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Welcome to Everybody in the Pool, the podcast where we dive deep into the innovative solutions and the brilliant minds who are tackling the climate crisis head on. I'm Molly Wood. When people are feeling some despair about how to tackle climate change, they tend to say things like, well, it doesn't matter what I do, it only matters what big companies do. You know, my feelings on this, it matters what everyone does. But it is absolutely true.
That big companies through their actions, their investments, the tech they buy, their business practices can have a really big impact. So today, I'm talking with a climate leader at a tech company that's cleaning up its own operations and is also trying to push new rules to make sure future technologies, namely AI, don't make our current climate problems even worse.
My name is Megan Lorenzen. I'm a director of climate and energy here at Salesforce. I'm definitely living the dream. This is my dream job. And in particular, my passion and my area focus is the energy transition and within that power sector.
And what can and do we need to do to really drive power sector decarbonization because after all Salesforce is a data center company and data centers rely on electricity and the electricity grid to operate. And so this is an integral part of both our commitment to sustainability as well as our business continuity.
Salesforce is not even close to the most giant tech giant, but it is a fortune 500 company with a little over 200 billion dollars that provides cloud based customer relationship management software to companies all over the world and the cloud. As Megan mentioned, is actually just a whole bunch of computers located in data centers and data centers consume one and a half to 2% of global electricity currently. And that's only expected to increase as AI uses more and more and more computing power.
Let's dig into what you said a little bit more because I think people may not realize the power that big companies have already had to drive change toward the energy transition driven.
In some cases, by outside pressure, but also just efficiencies like data centers use a lot of energy, for example, just one simple example right they use a lot of energy and that's expensive. And so the more sustainable they can be the cheaper they are definitely and this is really you know there's a cost perspective for sure, but this has been really integrated into the way Salesforce operates as a business from day one.
We've really operated with this concept that business can be a platform for change. It started with our founders who kick started this one one one model, which is 1% of the company's equity 1% of its product and 1% of its employees time given back to the community.
So when we think about parts of our business like our data centers, of course, we're looking for reliability efficiency, but we're also thinking about sustainability. And that's why we were one of the early companies to commit to 100% renewable energy back in 2013, which really kick started a lot of our work on trying to drive power sector decarbonization.
And then how is the progress toward that goal? It's been wonderful. We achieved 100% renewable energy in 2021. So what this means is we match an equivalent amount of renewable energy or renewable energy attributes to the amount of electricity we consume globally on an annual basis.
And so this is catalyzed a number of projects all around the globe from the US to Australia to some new projects being announced next month, which we're excited about. And just last year we were able to do some really amazing work across the global south and markets like Africa, India and Southeast Asia. So really it's been a great opportunity to think about what role we can play to catalyze the energy transition in different markets.
And I should I don't want to gloss over I mean, I should sort of say you're being a humble Salesforce is one of the very few companies in the world right to source 100% renewable energy like this is really big. This is a really big accomplishment. There are definitely a lot of companies working on this and it's really fascinating to hear the different stages that each company is at and the different series of change that they've embraced on how they can be most impactful with their procurements.
So if you have some companies that are hyper focused on procuring as local as possible for Salesforce were part of again a coalition of our peers called emissions first partnership where we're really focused on where can you have the highest emissions impact for your purement.
And not just continuing to procure in California, for example, where we're headquartered that already has a lot of renewable capacity. And instead we're asking ourselves where is this additional project needed and where will it be most impactful.
So one of the very interesting things about the market today is that most renewable energy procurements by corporates are taking place in North America and Europe. I believe the stat from Bloomberg New Energy Finance was 29 out of 31 gigawatts were in North America and Europe.
And you're leaving the global south behind and that was a large part of this ethos around our procurement with directs across the global south was really there's a gap and a need and we were trying to focus on where can we drive that impact. Translate that a little bit if you just build another solar farm in California or even Europe you might be adding another 2% of renewable energy to a place that's already generating mostly renewable energy.
But if you build a solar or wind farm or hydroelectric plant in a place where the alternative was going to be a new coal plant. You not only get credit for the renewable energy you've helped generate but you also displace dirty fossil fuel emissions meaning fewer emissions yes but also cleaner air and water and economic development in the place where you built. The emissions first partnership also includes big companies like Amazon meta Intel Akamai GM Rivian Heineken I know right and work day.
Alright now let's get AI as I mentioned in April sales force announced its sustainable AI principles which in addition to all the other things people are worried about with AI are specifically designed to help build best practices and regulation around the environmental impact of AI.
Because we're at this really interesting inflection point we're seeing AI take off and everything we do and in the face of this escalating climate crisis AI has the potential to either exacerbate it or help alleviate and accelerate our work to address environmental challenges. And we see regulation as having a critical role to play and helping us navigate that future and really maximize the potential benefits while mitigating some of the potential impacts.
And so that's where our new sustainable AI principles come into play and this is really about guiding conversations with lawmakers trying to get ahead of the conversation and help indicate where there might be support or opportunity. So there are two major buckets all just touch at a high level and then we can dig in in a bit more detail. But the first is really about better measurement and management of the environmental impact of AI.
I mean we really cannot talk about AI without also acknowledging its impact on climate largely due to the amount of compute power it requires especially with training. And there have been some really fascinating studies emerge about data centers which currently represent about 1.5% of global power generation. And that is expected to grow to about 4.5% by 2030 largely as a result of AI. So we're seeing this energy demand increase already.
And so how can we think about better measuring and managing that impact. And then the second piece is really about not just mitigating the harm but also accelerating the innovation we can achieve with AI. We have the ability now to analyze fast data sets, identify patterns and predict outcomes that we previously required a lot of tools and resources to do.
And so how can we use government policies to incentivize and enable those AI tools that can accelerate innovation on climate and unlocks those critical social benefits. So those were really the two main buckets we wanted to tackle as a starting point with these principles. And so that's amazing now as promised let's dig into some of that because it sounds like it is a combination of internal action and engaging policy makers your background.
Let's talk about the internal action part of that and I imagine that's where the measurement and management comes in right what does that look like practically. And so with everything we're calling for we're really focused on also walking the talk and so we are focused on driving change within our own four walls. But we know that's not enough so we're we're using policy in our platform to drive change at scale.
So as we think about within our four walls we've been really focused on sustainable AI in our own development. We've had an amazing AI team for many years now and this has really been built into the ethos of how they operate. I touched on a few of these earlier but let me just reiterate it here. So one is optimizing our models particularly with AI and this concept that bigger isn't better.
So looking at domain specific models really customizing them for their intended application optimizing for cost and emissions impact. And talking about this ever growing power of small models. I think we've seen this race for giant models as of late and that's not necessarily where we need to go or where we should go. Let's can we can we break that down to for people who just may not be that familiar with how.
What we mean when we say models and and training right and it's sort of like the idea the difference between training a chat. Interface on every piece of information ever. And and or saying I just want it to. Parse the inflation reduction act for subsidies I can get at my house. Exactly and I think what's important to note is that when sales force is thinking about our own AI application. We are doing an enterprise AI software.
This is not a general purpose model that has all the information you could possibly find and you can generate cat videos or whatever it might be. This is very specifically intended to enable your business and augment the work that you and your employees are doing. I think a great example of this is we have Einstein which is our AI. AI friend AI partner embedded into our slack platform.
And I was able to drop a new report that just came out that I was fascinated about reading and it's 100 plus pages. I was able to drop it in my Einstein tool and get a you know one page summary to determine what parts that might be most relevant for me to read further on. Or use that to help me with scheduling or different tasks that take time away from the work that you want to be doing.
And then we have a lot of questions about sales forces AI product. It's really this enterprise AI designed to augment your business. It's not the general purpose AI models that are anything in everything in the world. Right. And then why is that what makes that sort of a lower energy interaction. Well, there are a couple different ways in which it's a lower energy interaction.
Part of it is how we design the training. So this is a piece where definitely you want the technical engineers to lean in. But we're optimizing our models for efficiency with the multi epoch training and flash attention. And we're able to get our models to perform as well as larger models at half the size. And so there's different technical optimizations that we've been able to implement with our model.
And I think that I think the key is knowing that those exist, right, that there is in fact a way to develop something like this so that you're not going out to this bring not sifting through every piece of information in the world to get one simple answer when you just need this narrow focus tool. Yeah, perfect. Okay. And then so that's the management internally and it sounds like you're also trying to sort of solicit and send out best practices.
We are very committed to where we can sharing externally these best practices and learnings. And so we were able to actually publish quite a bit of this just last year talking about these optimized models, talking about the power of small models, as well as the opportunities with efficient hardware, the role of citing data centers in low carbon regions.
And these come in to play in driving down emissions and then really rounding that out with disclosures. And so we we have disclosed the emissions impact of our models and those carbon footprints, both pre training and those are located on hugging base and some of the other leader boards out there as well as our own website. And so we're really walking the talk and putting forth that information so other companies can can follow that lead.
I mean, it's pretty powerful. Like I think what we find is that the the measurement is sometimes the place where not everybody wants to go. Yeah. Like you're pretty exposed when somebody starts putting the information out there. And it's an important balance. And especially in this moment, we're seeing really critical regulations around the globe, driving companies to more transparently disclose their emissions.
That's critical information, but you also don't want to be in a position where you're seeing the dollars and the time a company invests in climate and sustainability only go to reporting. So reporting is part of the puzzle and that disclosures part of the puzzle and should be the the way in which you identify where you need to focus and take action. And so there are certainly sort of two pieces to the puzzle here.
Let's save the second piece of the puzzle for the second half of the show. Time for a quick break. We'll be right back. Hey, you crime fans tired of ads interrupting your gripping investigations. Good news with Amazon music. You have access to the largest catalog of ad free top podcasts included with your prime membership. After all, ads shouldn't be the scariest thing about true crime to start listening download the Amazon music app for free or go to Amazon dot com slash ad free true crime.
That's Amazon dot com slash ad free true crime to catch up on the latest episodes without the ads. Welcome back to everybody in the pool. We're talking with Megan Lorenzen, a director of climate and energy at Salesforce about its sustainable AI initiative. And part of that is trying to engage lawmakers to consider climate goals in any future AI regulation.
Can you talk about the high level ideals like what is what are some of the policy outcomes that you would like to see even just around sustainable AI, for example, definitely some of the specific things we're calling for requiring AI disclosures for all general purpose models. I think this is a really important again starting point because where there's visibility and disclosure, we can drive action and a large part of that is going to be the development of standardized metrics.
A second piece has been around adding the environmental lens as a risk factor. So as governments are thinking about AI systems and starting to identify which AI system is high risk because a lot of what we do could be captured in a really generic AI description. And so we want to make sure we're really focusing that additional attention on models that might pose additional risk or in the EU AI act they've called it systemic risk.
And so we're looking at training that might exceed a certain compute threshold or cause a certain threshold of emissions. So once you exceed that threshold, then those AI models should be considered high risk. So before those high risk models, let's layer on those additional efficiency standards and benchmarks, whether it's optimizing the model for efficiency, right sizing it, ensuring we've got that those right energy efficient AI algorithms in place.
This could be around the efficient hardware that's used to both train and run these models or it could be about where you are citing or training your models to really try to leverage some of those clean energy or low carbon grids. So as we think about it, it's a really natural bill, right starts in the disclosure, then you say, what are the models that we really need to worry about that have that outside environmental impact and for those let's layer on those additional efficiency benchmarks.
So fascinating because there's obviously a lot of conversation all the time about attempts to regulate AI and they mainly, you know, they focus on deep fakes or disinformation or copyright violation or privacy. So what you're really specifically saying is as you're crafting regulation, please also include environmental impact in any future regulations, what is the, what is the reception to that, would you say.
So I definitely think that we've got opportunity in front of us to EU AI Act, which has the initial foundation, they've included some of the training thresholds and in their definition have left the door open to additional criteria emissions wasn't explicitly stated, but there's a toe hold there on which you can build we're seeing legislation that proposed in different markets in this vein.
So I really do see the momentum building that folks are understanding that the energy and emissions impact of AI models is something we should be thinking about. It does sort of feel like if you, yeah, I could, I could have a longer philosophical discussion about how it, you know, it sort of feels like, look, if you can strain it in a lot of really natural ways that are also good for privacy or good for copyright.
And you therefore create potentially smaller models that are not as impactful and that they can, those regulations could all feed each other in a really a way that could be good for all of us. Exactly. And it's not just about how do you minimize the harms, but it's also how do you unlock the potential benefits of AI. And so there are some really exciting.
Yeah, mine. That's my second. Yes. No, totally you have gone exactly to the next place, which is, okay, cool. Now how do we make it and do some good stuff? Yes, exactly. And you know, AI has such capability to analyze data, predict outcomes, generate really robust models. And so how can we create maintains from those open source databases really around environmental data and make it freely accessible to really accelerate the R&D process.
And enable action. And this is so exciting because I'm already seeing some government organizations lean in here. Some great reports came out of NREL in the last week on exactly this front leveraging AI and data sets and open sourcing it for in that case grid operators.
And so I think there's a lot of potential here for the government to unlock a more cohesive effort. And then the government also has an amazing role to play in fostering collaboration and some of those public and private partnerships where each sector, whether it's academia, private sector or government, we have something to bring to the table.
And so how do you convene us and then open source some of those learnings and best practices. So it's accessible to communities that may not have the ability to develop those resources in house. And then last and certainly not least is how do you then spur innovation. So grants, tax incentives, the like around the environmental application of AI, whether it's for tools to optimize critical systems like the electricity.
Excuse me, the electricity grid or to leverage AI to detect or monitor wildfires or illegal deforestation. There's so much potential there. How do we really spur that innovation. And we're doing as much as we can within our own sphere. But if you can achieve that at the government scale, we can unlock so many ecopreneurs. Yep. Okay, so be more specific about what government could and should do. It sounds like some version of open data, which many of us have been asking for a long time.
But availability of data seems like a key component that you're describing. Definitely. Yeah, it's definitely the how can you open source those environmental data sets in particular so that we are enabling whether it's researchers early stage development of new technology. How can those folks just jump ahead with this data. We now have available available. And how can we train AI models on all of this really deep environmental data.
Well, I would guess though that that's exactly why public private partnership is so crucial here, right? The government may have a lot of data, but maybe not a lot of super efficient high tech systems to sort through and organize. You said it. Just just, just hazarding, I guess, what might be happening. Got it. Check.
And then when we think about problem, you know, this is somewhat high level, but when we think about the sustainability problems that AI is potentially uniquely suited to tackle, like what is the view from Salesforce on what it could really do well in this arena because it's attempting to sort of say like, I know it's just going to like soft climate change and you know, and then I'm always like, cool, how.
Yep, it has so much potential. And when we have already we've already started on this journey with our benches team and our Salesforce accelerator, we just recently completed an AI accelerator for climate.
We're investing in a lot of startups and ecopreneurs who are really trying to leverage AI to benefit the planet. So whether it's a company like piano AI who automatically detects wildfires with AI before they spread or a company like what time who's working on elevating the emissions impact of renewable energy projects around the grid and really trying to access that small to medium market that they
don't have the resources to access today. How can they use an AI assistant to reach more companies. There's so much potential. The AI accelerator, which we just announced this week actually identified five companies in particular as the winners that we felt we're doing really amazing work on using AI for some of these climate outcomes.
And I'm happy to talk about a couple of them if it's of interest. I would love it. Yeah, I mean, I think people honestly we just want to hear about more solutions all the time. Yeah, and I love that about your podcast right. It's like let's not just talk about the problems. Let's talk about the people who are doing the work and trying to drive change. And this is brilliant, brilliant, hopeful people.
Yeah, and this is really where I think the sales force accelerator really flourishes because it acknowledges that there's an access. Yeah, and there is inequality between who has the resources and skills and opportunity to benefit from AI and those who don't. And in particular, a lot of nonprofits are feeling like they see the digital transformation as essential, but they don't necessarily have the means to really embrace that opportunity from technologies like AI.
And so the accelerator was a really innovative model that is bringing forth unrestricted funding technology donations and pro bono expertise from sales force to help those nonprofits maximize their impact. And so it's this really amazing full circle engagement and I can brag about it because it's our wonderful full-anthropy team. It's not it's not my project. Unfortunately, but I am just so excited every time I see the work that comes out of that team.
And so they identified several companies. One I already mentioned I might just elaborate on slightly which was what time. And so we actually have worked with what time on a number of projects over the years on our own renewable energy journey.
And they think really deeply on how do you strategically site wind and solar and they've worked very closely with a number of large companies just given the size of their organization. But there's this huge long tail of small and medium sized businesses that are also embarking on this journey.
And so how can they augment their very limited capacity as an NGO by providing self service access tutorials FAQs with their AI assistant to help serve that broader market. And so really excited to see how a tool like that which I have personally had a lot of benefit from can it can reach a broader audience with AI.
So another company is good 360 and so this this is really focused on responding to disasters. So they they truck I think it's in the order of magnitude around 16,000 truck loads of donated goods nationwide. And so it's this amazing network. But they're trying to figure out how can they minimize their environmental impact. And so they're using an AI resource to analyze their product data to minimize delivery distance fuel consumption.
And just really optimizing their systems all together to decrease waste increase impact and make sure that they're delivering the right resources to the right places and they're expecting to see almost a 20% reduction in carbon emissions just through using AI to optimize their logistics. And so there's just so many different possible applications here.
And then Megan tell me about your background. How did you end up with dream job. Yes, so I actually I started my undergraduate in political science. And then discovered that environmental studies was a potential pathway and I was like wait, you mean I can pursue a career and a curriculum around something I'm personally very passionate about.
And most of my time trying to get outdoors and enjoy nature and that really set me on this path. At the time you couldn't take an environmental degree as a standalone major. It was still one that had to accompany a more legitimate degree. And so it was really I think early on there and just had the fortune of getting my foot in the door with some utility work.
And then working on water and clean energy through local utilities and then really turn the corner with a company called three degrees, which is a renewable energy consulting firm. I like to say I grew up there. I had a lot of opportunity to learn fast and dabble in a lot of different initiatives in the clean energy space before really turning the corner to sales force because at three degrees.
I worked a lot with utilities and there's such an important role to have the enabling environment with the utility are they offering the right options to their customers. But I consistently saw that corporations could come in and just change the dynamic because you're bringing such scale to the conversation. And so really saw the opportunity to engage in the corporate climate movement because that's where so much innovation is taking place.
Yeah, it's I want to put a fine point on this because I think it is easy for you know when people talk about climate action. And sort of simultaneously point to the need for corporations to have a big role and also don't believe them when they try to take that big role. And I think it's really it's important to sort of say that people are choosing to work for companies that reflect their values.
And that if sales force or Google or Walmart, you know, makes big changes in the industry, that's how change happens. And if you think about it, just from the perspective of the clean energy again, that's that's my bread and butter where I'm most comfortable.
And a decade plus ago, there were only a handful of companies who were thinking about procuring clean energy. And now you have hundreds who are part of this community and on this journey. And I think what's amazing is together we've catalyzed over 150 gigawatts of new renewable energy. It's amazing to see what change can happen when you have that focus that unified focus of corporates.
Thanks to Megan and again, let me reiterate startups, individual action policy, investment, we need all of it and we need big companies to move and to encourage each other to move and to tell us what they're doing internally. Whether it's out of genuine care or simple economics or ideally both. When I talk to company executives about say a lack of regulation or what will it mean if the political winds change and there's an anti climate administration, you know what a lot of them say?
Something along the lines of well look back in 2017 Walmart announced it was going to try to decarbonize its supply chain. And so we all know that's where business is headed and you can't stop that train. By the way, what Walmart did was set a goal to reduce a void or offset a billion tons of greenhouse gas emissions from its supply chain and it achieved the goal this year six years ahead of schedule. You can't stop this train.
That's it for this episode of Everybody in the Pool. Thank you so much for listening. Email me your thoughts and suggestions to in at everybody in the pool.com and find all the latest episodes and more at everybody in the pool.com. The website. If you have a moment, I would really appreciate it if you could rate review and share this podcast on Apple podcasts or wherever you like to listen. Thanks everybody. See you next week.
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