Ep 312: Is AI only a resource hog? A greener side to AI

Episode Categories:

Unlocking the Green Power of AI: An Initiative Towards Sustainable Businesses

In today's technologically driven world, an innovative approach is emerging at the intersection of artificial intelligence (AI) and conservation. This approach consists of using AI-powered tools to restore biodiversity, primarily by fast-tracking global tree plantation efforts to outstrip deforestation rates. The strategy involves a four-pronged process: landscape analysis, AI-powered plant data match, digital twinning of landscapes, and precision plantations through drones, further melanging into continual landscape monitoring.

Boosting Efficiency: Drone-enabled Precision Planting

Here's an intriguing fact: precision planting with drones - facilitated by AI - can speed up tree planting processes by 13 times compared to traditional forestry methods! This efficacy leap is a testament to the boundless opportunities AI could unlock to make businesses both productive and eco-friendly.

The Backbone of the Initiative: AI Technologies

A variety of AI technologies and components play key roles in the conservation process. Advanced tools like LIDAR are used for landscape analysis. Data is collated and stored on global servers using savvy algorithms, predominantly developed in Python. AI also crafts scenarios and make pertinent reforestation decisions, accounting for biodiversity, soil analysis, and environmental changes.

High-tech and Local Traditional Knowledge

The fusion of sophisticated technology (drones, robots, AI) and local traditional ecological knowledge can have substantial results in restoring landscapes. By liaising with native indigenous communities for endemic knowledge, businesses can strike an effective balance between traditional and innovative approaches.

Reducing AI's Carbon Footprint Through Innovation

However, the immense potential of AI should not overshadow the issues of its energy consumption and carbon footprint. That said, strategies such as deploying digital twins for landscape analysis and energy saving can help offset AI's environmental impact and direct companies towards a more sustainable future.

Begin your Green Revolution with AI

Every leap towards progress can be daunting, yet essential. As business leaders, it's time to consider incorporating AI into your eco-conscious steps. The greener side of AI is growing exponentially and embarking on this journey could be easier with the right guidance and support.

To a Greener AI Experience

As AI continues to evolve at an unprecedented pace, it's crucial for businesses to engage with its environmentally friendly side. It's possible to create a greener, more sustainable future with AI, and it begins with a single step. Reduce emissions, conserve biodiversity, and enhance overall business productivity – AI has a lot more to offer than being a mere resource hog.

Topics Covered in This Episode

1. Overview of Perplexity
2. Differences Between Free and Paid Perplexity
3. Use Cases of Perplexity
4. View and Edit Sources Using Perplexity
5. Future Implications of Perplexity

Podcast Transcript

Jordan Wilson [00:00:17]:
When looking at artificial intelligence, I feel sometimes we only look at what it can accomplish, but not what it costs, or what we should be doing as business leaders to maybe offset that cost. Because here's the reality. When we're using generative AI, when we're using large language models, it's extremely resource heavy. So much more so than, you know, doing other things that you may be doing on a day to day basis on your computer. So I'm excited today, to to have a special guest on. We're we're gonna be talking about is AI, just a resource hog, or is there a greener side to it? So we're gonna be talking through some exciting use cases, on how this organization is using AI to what I think to create a very greener future. Alright. I'm excited for today's episode.

Jordan Wilson [00:01:11]:
If you're listening on the podcast, as always, make sure to check your your show notes. You can click and go to your everydayai.com. Sign up for our free daily newsletter. We will be recapping, today's show in great detail as we do every single day written by me, a human. And normally, we do this live and we go over the AI news, but our guest today is from Australia. So, you know, normally at that time, it would be, I don't know, like 1 AM or something like that. But we will still have the AI news and everything else, that you love, in today's newsletter. So make sure you go check that out.

Jordan Wilson [00:01:45]:
Alright. With that, I'm excited to bring on our guest today to talk about this other side of AI, the greener side, and how they're using AI to, really do more impactful work and hopefully inspire some of you all to think about, using AI in the same way. Alright. So please help me welcome to the show. There we have him, Emrick, Modu, who is the founder and CEO of Lord of the Trees. Aymeric, thank you so much for joining the Everyday AI Show.

Aymeric Maudous [00:02:15]:
Thanks, Jordan. Hi, everyone.

Jordan Wilson [00:02:17]:
Alright. And, hey, Aymeric, can you tell us a little bit about, what you all do, at Lord of the Trees?

Aymeric Maudous [00:02:25]:
Yep. So in a nutshell, we use drones, robotics, and AI to restore biodiversity. So, you know, mainly plant trees, all around the world. So the aim, really, the mission is to, heal the planet or, you know, plant more trees at a faster rate than than we destroy it.

Jordan Wilson [00:02:47]:
And I think that's a great mission, and and we'll talk about that more later because I think when it comes to AI, there's there's definitely a side that people don't look at. But before we get into that, Aymeric, I'd I'd really love to hear just maybe some examples of even how you are using AI. Right? Like when we talk about planting more trees, that's, I think a cause we should all be paying more attention to, but, in my mind, I think of it as a very laborious process. Right? Like going out there, you know, probably having groups of people walking around, finding the best places. How do you all use AI, to make that process maybe a little more efficient?

Aymeric Maudous [00:03:25]:
Yep. So the way we work is, really divided into 4 phases. We on phase 1, we do, landscape analysis. So depending on the size of the terrain that we have to work on, It could be anything. It could be, rehabilitating a mine that's closing down. It could be assisting governments after bushfires, wildfires, and we are starting now to work with farmers as well. So depending on the size of the terrain and, of course, the accessibility, we, either send a drone. So the pilot, the copilot, and then a little, array of drones, or we use satellites.

Aymeric Maudous [00:04:10]:
The data that we collect is then, processed to that stage 2. And that's when AI, comes into play where we look at the data that we've collected into the landscape, and we match that with the plant requirements. So each species, as you know, has different needs and wants. Some plants like sun, some likes a bit more shade, some likes to be in drier parts as opposed to others that like very moist environments. Some are not susceptible to wind, etcetera etcetera. We look at soil quality as well, some like acidic versus alkaline soil. And based on these, data that we have on the landscape, we match that with the plant requirements, and we create, what we call a digital twin of that landscape. And AI helps us to come up with what is in theory the best planting plan for this particular, this particular landscape.

Aymeric Maudous [00:05:17]:
Once we have that into place, we use AI again to help us calculate with precision, how many seeds of each pieces will be required for this particular job. We then go on, onto phase 3, which is the planting. There is 2 things that happen here. We, we for temperate forest, we create what we call seed pods, which is, it's all done in a lab. Each little seed is isolated and we make a little backpack of nutrients to give it the best chances of survival and better chances of of germination while it's dropped into the landscape. We load those, seed bulge onto a drone, then we fly the drone into the landscape. And based on the result from the AI, the drone, which has been pre programmed, can shoot with precision. So we do precision planting.

Aymeric Maudous [00:06:15]:
We fly the drone no more than, 3 meters above ground, which is 7 to 8 feet maximum. So we we we're not going too high in the sky when we do that just because we wanna make sure, the seed pods are in the zones that have been identified, for the best, chances of survival. And that use of drone technology and robots, enables us to cut the time spent by about 13. So we can work in essence, we work we're able to work 13 times faster, than if this was done by hand on the back of a tractor using traditional forestry methods. Once this is done handed, the drone, as you can imagine, can access difficult to reach terrains. We work on all weather conditions as well. The drones don't take breaks, And they work at night as well, which is great when we have, when we have big landscapes to reforest. And after after the planting is done, we move on to the last phase, which is, the landscape monitoring.

Aymeric Maudous [00:07:28]:
This is the phase that takes the longest, when we build carbon credit projects. We are there. We are going to do the monitoring for the next 20 to 30 years. So, usually 20 years in landscape environments, 30 years in more temperate, forest. And when we work on biodiversity projects, that's a 99 years, time frame that we're looking at. So yeah, that's really us, you know, that's that's how we use AI, in our operations.

Jordan Wilson [00:08:00]:
So now now I have so many questions. Right? So let's start here because that was a lot to unpack all at once. So, you know, Emeric, you talked about kind of the different phases or different stages that you're using artificial intelligence to just grow more trees. Right? But, you know, can you maybe walk us through, how it actually works? Right? So, even like AI. Right? When we when we use AI, sometimes it just becomes a buzzword. So, you know, are are you using, you know, traditional artificial intelligence, you know, deep learning, machine learning, algorithms you're building in house, or are you using, like, as an example, you know, APIs of of common large language models that we use daily like, on a daily basis, right, you know, from OpenAI, Gemini, Claude, etcetera. So, yeah, walk us through a little bit more of the technical side and also, you know, what, that has led to in terms of, you know, just more efficiency and productivity?

Aymeric Maudous [00:08:59]:
Yep. So to answer your question, it's really all of the above. It's, it's quite extraordinary. So when we, when we send, when we do landscape analysis or, the monitoring of the landscape, we collect as we fly the drone. I'm gonna I'm gonna stay with the drones because we use, you know, drones and satellites, but, let's keep it simple. Let's let's let's stay with the drones. We use, for landscape analysis, a a LIDAR component that's attached to the drone, and then we fly fly the drone. We collect 2, 000 data points per second.

Aymeric Maudous [00:09:37]:
So you can imagine the enormous amount of data after an hour of flying that we collect. This data is stored, in into servers that are scattered all around the world. And after that, we develop our own, algorithms. So we use Python for that. It's all in house built, And we add layers, and think of them as, there's a layer for each plant species that we use as I explained earlier. But there is there are external layer. We call them external layers when it comes to biodiversity. We have a very unique way to engage and look at landscapes that we work on, which is a very holistic way to to work where we actually instead of zooming in, which we've already done with the landscape analysis, we actually zoom out.

Aymeric Maudous [00:10:34]:
And we need to understand what is around and what is going to impact the landscape. Working with nature is always like, it's not something that is static. It's always moving. There is there is always something happening. There is not 1 day which looks like the day before. Every day is unique. The weather can change from 1 day to the next. You you species move into the landscape, at any time and we take that into account.

Aymeric Maudous [00:11:08]:
So just to give you an example, related again to AI, we look at and when we look at, biodiversity that can help us with mainly focus on birds and small mammals that are going to help us as we regenerate, the landscape, that are going to help us to naturally disperse their own seeds, into the landscape. And when it comes to soil analysis and soil biodiversity, we are very, we we look a lot at, fungi and how fungi, is already present in the particular landscape that we work on, but also around, the landscape. And that's very important especially when we work on on grounds that have been severely burned. 3 years ago, I'm not I mean, I'm sure you've heard about, the big fires that surrounded Sydney for more than 5 months. And those fires, same as in California recently, were so intense that they've actually completely sterilized the soil. And, this they completely burned the natural seed banks occurring in the soil, but they also completely decimated the fungi that helps in in creating the mother forest, which is a healthy soil for for those of them. So we look at all of that, and AI helps us to, yeah, we with creating scenarios that we layer on top of that digital twin, help us to make decisions or actually change a few things that we sought might work, but actually, it turns out that it's probably there's probably a better way to to look at that. So it's a very interesting, way.

Aymeric Maudous [00:12:55]:
Now when it comes to so that's on the reforestation side. When it comes to the tech side of things, as I said, we use so there's 2 elements that work in perfect symbiosis in our operations. You have the high-tech. So it's, obviously, the technology, the drones, the robots, and AI that work in harmony with low tech. And low tech is so it's high-tech and low tech. And low tech, it's it's a term that was created by, an amazing person. Her name is Julia Watson. It's spelled L0TEK, and it stands for local traditional ecological knowledge.

Aymeric Maudous [00:13:41]:
And it is all that, ancestral knowledge of the land and the forest, which is, kept, by the forest people, the native indigenous people that we work with, which is something that AI doesn't know, or, you know, so machine learning comes into play in that regard. So I give you a few example, when it comes to understanding the landscape In that regards, we look at plants that are, that have medicinal or cultural value that those forest people would use for cultural practices. We look as well at the fire management, which is a big, it it's very unique in the case of Australia to have regular, fire regimes in order to help the landscape. This has been done for, you know, thousands thousands of years. I know there are different policies around the world. I used to live for 4 years in California, and I remember Smokey Bear, you know, as soon as you see yes. Yeah. Now the problem that you have with that is, when is you have an accumulation of liter, onto the ground so that the day you have fires like the ones that occurred last year and the year before, in California, you have an incredible amount of liter that is stressed as the fuel, and it's that is creating, even bigger fires.

Aymeric Maudous [00:15:17]:
So that's 1 thing that we take into account. And the last 1 is anything, the ancestral knowledge that surrounds the, the collecting of the seeds.

Jordan Wilson [00:15:29]:
Yeah. And I think, Aymeric, like that combination that you just talked about there, that kind of high-tech, low tech, I think it's extremely important. Right? Even if we're thinking, in a corporate setting, right, to still have the high-tech of generative AI, but you still have to have that low tech, right, or that local knowledge of your people. Right? And III think it's important to strike that balance. And and going back to something you said there, I did some rough rough math. Right? So 2, 000 data points per second, an hour of flying. That's, like, more than 7, 000, 000 data points. So you have a lot of data.

Jordan Wilson [00:16:02]:
You're using a lot of AI, and that's resource heavy. Right? But at the same time, you guys are literally making the world greener. So before we transition, I do wanna ask you, like, just overall, how many trees are you planting, or how many acres are you able, to to reforest a year using kind of this high-tech, low tech, sweet spot combination. Hey. This is Jordan, the host of Everyday AI. I've spent more than a 1000 hours inside ChatGPT, and I'm sharing all of my secrets in our free prime prompt polish ChatGPT course that's only available to loyal listeners like you. Listen to what Lewis, a business owner, said about the PPP course.

Jordan Wilson [00:17:13]:
Everyone's prompting wrong, and the PPP course fixes that. If you want access, go to podpp.com. Again, that's podpp.com. Sign up for the free course and start putting ChatGPT to work for you.

Aymeric Maudous [00:17:30]:
Yeah. Yeah. So when it comes to I mean, that's a good point. I I wanna go back to your first point, which is the energy resources that we use. We are very aware of that. And when you look at, what we do, the you can't really even when you have a service, it could be any service or any product. The end product or the end service that you provide cannot be looked at on its own. You you really need to have what's called a full picture of the life cycle of your entire operations from anything that is being created with the tools that you are using.

Aymeric Maudous [00:18:12]:
In our case, AI plays a big part of it. You mentioned the enormous amount of of data that we collect that is stored in in in those data centers or run away. So we are very aware of that, and there is, it's part of our DNA, obviously, to use AI for good and to use drones for goods and and to do good for the world. So we're very aware of that, and we monitor all of those emissions, and the weight of the resources or the additional resources that we put, on the planet to actually sustain our operations. Now we're very lucky in the sense that, yes, we we do plant our own trees. So to go back to your second to come back to your second questions, the swarm of 4 drones, in 48 hours can plant a 1000000 tree, a 1000000 seed bones. So that's 48 hours. We allow, 4 hours total out of those 48 hours for, battery, and seed refill.

Aymeric Maudous [00:19:19]:
But all in all, those 4 drones can work tirelessly for 48 hours and plenty of 1, 000, 000 seed points. Now, we recently became, a b corp, maybe a months ago, and we we so we record our, we have a very good understanding of our emissions, not just when we travel to go from point a to point b with with with with the team, but on the resources as well that we put when it especially when it comes to electricity because that's mainly, you know, AI being powered by, you know, with energy. And, and we plant more trees, than we, consume. I'm gonna say that, yeah, than the energy that we consume. So we're lucky in that sense, and I'm very, it it's something that is very ingrained in the DNA of our company. It's part of our culture as well, the company culture. And for everyone listening to the show today, I think we have a duty as, you know, custodians of this planet to do the best we can. It's not, you know, it doesn't have to be complicated, you know, planting trees or or being supporting projects, like like the ones that we have that actually do good for the planet, and create more positives than negatives are a big part of of that, that mentality that we all need to get as a collective in order to make, yeah, in order to to be flourishing as a species.

Jordan Wilson [00:20:55]:
Yeah. You know, Aymeric, again, great great points you bring up there because, yes, you're using a lot of AI, but you're obviously literally making the world greener and, you know, the ability to plant millions of trees in a week, which is which is pretty fascinating. But, you know, not everyone's in that position. Right? But and and the the use of AI is is just going up. A Morgan Stanley report recently said generative AI's power demands is expected to grow 70% annually. You know, another study that came out showed that a simple ChatGPT query, you know, requires 10 times more power than even a simple Google search. Right? So I know there's no easy solution to that. Right? It's like, okay.

Jordan Wilson [00:21:40]:
Everyone's gonna be using AI more, yet there is this, kind of almost ugly underbelly of it. So, for companies out there, for business leaders that aren't in your position, right, who aren't able to plant millions of trees, what are some of the decision making processes, or what important questions, do business leader leaders need to keep in mind when it comes to their generative AI use?

Aymeric Maudous [00:22:03]:
Yep. So I think you need to, yeah, look at I mean, that that's exactly what you say. It's it's to look at where you stand and where you want to actually move forward when it comes to, you know, integrating better management practices, right from, you know, the top down. That thing that's very important to have the support of support of top management. It's really a top down approach. We do work a lot with, governments and tier 1 companies in that regards that get behind us to support reforestation projects, all around the world. So it's not just reforestation project of just planting trees for the sake of, generating carbon credits. That happens.

Aymeric Maudous [00:22:52]:
But we have projects as well that, sustain endangered species. We do work at the moment. We have a a mission happening in Borneo, as we speak, to work with, not a great organization called OOF, the Orangutan Republic Foundation of Borneo. We do work in Vanuatu and on a project that is, mapping helping the government to map and protect their mangroves. And we have, as a result of that, we're about to generate biodiversity credits, that specifically focus on turtles. Just to give you an example, another project in Mexico coming up to do with, 300 species of bats that migrate from the South of Mexico all the way to South of America. So it's, it's varied and there are avenues or ways to, you know, basically compensate. And and you you don't need to have you don't necessarily need to have 1, 000, 000 in the bank account to make that happen.

Aymeric Maudous [00:23:58]:
It all starts with, you know, small steps to add I think the fur very first step is the awareness of what you just brought. And the second step is is is a commitment, to, yeah, to create positive change whether, you know, you back those projects or you decide to use green energy or or be behind other project. We're not the silver bullet of environmental, issues. There is hundreds of of companies that are doing great work around us that we work with, from, you know, small farmers in South America to bigger corporations in other parts of the world. But I think it's the collective, you know, the the collective of those little actions and everyone is doing their their their bit, to,

Jordan Wilson [00:24:52]:
yeah. Yeah. And I think maybe another example, you know, going back to 2 points that you talked about earlier is, well, when you use generative AI, even if it's heavy use, even if you're, you know, gobbling through millions of data points, ultimately you are probably saving time in other places, or you're probably saving, compute or just human hours. Right? So going back to your original point, you know, using the drones and AI and robots, it's it's 13 times faster, right, than you would with humans. And there's obviously environmental costs of of humans walking around and, you know, the energy that they need. Right? I'm sure you could go on and on. But, you know, 1 other thing that you talked about, that I I wanna dive into a little bit deeper is this concept of digital twins. So, we've talked about it here on the Everyday AI Show before.

Jordan Wilson [00:25:39]:
You know, I was lucky enough to be out at the, NVIDIA GTC conference this year, talking with a lot of the individuals who are building, you know, the future of digital twins. But maybe, Aymeric, just give us a quick, you know, overview of what the heck is a digital twin, and, you know, maybe give us a concrete quick example of how you're using, digital twin scenarios.

Aymeric Maudous [00:26:00]:
Yeah. So the first 1 I've already covered in, when I was talking about our operations when we do landscape analysis. So, basically, to put it in very simple lay placement terms, digital twin is the representation of the landscape onto your computer in a 3 d thing that you can rotate and look at and turn around a little bit like, Think of Google Map. Right? That would be the best of Google Earth. That would be the best example, of a digital twin that we have of the particular landscape. When it comes to tech, we use digital twins as well for our tech. And I'm gonna be I'm gonna give you another example here where we are building, new drones, in part we have a joint venture with the University of Queensland to build a new drone for them by the end of this year. And, we've built the drone, that came up.

Aymeric Maudous [00:26:57]:
So it's a prototype at this stage. It it it flies really well, and it does all kinds of really cool things. But what we've decided to do, because we need to fly this drone in different weather conditions, instead of us waiting for those weather conditions to happen and then take the drone out, take it in, take it out again, and and and verify and do all kinds of testing, which would take us literally a year. Right? Because we want to test that drone in extreme conditions as well. So when we are hit, for example, with a cyclone, when the weather gets a bit insane out there, and compare that with when we have actually better, weather conditions, We have put we have put the CAD plan into, a a specific software that our engineers are working with. And the software has been able to look at different scenarios of pressure and wind condition that mainly impacting our industry, you know, the flying of the drones. And based on the results, we are we which happen in minutes. We've been able to modify the building plan of that particular.

Aymeric Maudous [00:28:16]:
Job. It would have taken us, as you said, a year to actually comes to those conclusion and do a lot of, you know, trials. But within a few hours and and, yeah, it was just incredible to see what would happen when it comes to velocity, pressure, thrust, etcetera, of of of that drone, just on a computer. So that's when, using AI for good, really speeds up the operation, reduces cost, and and enables us then to be back outside on the ground or in the air, as soon as possible so that we can, you know, we can plant more trees and and we can do more, more things.

Jordan Wilson [00:28:58]:
Yeah. And and, Aymeric, we've talked about a lot in today's conversation. This is gonna be a jam packed newsletter, by the way. But, you know, as we, you know, wind down, for this episode, I mean, we've talked about a lot, you know, AI is increasing, energy consumption and the environmental impact, offsetting, you know, how companies maybe should be offsetting their AI carbon footprint using digital twins. Right? Like, you just talked about using digital twins for landscape analysis and energy saving, but maybe what's the 1 most important takeaway that you want other business leaders, to to glean from this conversation on maybe creating a greener side of AI?

Aymeric Maudous [00:29:39]:
Look. I don't I I don't necessarily think it's the greenest side of AI. I think that should come naturally. Like, I think we'll get there. I mean, you're right. The AI is growing. I I don't think growing is the right time. I think it's exponentially growing.

Aymeric Maudous [00:29:55]:
Like, when I look at, you know, what the algorithms now spit out compared to just even, like, a months ago, I'm absolutely baffled, in in a good way. But, I as I said earlier, if there's just 1 takeaway, I I would like your audience to, to stay with this. It's just 1 step at a time. It says take the first step. It doesn't have to be daunting. There are people out there that are doing the right still doing great things. We're more than happy to help and talk to, to people if they have any questions. So how could that happen? But, yeah, just 1 step at a time.

Jordan Wilson [00:30:34]:
Alright. Hey. Well, Aymeric, thank you so much for your time and joining the Everyday AI Show. We really appreciate step

Aymeric Maudous [00:30:43]:
at a time, the next step that you need to take

Jordan Wilson [00:30:50]:
is going to our website, your everydayai.com. Sign up for that free daily newsletter. We will be recapping everything that Aymeric talked about and a lot more. So if this sparked your curiosity and maybe you want to do, better understand of you know, better understand different ways that you could be using AI or, you know, some of these projects that, Aymeric talked about, it will be in the newsletter. So thank you for tuning in. Thank you for your time, and thank you for joining us. Please, we'll see you tomorrow and every day for more everyday AI. Thanks, y'all.

Aymeric Maudous [00:31:22]:
Thanks, everyone.

AI [00:31:24]:
And that's a wrap for today's edition of everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit your everydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers, and we'll see you next time.

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