here.

This is actually a story from AP News about actually staff. This was happened last week actually. This says Amazon work workers. Basically they did a walkout about the company's climate impact and the return to office mandate for the walkout. This is the follow one from us having a discussion about employee activism last week.

I, I think it's interesting because we see a lot of the impact and lots of the action from large firms coming from employees a lot of the time.

Nina Jablonska: I think it's, I think it's an extremely interesting conversation in general, not only about remote or at in the office work, but also of the impact of both the pandemic and the climate crisis and how of the new generation of workers coming to the job market. I think the reality of what you're looking for in a job has changed so much, so much over the past two or three years,

Chris Adams: mm.

Nina Jablonska: and there there is power in the people.

I think main outcome of this is just really, if you want to keep your employees satisfied, it's not only enough anymore to pay them well. In fact, some people are willing. There was also studies done on this that people are willing to be paid less if they know that their companies are. Extremely climate aware and sustainable yeah.

Chris Adams: I agree with you. This one is actually this one thing that there's a particular quote. Okay. Today looks like it might be the start of a new chapter in Amazon's history when tech workers coming outta the pandemic stood up and said, We still wanna stay in this company and the direction of this company.

This is from Eliza Pan, a former employee and a co-founder of Amazon employees for Climate Justice. These are some of the people who have really been pushing for Amazon to be moving faster. And as an organization, which is as large as it is, this is a real significant driver. That's a lot of leverage that we'd actually have there.

And you see this in a number of places, and I, I think it's worth paying attention to some of this stuff here because, power, leverage and pressure comes from lots and lots of places, and today as we learn more and more about the state that we're in, I think as much pressure as possible will help us accelerate and get to where we need to be, especially for 2030 on this one.

Nina Jablonska: And also not to mention that sometimes I would. Even say, usually if you do the climate consciousness part right of your business, you may up even saving money, not only spending more, so it's just a matter of really wrapping your head around how you want to do it and what concrete actions you want to you want to undertake.

But in the end, I think it just pays off to be green, and I hope it will only go in this direction.

Chris Adams: So this has been interesting with AM Amazon specifically because they are already. The largest purchaser of renewable energy in the world now and last year, I think they've already spent something in the region of $60 billion on infrastructure already. And this gives you an idea of the kind of scale that we need to be moving at.

So this is the largest one saying you need to be moving even faster than this in order to do this. And I think it's, for many of us, it's difficult to get ahead around just the scale of these numbers and the change that we might actually be needing to do. Like you mentioned, another France worth of, of of electricity, for example, to replace fossil fuels in certain areas.

It's a dizzying times to be in, that's what I can say.

Nina Jablonska: Definitely super interesting.

Chris Adams: Okay, so we've covered through this, we spoke about the some of the green coding stuff from Microsoft. We spoke a little bit about the carbon oil sdk. I think the last question we have now is just a final question that we have. This one is, I think this is one from Chris, our producer.

If you could have any celebrity become an ambassador for green software, who would it be and why?

Nina Jablonska: Is it a question coming from the Cara Delevingne, maybe.

Chris Adams: Oh, that's a good one. Actually. I hadn't actually thought about that, but you might wanted to explain that one because if you, I'm not sure how many people know about this stuff. Actually, it's worth just explaining some of this.

Nina Jablonska: It is so good. Of course it has it's many haters, but haters gonna hate. Basically, Cara Delevingne participated in a, in advertisement from Vattenfall, which is a huge company here, a huge energy company here in in Sweden and in other countries as well, where she promoted an emission free face mist or perfume. I don't exactly remember what it was, which was basically a campaign targeted at advertising.

The fact that waterfall is moving towards carbon neutrality and they're going to, uh, create, oh, I don't remember actually if it was hydrogen or if it was just industry clean water. Anyway, it was a campaign that was aimed to raise awareness about the climate goals of Vattenfall and the way they're moving forward with with all of this, but I wouldn't pick Cara Delevingne for green software. I think for green software, and I'm so bad at names of actors and actresses, but the guy who played in Matrix?

Chris Adams: Keanu Reeves.

Nina Jablonska: yeah. Yeah. Because the software, the zeros and the ones in the background, they were running like green. It.

Chris Adams: also green as well.

Nina Jablonska: So I think he would like to the back move and avoid some carbon emissions and then, and then have these zeros and ones in the back.

And it's all green software.

Chris Adams: So it's literally green software against a black screen. Okay. So that's your person.

Nina Jablonska: For Keanu Reeves.

Chris Adams: All right. Okay. And also when builds, when things aren't working so well, we can always roll out the sad Keanu meme. So it's, it works out on low all these levels. Excellent. All right. Okay, so Cara Delevingne for Energy and Keanu Reeves for software.

Nina Jablonska: Carbon free couple,

Chris Adams: Carbon free car. Yes, indeed. Alright, that takes us to the end. I think that's all we have time for this episode of this Week in Green Software. All the resources in this episode are gonna be in the show notes as we normally do. You can also visit https://podcast.greensoftware.foundation to listen to more episodes of Environment Variables.

And, uh, finally, I wanna say huge thank you, Nina. Thank you so much for coming on for this. I enjoyed hanging out and chatting with you, and I wish you the best with messing around with Python Power Systems analysis.

Nina Jablonska: Thank you. I'll need some of that for the next month or so. But thanks so much for having me. It was a lot of fun. A nice way to start the week.

Chris Adams: Cool. All right. Take care yourself, Nina, and everyone else. Thank you very much and see you on the next episode, tara!

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