Ep 119: AI in Renewable Energy – Insights from NVIDIA

Episode Categories:

Overview

Renewable energy has become the driving force behind our quest for a sustainable future. As businesses and decision-makers, we are constantly seeking innovative solutions to enhance energy efficiency, reduce carbon emissions, and meet the increasing demand for clean energy. In a recent episode of the Everyday AI podcast, industry expert Marc Spieler shed light on the transformative role that Artificial Intelligence (AI) plays in the renewable energy sector, providing valuable insights on how AI-powered technologies are reshaping the future of energy.

Transitioning Towards Renewable Energy:

The global energy industry is undergoing a momentous shift from traditional fossil fuels to renewable sources. Countries worldwide are investing in sustainable alternatives such as solar, wind, and hydroelectric power. However, transitioning to renewables while maintaining reliable and resilient energy production poses numerous challenges.

Optimizing Energy Production and Distribution:

AI proves to be an invaluable tool in optimizing energy production and enhancing distribution systems. By leveraging advanced algorithms and machine learning, AI can provide real-time monitoring and analysis of energy consumption, enabling businesses to make informed decisions that prevent energy wastage while meeting demand. AI-powered navigation systems, similar to those used for determining optimal travel routes and times, can be applied to the energy sector to monitor the production and distribution of electricity, particularly as the number of electric vehicles on the grid continues to rise.

Balancing Energy Supply and Demand:

A crucial aspect of the renewable energy sector lies in maintaining a delicate balance between energy supply and demand. Overproducing or underproducing electricity can have significant economic and environmental repercussions. Through AI-driven predictions and modeling, energy plants can accurately anticipate electricity requirements based on factors such as weather conditions and temperature. This helps prevent excess capacity, reducing costs and environmental impact. AI can also analyze the impact and capacity of distributed energy resources, providing insights to expedite their interconnection to the grid, contributing to quicker and more efficient renewable energy integration.

Optimizing Transportation and Shipping:

AI not only revolutionizes energy production but also improves transportation and shipping efficiency. Route optimization algorithms powered by AI can enhance the performance of shipping logistics, reducing carbon emissions by choosing optimal routes, packing techniques, and location choices. For instance, the introduction of cuOpt, a specialized library for route optimization used by distribution and transportation companies, has enabled a significant reduction in the environmental impact of shipping.

Tackling Environmental Challenges:

The future of renewable energy relies on addressing critical environmental challenges, such as capturing carbon emissions and exploring long-term storage and reuse options. AI is proving instrumental in these efforts by enabling oil and gas companies to deploy AI technologies to detect methane leaks and capture carbon, minimizing the industry's environmental footprint.

Promoting Energy Equity:

While renewable energy holds immense potential, it is crucial to ensure equitable access for all. Many underserved communities lack affordable access to renewables and energy storage solutions. AI can help bridge this gap by analyzing energy usage patterns, incentivizing the deployment of microgrids and virtual grids in underserved areas. This not only enhances access to locally produced energy but also ensures uninterrupted power supply during outages.

Conclusion:

Artificial Intelligence continues to shape the landscape of renewable energy, offering unprecedented opportunities for optimizing energy production, distribution, and consumption. As businesses and decision-makers, it is our responsibility to embrace these innovative technologies to successfully transition to a more sustainable future. By leveraging AI's capabilities, we can ensure a balance between energy supply and demand, promote energy equity, and empower consumers to make greener choices. Let us collectively harness the power of AI in renewable energy and work towards a cleaner and brighter tomorrow.


Video Insights

Topics Covered in This Episode

1. Intro to the energy industry and transition to renewables
2. AI's role in Energy production and distribution optimization
3.  Creating sustainable and green environments
4. Balancing energy and sustainability with generative AI


Podcast Transcript


Jordan Wilson [00:00:17]:

So we talk all the time about how AI can help power our economy, but can it literally power our future? That's one of the things that we're gonna talk about today on everyday AI. This is your daily livestream podcast and And free daily newsletter helping everyday people like me and you make sense of what's going on in the world of AI because there's a lot going on. And there's things going on that We might not even really think about in our day to day lives, like, how does AI impact our energy usage? And it's more than you might think, so stick around. We're bringing, one of the leading experts, from NVIDIA to actually help us Answer some of those questions about how, AI and power relate to each other. I'm excited to talk about it.

Daily AI news

But before we do, Let's get to the AI news like we do every single day, Monday through Friday. So let's start at the top. AI is here to stay in medicine, and I'd say it's in a big way.

Jordan Wilson [00:01:18]:

So Mayo Clinic, one of the leading medical institutions in the world, Has just recently appointed a chief artificial intelligence officer. Y'all, this is something I've been telling companies for many months. You gotta get a chief and Artificial intelligence officer. So, radiologist, Bhavik Patel was recently appointed to the role. So make sure you check that out in the daily newsletter Because also, in in quoted in the article is former guest and everyday AI regular, doctor Harvey Castro. So let's see what he has to say about it as well. Alright. Could there be a new type of generative search on the way? So according to some SEO specialists who spotted this in the wild, Google could be shying away from its traditional search generative experience.

Jordan Wilson [00:02:03]:

So, what's called the SGE, Google, debuted this a couple months ago that really changes what search results look like and, it relies much more on the generative experience. So, Specialists have spotted what they're calling SGE lite, which is essentially a stripped down version of Google's new Search generative experience. So it looks much much different, and people are wondering if this is kind of signaling from Google if they're stepping away, from this generative experience. I'm not sure. I actually just think that they're trying to ease it in, in a more gradual way. That's my take.

Jordan Wilson [00:02:45]:

Alright. Last, are smarter robots coming? Probably. So, Google's AI arm, DeepMind, is working with more than 30 other research institutions with the goal of creating a general purpose AI system that can work with different types of physical robots and perform many tasks. So, essentially, all these companies are getting together, and they're creating a better way to train physical robots. So the pro the the project It's called OpenX Embodiment, and it's already achieved a superior results in comparison to the commonly used methods for training robots. Wow. Smarter robots on the way. New Google search. Chief information chief, artificial information officers. So so so many things going on.

About Marc Spieler and the energy industry

Jordan Wilson [00:03:26]:

So make sure, if you haven't already, go to your everyday AI.com to sign up for that free daily newsletter. But You might be here to talk about AI's role in renewable energy. I'm excited for our guest. I hope you are as well, so please help me. Welcome to the show. Mark Spieler, the senior managing director of global energy industry at NVIDIA. Mark, good morning. Thanks for joining us.

Marc Spieler [00:03:50]:

Good morning, Jordan. Good to see you.

Jordan Wilson [00:03:52]:

Yeah. Alright. So, hey, just as a reminder, everyone joining us live, thank you. If if if you have questions about AI's role in, renewable energy and maybe what NVIDIA is working on in that realm. Get your question, get your questions in. We'd love to take questions on the show. And as a reminder, if you are listening on the podcast, check your show notes. You can always come in after the fact.

Jordan Wilson [00:04:12]:

Join the conversation here on LinkedIn. Mark, maybe just start us off at the top. Maybe just talk a little bit about what you do in your role, as the managing director of global energy, industry at NVIDIA.

Marc Spieler [00:04:24]:

Sure. So, I joined NVIDIA about four and a half years ago to basically come in and run their energy vertical. NVIDIA goes to market by industry, so I have peers across health care and retail and financial services. I run the energy industry. And what my goal is and role is is to take our horizontal platforms and software stacks and use them to solve problems in the energy industry, And then build an ecosystem of partners that can leverage those software stacks and create solutions for end customers To leverage AI, high performance computing, visualization, but specifically targeting energy industry use cases.

Jordan Wilson [00:05:06]:

So, you know, real like, let's even hit rewind, because, you you know, I think maybe if you don't follow, energy, and I know not all of us do, but, it it it seems like there's a lot of, problems or challenges in the industry, in the in energy industry, because more and more, you know, the everyday person, companies, it seems like everyone's energy needs are increasing. Right? So maybe maybe, Mark, could you just talk a little bit about some of those challenges you face because of this, increased energy, consumption and and demand as well.

Marc Spieler [00:05:39]:

Sure. So the energy industry is is is huge. Right? Most Countries, economies are based on energy. Right? Typically, oil and gas, but now more and more renewables. Right? Every country requires energy to perform, and that mix of energy, and you hear the industry talking a lot about the energy transition and, You know, we originally went from from burning wood to oil and gas and coal and and now to renewables. Right? That transition has has been going for for as long as we've had energy. Right? And and now the goal is is how do we Help create the increasing demand for energy in the most environmentally friendly way as possible. And so how do we continue to develop The oil and gas requirements that we need in order to have reliable and resilient energy production, But how do we replace those with renewables in a way that we can depend on those things and store the the energy that's created in In the forms of either hydrogen or in batteries and others, for when the wind isn't blowing or the sun isn't shining.

Marc Spieler [00:06:52]:

Right? So that whole energy space is very dynamic. And some of the world's largest energy companies Are looking at how do they accelerate that, transition, but how are they able to meet the energy demands at the same time. Right? And so the technology is not quite there, but AI is is helping them develop new solutions fast. And then the biggest thing is probably how do they balance? How do they balance the the, supply and demand? It used to be pretty easy. Now it's it's highly complex because energy is being produced in far more places, you know, rooftop solar, battery walls, EVs that plug in and push back to the grid, all of those things. It's very complex, and so the industry is is adapting the best they can, But regulations are pushing very fast as well.

How AI is used to combat energy consumption


Jordan Wilson [00:07:49]:

Yeah. And, you know, you brought up so many so many great points there, but it it spurred a question, in my mind is, you know, when the average person, right, is is using more energy. You know, you brought up a great example is, you know, there's more electric in cars. You know, there's more electric vehicles, you know, now than there were, you know, 5 or 10 years ago, and and even things, we don't really think about. Right? Like, a lot of our, you know, listeners and and viewers use now generative AI, you you know, pretty pretty frequently, and that creates increased energy demands. So, you know, with all of these, kind of, I guess, new, energy suckers, right, at, like, everything that needs the energy. How specifically is AI even used, you know, to address these things? Because I think sometimes we just say, oh, AI can do this and AI can do that. But specifically, you know, how can AI, address kind of balancing this this energy, this energy need?

Marc Spieler [00:08:47]:

Sure. So let me let me provide a, a scenario that most people are used to. Right? I have to get across town. I have an eleven meeting. What time should I leave my house? Right? And what's the best route for me to go? And, when I was a kid, my dad used to get up really early, And he used to watch the news before work. He'd see where there was traffic, and he would make a decision. Once he left the house, he was all in. Right? Because he didn't have real time updates.

Marc Spieler [00:09:16]:

Today, we put it in our navigation system. It tells us it's gonna take 19 minutes to get to this location, and here's the route I need to go. Right? As we get more and more cars on the road or if there's an accident or a downfall, we start to see that, You know, we get rerouted. Right? And that the time frame expands. Well, energy is gonna be the same way. Right. You know, as as we start to put more and more, electric vehicles on the grid, as we have people producing their own solar locally, How much energy needs to be produced, and where does it need to be moved in real time? Does somebody have an electric vehicle? Does somebody have a generator? Do they have, solar? So the ability to monitor those things in real time and to be able to make good decisions means that we're gonna have to produce less energy, Unless energy will be wasted. If if we had to put, you know, 3 times the cars on the road in the next 7 years, And when we talk about the goals for EVs and everything else, it's far more than 3 times.

Marc Spieler [00:10:20]:

Right? You could either build credibly amounts of infrastructure and new roads, or you could redirect traffic using technology like Waze. What we're saying is is there's no way to build enough infrastructure to accommodate, so we're gonna have to use AI. We're gonna have to simulate what's gonna happen, And we're gonna have to take real time data feeds computed at the edge and basically create a balanced grid using artificial intelligence.

Jordan Wilson [00:10:48]:

Yeah. And and, you you know, maybe let's talk about that a little bit because these are things, you know, I I wasn't even aware of. We were briefly talking before the show. But talk about, like, the importance of balancing the grid because, you you know, essentially, in times, if energy is is not Used. It's wasted. Right? So, like, talk a little bit about that and then how AI is is, can help solve some of those challenges of of balancing it.

Marc Spieler [00:11:13]:

Right. So if if you think about in the past, right, we had very centralized energy generation. Right? Big and Oil and gas turbines, coal turbines, steam turbines, those things. And basically, they would push out one direction. Well, today, they're Those things still exist and they produce a lot of the energy, but you also have batteries throughout the grid. You have EVs. You have people with rooftop solar, you have solar farms, windmills. We've expanded from, I think it was 8,000 points of generation in the US, to millions of points of generation and storage.

Marc Spieler [00:11:50]:

And so if if you think about, you know, how much energy They need to produce at centralized plants. They they predict that, right, based on the temperature, based on how much, Like, electricity can be produced out at the edge, and they make their best estimates. And when they have excess capacity, They have to either sell it off less expensive and and try to store it, but if there's no place to store it, they end up having to run it to the ground. And and that's expensive and it's wasteful. So, you know and they don't wanna create too little, right, because some people then won't have enough energy, and we've seen this when we have Storms and other things or bad weather and and parts of the grid are down. So that balance is gonna become even more critical ad As more distributed energy resources come online, and the amount of time it takes to interconnect these things It's significant because they wanna study it and understand how much power is that gonna take off the grid and put back on the grid. And I think AI is gonna accelerate that time because as the customers or businesses wanna add new Energy resources onto the grid. AI can quickly analyze the capacity, the impact, and allow people to have much and Quicker interconnects into the grid.

Making energy plants efficient using AI

Jordan Wilson [00:13:16]:

You know, hey. And just just as a reminder, if you're joining us, we have Mark Buehler, the senior managing director of global energy industry at NVIDIA. So if you have questions, make sure to get them in, you you know, for our audience here on the livestream. You know, Mark, one thing you've talked about is kind of on the front end, how AI can help the everyday person make smarter decisions, whether it's their their commute or something else. And then on the back end kind of in in energy storage and and, you know, making sure we're not wasteful, with the energy and balancing it on the grid. But, I'm I'm I'm curious. What about the actual production? Right? Can can AI, help and make, you know, energy plants, and more efficient, and and if so, how does that work?

Marc Spieler [00:13:58]:

So once again, there there's a lot of ways. So generative AI can help with designs. Right? Design more efficient, turbines, gas turbines, coal turbines. It can help produce more, more efficient, wind turbines. One of the things that we're doing right now is we're working with a few different wind companies on combining weather forecasting with how they design an actual wind farm. Right? Because one of the things you need to think about is a lot of people think that you wanna optimize the performance on a single wind wind turbine, But really, you want the entire wind farm to be optimized. And that may mean sub optimizing some of the, turbines at the beginning So that you get better production later on. And so, basically, we we have tools called, that are used for wind wake optimization.

Marc Spieler [00:14:55]:

Right? Just like off the back of the boat, when you're driving the boat, you see the water wake off of the back. When you have lots of different wind turbines stacked in rows, the the wind that's coming off of the back of those creates, An impact for the turbines behind it. And so you wanna make sure that when you set up a wind farm, that you're optimizing for the complete inform and using AI and and what we call physics machine learning, where we actually teach machine learning models or neural networks physics, We can actually simulate the impact of that wind without having to do full physics simulations, which may take months. We can now do it in in minutes or hours, and therefore, we can continue to run different scenarios to really get the most production. And then when we overlay weather data and and predictions, we can actually determine the best location and the best design for a wind farm, Thinking out 10, 20 years, not just what the impact is today.

Innovations in Green Shipping

Jordan Wilson [00:15:59]:

Right. It's it's Fascinating, yeah, that that you can take, you know, and I think people that use generative AI, you you know, you know, these tasks that used to take, You know, hours or or days, you know, you can be, doing now in in minutes. So it's it's fascinating to hear that, you know, kind of these these same, you know, large gains are being made, around our energy, which is just fascinating. So a question here from from Stuart. Stuart, thanks for joining. So he's asking, love to hear anything about how green shipping, example, large tankers moving around through oceans, freshwater rivers, to shift off fossil fuels. So asking anything you can point us to on innovations around green shipping.

Marc Spieler [00:16:43]:

That's a that's a great question, Stuart. So there there's a few things that AI can do in in those situations. One is You can optimize the, the transportation routes and who's carrying what. Right? That that to me is one of the easiest things is how do we make sure we maximize the impact of the shipping and the routes? And and, you know, it's kinda like a traveling salesman type mentality is is as you're going around and distributing things on ships, how do you optimize And and reduce the route and reduce the the carbon emissions and and all of those required To get product from place to place. So there's a lot of tools out in the market. We've introduced a library called cuOpt, which is being used by, Quite a few companies that do a lot of distribution and transportation, and really it comes down to how do you optimize those routes, How do you put in as much information about the specific ship or truck or others to understand what features and functionalities that you're in, and then really optimize that. As far as shifting off of fossil fuels, right, it really comes down to the storage of of, You know, energy. Right? Batteries, hydrogen, other things that that ship is gonna have to run off of.

Marc Spieler [00:18:07]:

And and really, we're seeing a lot of development in those areas. Right? A lot of the large energy companies are investing significantly in hydrogen. Right? And They're they're investing significantly in battery technologies and others, but, you know, that that that's gonna be a work in progress for a while. And so, You know, just like we talk about with, data centers and other things is you can start off by by by optimizing what you have control over. Right? And that's routes and packing and dropping off and picking up at the right locations. And then eventually, you move to renewables as as the next step in in creating more green environments. And, so that that's what I'd suggest. I'm not sure that There's a short term solution for some of these big big ships, but I tell you, the energy companies are all really focused on, you know, different ways of capturing carbon and and then long term storage and reusing some of the carbon that's been captured off of, You know, fossil burning, environments.

How AI helps production in underserved communities


Jordan Wilson [00:19:15]:

Yeah. No. That that Mark, that is such a such a great response, you know, because you you you laid out the, kind of a 2 tiered approach on on how AI can be used kind of in the shorter term, and in the longer term. So, great great response there. We have one more here from, Cecilia. So, Cecilia, thanks for your question. So asking, Mark, you you know, we're saying she appreciates the need for balancing production centrally. Have you seen ways The AI is being used to begin democratizing or socializing use of renewable, energy in underserved communities.

Jordan Wilson [00:19:44]:

So, yeah, I'm I'm interested in this, you know, as well, whether it's, you know, rural or, you know, other parts of the world. You you know, maybe how can, AI help in In, production in underserved communities.

Marc Spieler [00:19:56]:

Yeah. So so that it's a great question. And energy equity is a is a huge issue right now. Right? And and And, obviously, renewables and batteries and those things are are not the not the cheapest things right now. Right? While they're really good and people want to adopt them, They're not necessarily affordable for everybody. And so we're working with a few different companies on getting a better understanding of how energy is being used in underserved Communities, and how do we create an environment where people who have access to renewables can share that, whether they have rooftop solar Or whether they have battery walls or EVs, how can that be used by people who maybe can't afford it? Right? And and when you talk to regulators, there's A whole discussion around carrots and sticks. Right? And I'm I'm not a regulatory guy or a lobby guy, but I've I've had to learn over the last in years since we moved into as I've moved into this regulated industry. And really, it's how do we incentivize people who have Access to renewable energy, and incentivize them to share it, and basically create environments In which there are commercial reasons for people to make investments in these underserved, communities by ad Providing either low cost loans by providing access so that we're in a situation where, especially when the power grid does go out, That you're created you're able to create these micro grids and virtual grids, and actually provide underserving communities with access to energy That's being produced locally.

Marc Spieler [00:21:36]:

Uh-huh. And so it it's definitely something that every utility executive that I talk to Talks about, and we've actually worked with some of them to apply for some, government grants coming out of the IIJA and others With a focus on creating applications and tools for underserved communities to measure and quantify How they use energy and how we can embed more distributed energy resources into their communities.

NVIDIA's smart grid chip

Jordan Wilson [00:22:04]:

Wow. Such a, again, such a such a deep and detailed answer. I love it. This this is something I'd love about, you know, having this, this live dialogue is is being able to ask, you know, people, who are really leading the industry in these fields, you know, their their their feedback and input. So, another great one because, yeah, we've we've talked about a little of everything, but I'm wondering, Mark, and and so is Monica. Specifically, you know, When we talk about AI and and energy, maybe what's the most exciting project that you're currently working on that you're able to talk about?

Marc Spieler [00:22:38]:

Sure. So probably, you know, and I just mentioned it right now regarding the, energy equity. We're we're working with a small, I I won't call them a startup, but they're a small company. It's called Utilidata. And they've been in the industry for for about 14 years, and we're working with them to create What what we're calling a smart grid chip that will go actually out to the edge and sit on people's houses, right, in the form of a meter. And think about your iPhone today and all of the capabilities that an iPhone has. Well, that's significantly different than today's smart meters. Today's smart meters are really good at 2 things, making sure your bill's accurate, and turning off your power if you don't if you don't pay your bill.

Marc Spieler [00:23:20]:

Right? And so those those are what we would call the metering aspects. But really, the future of energy is how do we understand what's going on behind the meter And in front of the meter to create an environment where the consumer actually has more control of how they manage their power and, You know, even to the point where they can load e contracts, they could see metered, muted communication so that if a branch is Hitting a wire between 2 houses, we'd be able to to identify a vegetation management issue and go get it addressed. Right? To to understand who has power, who doesn't, and understand how do we share that power By incentivizing people to to do things that, that they might not be able to do today because there's not enough technology at the edge. And it really requires that real time capability so that, you know, electrons move very fast. And and you and I talked about, we've talked about ways, right, and the ability to, you know, redirect traffic if there's an accident, but electrons move a lot quicker. And so if if we have a failure, how do we redirect? How do we get energy back online? How do we give people control over How they consume their electricity. That that that's gonna be great. And and it's gonna create an environment where we're gonna have an open ecosystem similar to An Android store, right, that basically allows everybody to create apps that can run on this, and utilities can build their own apps.

Marc Spieler [00:24:54]:

There are only third parties, but, really, it it's gonna be an exciting time to democratize the way in which people Consume and and supply energy moving forward.

Future of energy with Gen AI

Jordan Wilson [00:25:06]:

Yeah. It's fast you you know, that's that's a fascinating response because it does seem, now now that you say it out loud that, you know, hey. These smart meters and I think we hear about these, but it doesn't seem like they're at least now very smart. Right. Right? If if if if there's so little that they can actually do, but it seems that the, potential impact, of of what you just talked about there, Mark, is is pretty is Pretty monumental. You you know, I have another question. So if, you know, when you kinda just talked about, like, one of the most exciting things that that you're working on. But Maybe, you know, specifically, in the last, you know, year or 2.

Jordan Wilson [00:25:43]:

You know, I know NVIDIA is actually helping power, you know, this whole generative AI movements, you know, producing, you know, these chips that, you know, we all kind of need in these, and you know, generative AI systems that that we use. But, specifically, when it comes to energy, I mean, are there any, you know, I guess, recent generative AI advancements that maybe have happened, in in in the last year or 2 that are maybe gonna change, how we deal with energy in the future. You know? So I'm wondering if some of those developments that, You know, us everyday people, experience in our day to day lives and in our jobs, you know, might be changing kind of, how the way that we deal with energy.

Marc Spieler [00:26:27]:

That's that's a that's a complex question, obviously. You know, I I think the the amount of energy that's gonna be needed to solve a lot of the work that we're doing with generative AI is is obviously gonna increase. Right? And, you know, I think people are going to be in a situation where They need to figure out, you know, the most cost effective way of of of consuming that energy, producing it, consuming it, And and, of course, everybody has in the back of their mind sustainability and and efficiency. So as as we look to And all of those things. Right? You know, similar to the the question about shipping. Right? It it it's a multi tiered approach. How do I become as efficient as possible on the energy that I do use? And then from there, how do I make sure that energy comes from Renewable sources where possible, but when when not possible, how do I make sure that the energy I'm consuming is is developed in the most Environmentally friendly way as possible. So, you know, our team is is very diverse here at NVIDIA, and and we go to We go to market with a lot of third party partners.

Marc Spieler [00:27:43]:

Everywhere from the oil and gas companies who are trying to drill less wells to be able to Capture carbon at the point of drilling, and look for methane leaks, and methane detection, and all of those things as they move natural gas through pipelines, And use drones to identify, corrosion and stuff to make sure that there's no environmental impacts. They're all using AI for that. And then the renewables companies that are are are trying to do everything they can to make renewables more cost effective, to make sure that they're and Reliable and resilient and tied into that. But but then the consumers, right, have to think about how do they Consume power as effectively as possible. And you and I talked briefly about data centers. Right? And obviously, generative AI and the The amount of compute that's gonna be required in the world moving forward is significant. And, we just participated in a in a summit A couple weeks ago, my CTO, Ken, talked about data center growth, and and a lot of these companies are looking at 8% power growth Year on year in the data center and some are seeing spikes of 25%. Right? And and, you know, those data centers are working.

Marc Spieler [00:28:58]:

Those data center companies work closely with us to, potentially simulate, create digital twins of of data centers. We work with a lot of companies that produce, components for those data centers to make sure that there is energy efficient as possible. But the biggest thing that draws energy within those data centers are the compute resources. And really, it's gonna come down to Compute per watt. Right? And how much performance or outcomes do you get per watt of energy? And, you know, that's a measure that Jensen, our CEO, takes very seriously, and he he continuously focuses on how do we increase application performance To reduce the amount of watts required to solve a problem. Right? So, you know, it's not just about, okay, this CPU is It's a 100 watts and and this GPU is 200 watts or whatever. And so that's not the comparison because if If you need 10 of those CPUs to do the work of 1 GPU, right, all of a sudden, the problem costs a lot more energy. Right.

Marc Spieler [00:30:04]:

And so how do we accelerate the adoption of accelerated computing? How do we create lower Power, GPU's, CPU's, data processing units, the whole impact of what's going in the data center. In How do we make it as efficient as possible? And that's where software defined infrastructure is very important, because As you see with some of the the autonomous car companies. Right? They come up with a better piece of software, they do an over the air update, and you get Twenty more miles to char per charge. How do you create software stacks that when you upload them onto the systems, You can actually get 20% more output for the same infrastructure that you've already deployed at the same power envelope. So We continually look at ways in which we can increase the output per watt, and, we're committed To continuing down that track both from a hardware pers silicon or hardware perspective, as well as software, which tremendously impacts The performance per watt.

Marc's final message about AI and energy

Jordan Wilson [00:31:08]:

You know, Mark, we've we've talked a little bit about everything, which I love. We've talked about How AI can be used, to help reduce the environmental impacts of oil and gas. We've talked about how AI can be used to increase production, from renewables. But maybe, as as we wrap up the Everyday AI Show here, what is maybe that one takeaway message that you want people to to understand or to kind of glean from this conversation about how AI is kind of being used to to power our future. What's that one message that you really want people in to understand on on how it is or how it could be used.

Marc Spieler [00:31:46]:

I would encourage everybody, especially those working in the energy industry, to start fast. Right? Don't, you know, find a project. Find find a solution that you believe can be impacted by AI and try it. Right? You know, I think there's a whole wait and see mentality, especially in the energy space. We tend to be a very conservative industry. Right? People nobody thinks an energy industry when their power's been running for for, You know, 6 months with no interruptions, but the second it goes down, everybody's frustrated. Right? You know? And and what I would tell you is is that It's an industry that's extremely conservative, but there's opportunities, and I think there's things that we envision are gonna happen. Start now.

Marc Spieler [00:32:35]:

Engage with the the cloud providers, the Microsofts and the AWS and the Googles. Engage with the the hardware providers. Engage with NVIDIA. Right. Call me, reach out to me, and let's talk about a big problem that you anticipate facing, and let's figure out If AI can solve that problem, and and let's try it. And if it works, great. If it doesn't, let's move to another problem. Like, there's, I I think that hesitancy is is we don't have time for it.

Marc Spieler [00:33:03]:

With the acceleration that we want with electric vehicles and everything else, ad We need to start now, and that's what I would encourage people to do. Start a project. Try it.

Jordan Wilson [00:33:15]:

Yeah. I love it. And, you know, Woozy saying, super interesting, great stuff, and, you know, and and we'll we'll wrap with this. You know, Mark saying, so or or sorry. Brian Kennedy saying, everyone is Talking about AI being the end of the world. Thanks, Mark, for showing how it can also save it. So we talked about so much. If you missed a little bit, Don't worry.

Jordan Wilson [00:33:36]:

Just make sure to go to your everyday AI.com. You know, Mark Mark dropped a lot of great resources, different programs that NVIDIA's working on. We'll be sharing all that in the newsletter. So if you're not already signed up, make sure to do so. Mark, thank you so much for joining us on the show.

Marc Spieler [00:33:50]:

Thank you so much, Jordan.

Jordan Wilson [00:33:51]:

Alright. We hope to see you back again tomorrow and everyday for more everyday AI. Thanks y'all. Thanks.

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