Embedded - 501: Inside the Armpit of a Giraffe

Episode Date: May 15, 2025

We spoke with ecologist Dr. Meredith Palmer and embedded engineer Akiba about lions, terror, and technology.  Akiba works for FreakLabs.org on global conservation projects. We talked about their Boombox which Meredith uses to create experiments to map the landscape of fear in predator/prey relationships. While this may look like pranking animals with jump scares, well, there is real science being done.  What would it look like to be smooched by a lioness? (Video) Bird hears lion, decides to go over there (Video) Checking the reflexes of some zebras and other critters (Video) These are lots of fun to watch and you can find the freshest ones and help out science by categorizing some at Snapshot Safari. Or skip to using the data on Lila.science (Snapshot Safari 2024 data). Check out Meredith’s website for more github and Data Dryad links to data and science.  If you want to get involved, Wildlabs.net has discussions around conservation technology. There is also a Slack group by Sara Beery focusing on AI for conservation. Elecia mentioned David Quammen, an author who writes a lot about biology and ecology. And now, a guy gives birth to a botfly.  Transcript If you’re interested in the intersection of neuroscience and engineering, you might want to check out what Mouser Electronics is doing with Brain-Computer Interfaces. It’s all about how you can control machines with your mind, and it’s one of the coolest areas of innovation right now. Mouser’s Empowering Innovation Together site has great content on BCIs, from videos to in-depth articles and podcasts that break down the tech. If this piques your curiosity, head over to Mouser.com/empowering-innovation and explore what’s happening with BCI and other exciting developments in the world of design and engineering.

Welcome to Embedded. I am Alicia White alongside Christopher White. Our guest this week are animals. Wait, no, our topic this week is animals. Our guests are Meredith Palmer and Akiba. Hi, thank you both for being on the show. Not that we're not animals. I guess technically, yeah. Everyone's an animal.

Everyone's an animal. It's fine. Meredith, Dr. Meredith Palmer, could you tell us about yourself as if we, I don't know, met at the Monterey Bay Aquarium Research Institute in a random talk you gave. Oh my goodness. If only I did things that cool. Yeah, so my name is Dr. Meredith Palmer. Meredith Palmer, just like the character from The Office, I am a wildlife ecologist with over a decade of experience in the field and advancing technological solutions to overcome conservation challenges. And so I started out, again, over a decade ago at this point, doing ecology and conservation

of lions in East Africa. And I've since supported carnivore conservation and rewilding programs across Africa and around the world. And so I am currently a conservation scientist at Yale University where I lead and support projects integrating in situ sensor networks, so camera traps, acoustic sensors, eDNA, all of those great tools with AI driven data processing, again, to kind of drive impact in the conservation space and in global policy. And essentially, I'm interested in using emerging technologies

both to gather, like, quote unquote, big data that enables us to better understand biodiversity at scale, while also working with new types of sensors to develop data-driven strategies for protecting and restoring ecological systems. Akiba, what is it that you do? Yeah, so I guess my background is, actually I was originally a professional hip hop

and break dancer. That didn't work out for me. I went back to school and ended up as an FPGA and ASIC designer way back when. Since then, got into firmware and system-level hardware design. And I also discovered that I had a passion for wireless sensor networks and designing technology for harsh resource-constrained outdoor environments. So that kind of took me into developing technology for international development. And then, and now, like for the past 10 years, developing technology for conservation.

Honestly, the best origin story of anyone working in the field. I don't think I know anyone coming from the hip hop scene. And it like gives me a lot of straight cred to say I know someone who did. Yeah, I really just want to say how did that happen but we probably shouldn't spend the whole show about that so. I think you should ask Meredith about roller derby. Guys, that would definitely be, we'd be on the phone for forever. Okay, we're going to do lightning round and we're going to try to make this fast because we ended up with listener questions as well as our own, as well as all of the historic ones the listeners know we're going to ask. So let me get the first one out of the way.

Have you ever pet a penguin? Oh, I've seen plenty of penguins in the wild. I do a lot of work in Southern Africa and we do get African penguins. They're called jackass penguins. I don't know if you have to bleep that out or not. But it's because the sound they make sounds like a donkey, not because they're horrible penguins.

But I don't think I've pet one. Yeah, we like, we're part of the US Arctic Research, I guess, organization. Shut up, are you? And then, yay, Arcus. We missed out on the community call last night. It's like 2 a.m. Australia time. Amazing. Yeah, so we have a project for polar bear tracking, but we haven't actually interfaced with penguins, so unfortunately.

And even the animals that we work with, we never get a chance to pet them. That's a shame. Not even the polar bears? I don't really think you should do that. Well, there was a... So, one lady from a zoo offered to, like, was interested in being involved in the project and she offered to train the polar bear to present its ear to Jacinta to mount the tracking tag. And we're like, oh, that'd be awesome.

But yeah, we never had a chance to. Like, ethically, I think we're not supposed to touch animals in the wild. Okay. So theoretically, have you ever pet a lion? I mean, you're just asking to lose limbs at that point. Seriously? You haven't cranked one and then like check to see how soft it is? That's not very ethical.

My grad school advisor did once milk lions at one point. That's one of my fun kind of cocktail party facts. That's what I heard. Okay. Yeah, like a cow, except it's a lion. I've never done that myself. That's how they get the tiger's milk bars. Remember those?

Yeah, no, I think the problem with working with the technology and all of this like, in situ sensors is like the entire point is to do everything non-invasively. And unfortunately, I've built my whole career around being as non-invasive as possible. So no, I've been chased by lions. I've been, I don't know, there's been, there's always been incidents, but I don't think I've actually ever pet a lion personally. All right, favorite fishnall robot. Akiba, you can start on this one.

I've got to have a think. I would say Kit from Knight Rider. I mean, it's not a conventional robot, but yeah. I think it was the prototype for all the autonomous vehicles that are kind of coming out now. My first thought went to RoboCop just because Peter Weller has such beautiful lips, but I know he's not a real robot. So maybe those two legged robots in RoboCop that take Peter Weller down.

He was mostly robot by the end of that. Was he? Oh, but he had those beautiful lips. Anyhow, yeah, sorry, off topic. Technically, I guess he'd be a cyborg. Yeah, yeah. Well, we'll allow that though. Do giraffes make sense? Can I take this one? Yeah. I have nothing to say about giraffes.

I have so much to say. Okay. My brief moment of fame, like the only time I have nothing to say about giraffes. I have so much to say. My brief moment of fame, the only time I have ever been on the international stage in terms of like POP Sci has been my work with giraffes where we used camera traps. So the core device that's part of the boombox that we're going to talk about, we have like a gazillion of them set up across Eastern and Southern Africa. And we discovered in this camera trap footage, so like researchers don't go out into the We have like a gazillion of them set up across Eastern and Southern Africa and we discovered in this camera trap footage so like researchers don't go out into the middle of the Serengeti at night, right? Because there's like hippos and things that are They're gonna eat you essentially, you know, it's so dangerous. No one does that. No one knows our herbivores

No, they eat you they're the most dangerous thing You yeah after mosquitoes. The last thing you want to mess with is a hippo. Anyhow, at night, full of hippos, very dangerous. No idea what happens in the savanna at night. But we set up these camera traps, which are these cameras. You set them up like on trees and things. They run 24-7, taking photos of wildlife. And so we get that like full 24-7 picture of what's happening in the African savanna.

We discovered that there is a species of bird that instead of roosting on trees, like normal birds like regular birds do, this species of bird has decided that the best place to sleep at night is inside the armpit of a giraffe. And we have all of these photos of birds roosting in the armpits and in the groin pits. I don't know how to say this politely, but like right up in there. And that like made National Geographic, that made like everything. And that is like, I am a very serious researcher. I work at Yale. I worked at Princeton. And like my moment of fame was an article I published on birds that spend the night nestled up next to giraffe bits.

So yeah, no, giraffes, they don't make sense and the things that sleep in their armpits also don't make sense. So did the camera trap record pictures of birds flying out of the butthole or just like... They weren't that up close and personal. I do know a surprising amount about things that do live in buttholes. So hippos, there is a kind of leech that has evolved to live inside the hippo butthole. I could talk forever on this if you ever want to do a side chat about things that live in buttholes. This is the ecologist for you.

These birds did not live inside the butthole, but they were pretty close. So I'm enjoying this conversation very much, but this will be the last episode of this show of all time. There's a lot you're going to have to bleep out here. I'm so sorry. What is your audience, PG? I'll make up a determination while I edit. Okay.

Christopher has declared the end of lightning round even though I still have questions here. I'm just worried where they're going to go. Go ahead. One more. Do you have a tip everyone should know? That sounds innocuous enough. I know, but I'm really, leeches and buttholes have already come up, so I'm pretty sure we're going to go off the rails.

Akiba, why don't you start? I would say a USB rechargeable electric screwdriver is probably one of the best pieces of field kit you could have. Is this a Doctor Who reference? Are you telling us to have a sonic screwdriver with us at all times? No, I think it's something that like we just use it all the time. And there's these cheap Chinese ones that you can recharge via USB and that's great because you can just use your phone charger to recharge your screwdriver when you're in

the field, especially if it goes down. And you can fit drill bits onto it and other things too. So we use it all the time. You never gave me this hot tip when I was working in the field. I feel a little bit cheated here. It's like, it's a trade secret. working in the field. I feel a little bit cheated here. It's like, it's a trade secret. I feel honored.

Meredith, a tip everyone should know. Oh, goodness. I'm gonna go real classic and say, back your data up in three places. There've been so many times where we've had data that's been like eaten by hyenas or stolen out of our luggage on international flights. Like anything that could happen does happen to your data. And so like my religion is backing data up in three places.

On that note, I would also say that one of the boombox devices that Meredith had deployed got eaten, got actually eaten by a hyena and then it was recorded on camera too. So it was really fascinating. Oh, we have the final moments. It's so good. Like the final output moments or just the final input moments? What? You have the hyena's jaws closing in over the camera. Like you've got teeth, you've got tongue, you've got like... But not an endoscopy.

We're not going down the digestive tract now. There is no butthole involved in this story. It's not a diagnosing camera. It's not, they're not checking it for colon cancer. Like this interview is gonna be like the, like beep hole, beep hole. But also I can send over a link. I think I have it.

I have the video on YouTube somewhere. All right. We'll put that in the show notes. And now a word from our sponsor, Mouser Electronics. If you're interested in the intersection of neuroscience and engineering, you might want to check out what Mauser Electronics is doing with brain-computer interfaces. It's all about how you can control machines with your mind, and it's one of the coolest areas of innovation right now. Mauser's Empowering Innovation Together site has great content on brain-controlled

interfaces, from videos to in-depth articles and podcasts that break down the tech. If this piques your curiosity, head over to mouser.com slash empowering innovation and explore what's happening with BCI and other exciting developments in the world of design and engineering. -♪ MUSIC PLAYING.

You mentioned Boombox, which I know what that is. We're all flightening around, right? We're in the show. Right, because Boombox is one of the things we were going to talk about. All right. I assume this is not the thing you hold over your head when you're trying to make up with somebody after... In the 80s?

In the 80s in a movie? I feel like Akiba's hip-hop background really comes into play in the naming of this device. I guess, well, boombox like, so boombox is a device that connects to a camera trap and so when the, so a camera trap basically records and And so a camera trap basically records, like when it detects an animal using a PIR motion sensor, then it will start recording. And so Boombox will actually pick up on the trigger signal to start recording and then wait a few seconds and play a sound.

And then you can actually monitor the animal's behavioral response to the sound. Actually, I mean, Meredith is famous for this, so I don't even know why I'm explaining this part of things. Because you're the genius behind Boombox. I mean, I can talk a little bit about the origin of why we would want a device that does this in the first place. I mean, that totally makes sense. Every time I see a bird, I open the Merlin Bird app and I totally want to replay the song even though I know you're not supposed to do that. Don't do that. Don't do that.

Ecologist. It confuses the birds. I understand, but I want to and you get to. Yeah. I mean, I think the origin story here, so again, as we were kind of talking about before, so as conservationists and ecologists, which again, I am a conservationist, my introduction to electronics came solely through this project. I'm not a technically minded person. I'm not a technically minded person. Conservationists and ecologists, we're a field that doesn't have a lot of industry,

there's not a lot of scaling, there's not a lot of finances for ecology. We're not out there developing our own things. We're out there kind of like stealing tools from other fields and kind of adapting them to our own needs. And so we have things like drones, which we took from the military, and environmental EDNA, which we took from forensics and even GPS tracking devices, that all came out of navigation tools for aviation and navigation for ships. So we're very, very good at taking other tools and trying to make them work for us, but we don't really have a lot of capacity as ecologists to create data collecting

devices that do exactly what we want them to do. And so that was a problem I was running into with my research that I did during my PhD and my first couple of post-docs. And as I mentioned at the top of the show, my background, I have studied African lions, I'm into large African carnivores. I'm quite interested in understanding carnivores from a prey's point of view. So I'm interested in putting myself in the mind of a zebra or a wildebeest and trying to understand what those prey animals do to avoid becoming something's lunch. Understanding all of those tactics, those behavioral tactics that wildebeest and zebra do

to avoid getting eaten is really important in conservation contexts where we're interested, for example, for restoring an ecosystem if we have this park or reserve that we're trying to kind of rebuild from the ground up and we want to reintroduce predators, we want to make sure that the prey animals in there, that these herbivores, that they know what to do, that when you throw a lion in there, that they're not just going to stand there and let themselves get chowed down on. So all of my research is on understanding how are prey supposed to respond to predators, that they're not just going to stand there and let themselves get chowed down on. So

all of my research is on understanding how are prey supposed to respond to predators so that we can try and reinstill those responses into these naive prey populations when we're chucking a whole bunch of lions into a reserve that hasn't had lions in decades. Why do the prey populations get naive? Is it because their matriarchs and stuff are killed off? So, there's a lot of reserves in Africa. Well, so predators are problems for people. They eat our wildlife, they sometimes kill humans, like people and large carnivores typically don't get along very well. And that's historically

been quite a big problem in Africa where we do have half a dozen of these really large carnivores. It's not just lions, it's leopards, cheetah, hyena, wild dogs. I don't know, there's like gazillions of them. And so- I just want to interject really quickly here because in the predator-prey behavioral ecology community, there's this wonderful term called the landscape of fear. I just thought everyone should know that. This is what my whole research has been on is landscape of fear, which again is like

the best buzzword of all time. But yeah, so you have this landscape of fear, which is this idea that in a savanna, for example, there's different places in that savanna based on how your predators hunt that are very, very dangerous for you to be as a wildebeest. So lions, for example, they're not very fast, they're not very sprightly, they're not going to do a long distance marathon, they're more of an ambush and a sprint, you know, they're short bursts of energy. So they're very good at sneaking up at you from behind rocks, behind trees, at water holes. So those parts of the landscape, rocks, trees, and water holes, very dangerous for you as a wildebeest. Those are

the hot spots in our landscape of fear. Whereas other parts of the landscape, the big open savannas, no trees, you can see for miles, a lot safer. And so that kind of heterogeneity, spatial heterogeneity in predation risk is what's called the landscape of fear. Is that also Akiba's latest album name? It would be a great one. I'm sorry, Meredith. I am taking this seriously. Landscape of Fear. Go ahead. Oh, no. I literally called my PhD thesis, going back to the sonic screwdriver thing, I called my thesis, I think it was like, oh, what was it? It was something about the spatiotemporal distribution of fear in time and space. And I tried so hard to make

the acronym TARDIS that it was like almost painful at the end. So in intact ecosystems, you have this landscape of fear, but people don't like predators. They're the first things that get hunted out or extirpated in these landscapes in Africa and around the world. You quite often have these landscapes where 50, 100 years ago, all of the lions were shot, all of the leopards were killed, all the hyenas were run off because they were killing cattle, harming people, harming livelihoods. Then for 50, 100 years, for multiple generations of wildebeest or impala, these prey animals grow up

without any kind of lived experience of being eaten by anything, of being afraid of anything, of having to make decisions between having a drink at the waterhole and potentially being eaten by a lion. And so in these intact ecosystems where prey do live with predators and coexist with predators, they have all of these behavioral tactics that they use to trade off that risk versus resources, how they navigate that landscape to avoid predators, but also what they do when they encounter a predator. Because again, in Africa, it's not just a lion.

It's a lion's lepers, hyenas, wild dogs, the whole litany of predators. These predators hunt in different ways. These predators have different superpowers for catching you. So different responses to those predators, like running away is going to be effective for a lion because again, they're not really fast. They're kind of slow and sluggish. You're not going to run away from a wild dog. You're not going to outrun a wild dog. Those guys are sprinters. There's like when you see a wild dog, what you need to do is a completely different behavior hypothetically than what you would do if you faced a lion

or a cheetah or a leopard. What is the strategy, just in case I need to know? Well that's exactly it. So this is like what I'm saying right in here is the theory. Like the theory is predators hunt in different ways, they're successful in different ways, prey should respond in different ways. Like they must do because we still have predators and prey coexisting. The prey haven't been hunted out, so they

might. They must do something different, but we've never been able to study that before. And this goes back to the idea that we don't, as ecologists, have tools that collect necessarily the data we need to answer these questions. So the question we're trying to answer is we have this community that has half a dozen carnivores, and we have like a gazillion herbivores. We have 40 different species of large herbivores in the savanna. I was interested in maybe half a dozen of those. But if you think about doing robust research, we need a big sample size, right? We need a lot of replicates of interactions between each predator and

each prey to be able to say that we figured out what survival strategy prey use versus impala versus lion. That factorial is enormous. That's huge. And I have been driving myself around in the Serengeti and Orlando for a decade, and I have seen maybe five hunts ever. Really? Ever. And so the idea, like how are you supposed to create or simulate hundreds of interactions between all of these predators and all of these prey, you could spend lifetimes in the savanna waiting to watch these happen for real. And that's simply like, it's impossible.

So we have never been able to answer this question before because the amount of data we would need to observe actual interactions between predator and prey is ridiculous. So we needed an experimental approach, we needed a remote approach, we needed an in situ approach to do this that we just never had the capacity to do before. And this is where Akiba and the Boombox came in, this is where Akiba created for me the perfect device tailored for all of my ecology needs to do exactly this experiment, but at scale. And that's what the Boombox is. This is what the Boombox unlocks is our capacity to ask these questions in ecology that are

just you cannot ask them doing ecology the traditional way. Nicole Forrest It's funny, we see National Geographic and David Attenborough going out, and every time we see them, they're, you know, in the middle of a hunt, or we're seeing camera captures of amazing lions doing lion things. And you don't realize that this is this we're only seeing the special stuff. We're not seeing day to day. I've worked with plenty of film crews and like the amount of time they spend in the field to get that one moment is like, oh, it must be so mind numbingly boring. Also, happy 99th birthday, David Attenborough, yesterday. Yes. Still going strong, speaking of.

And the different responses between the different types of prey, like a wilder beast, which is a big, strong animal versus like a deek-deek, which is like a tiny deer, those, like, one fear. One of those would try to kick an animal and one of them would run away in all cases. Is the landscape of fear very different for different prey animals? It is. And it depends on a lot of different traits, both of the predator and the prey. Again, this is like the theory that we're testing with the boombox. But hypothetically, again, you have these predators that hunt in different ways. We typically separate them broadly into categories of coursing predators. So those are the ones like your wild dogs or hyenas. They're the long distance runners. What they do is they just chase you until you fall over exhausted

versus your ambush predators like lions that again just find a rock and they jump out at you and like eat you. So there's predator traits that play a role in this. And then there's prey traits. And so we have everything from body size, sociality. So if you're a herd of buffalo and there's 2000 of you, that's a great defense against lions. There's the morphology. So some of these animals have horns, they have hooves. Zebras can kick like no one's business. Then there's like, can you run away quickly? Can you vocalize? Can you make an alarm call?

There's questions about sensory modalities. We talked about giraffes. Giraffes have great vision. They're very high up. They can see very far away. Other animals rely a lot more on smell or on sound to detect predators. Again, it's this factorial combination of there's all of these different traits and ways of attacking prey and escaping from predators and sensing predators that all make this question

really complicated Which adds to the amount of data we need to collect in order to start addressing Like teasing this apart in a really scientifically rigorous way Okay, so you have the boomboxes how's it working? Yeah, so the the idea behind the boombox like Akiba just said is we have Ecologists rely a lot on a device called the camera trap, which is a camera, it's rugged, it's waterproof, you set it up in the wild, you attach it to a tree, it has a PIR sensor, so when something warm moves in front of the camera, it triggers the heat and motion, triggers the sensor to snap a photograph or take a video. And Akiba, I realize this is a gross generalization of how this works, so please jump in with

the technical details. But in layman's terms, that's how camera traps work. And I've used camera traps for decades and they collect really great data on where animals are and what they're doing and who they're associating with. But the problem is, is again, these predator-prey encounters are just so rare to encounter in the wild and so rare to capture that even with a hundred camera traps set up in the Serengeti, you're still not capturing enough of these predator-prey interactions to understand

what prey are doing. And so where the boombox comes in, and what's really clever with the boombox is the boombox is not observational, it's an experiment. And experiments are really powerful in ecology and science. So the boombox device is this, I'm, Akiva's going to be rolling in his grave all the way over there. Australia is not dead yet. He will be when I finish describing the boombox the way I understand it. The boombox is this modular attachment.

We essentially hack into the circuit board of the camera trap. Like Akiba said, the boombox device attaches to the PIR sensor. When the PIR sensor is triggered by an animal and it triggers the camera trap to, in this case, take a video, it also triggers the boombox device to play an audio recording. And these audio recordings could be anything. It could be disco. It could be hip hop. In our case, we programmed it with predator calls. And so I had all of these predator calls, calls from lions, calls from hyenas, calls from cheetahs, calls from wild dogs. Hippos? Hippo hop?

Hippo hop would be the great band's name. I would buy tickets to see that. I did not expect that one. That was great. The hip-hop eponymous, right? Classic flight of the concords. But yeah, so the boombox device, what it does is the experiment is when an animal walks in front of the camera, the boombox device roars like a lion or it twitters like a wild dog or it growls like a leopard. And then it records, the camera trap records the prey animal's response to that quote unquote predator.

So that's simulating for us that encounter between a predator and a prey animal. And if you deploy two or three dozen boom boxes and leave them going for multiple months, you're capturing, oh God, I should know this number because it like melted my brain. I believe it's a crapload. Exactly. A butt ton of recordings. I stopped hearing from Meredith for like a year and I think that was when she was processing all the videos. Oh my goodness. It melts your... Processing videos is the absolute worst. It's the...

You do get some gems and I would love a key, but to share some of these with you, we do have some really funny... like as a scientist, I shouldn't find it hysterical how scared animals respond to predators. So if my advisor is listening, please tune off now. But like, it is really funny. It's like you're pranking the animals. I know it is. It's like candid camera for animals. It is robust scientific work that is producing great papers, great inference, but it is also really funny watching some of these animals respond to predators because we just never see this. We just don't know

how this works. There's decades of anecdotal evidence. we kind of understand how this works, but like we finally got the thousands of videos, you know, the thousands of recordings, robust, verifiable video recordings that we can sit down and we can watch and we can rewatch and we can extract all of that data we need to be able to start answering these questions in a really rigorous way. I think it was really interesting because like the device was spec'd by a guy named Justin Srirachi and I think he wrote a paper on it and then Meredith had posted somewhere that she was looking for someone to help her

develop a device like this and so I think when Jacinta and I got involved, because we were working on an electronic board game that had audio sound effects that you could like via mp3 and so we're like, ah, I wonder if that would work. And then so we were discussing with Meredith and she spec'd out a lot of the like what she needed. We put together a prototype and like the weird thing was that this had to happen in like, was it like three or four weeks because you're about to go deploy

in Serengeti. So we're like, oh, I guess we have one shot to design. So no PCB respins or anything. Let's just cross our fingers. And I think it just- I was so desperate. It worked the first time, but you know, like later on we had to make a lot of modifications to like over the we had to make a lot of modifications.

Over the years we've made a lot of modifications, but luckily it worked that time to collect the data. How do you approach development as something like that? Because if it's me and I'm given a deadline like that, it's like, oh, I'm going to go shop on SparkFun and I'm going to plug several boards together and hope for the best. But maybe that doesn't work for something that needs to be in the field and sitting in the sun and- Hot glue and epoxy.

Right. Well, okay. But yeah, so how did you approach this? It was like a, because we had already kind of designed the audio subsystem and that was probably the hardest part is the audio and the amplifier and then like and interestingly enough the like the hard part was the power supply because the audio like an amplifier requires quite a bit of power but a lot of that was already designed so it was kind of just modifying our electronic board game PCB into into and adding like kind of

inputs for like the camera trap trap trigger and things like that. So it was, I think, it was kind of serendipitous and also it was kind of like, ah, let's give this a shot. And I didn't expect it to actually, I expected Meredith to be the only one in the world that would be interested in something like this. So, but later on we found out that there's actually quite a few researchers that are interested in this kind of thing. So, um...

Oh, it's, it's blown up. And again, it's because like ecologists, we don't have anyone like you, Akiba. Like we don't, like we spend all of our time trying to make stuff that's not built for us, work for us. And I just think that the potential people saw in a device like the boombox to actually like do the things we need technology to do as ecologists. Like it opened a box for a lot of people. And like what you've got projects in New Zealand and Italy and North America and Africa, like

where don't you have boombox projects running now? Ah, yeah. I mean, like, well, I think there's a lot of, yeah, we, so since then, we've had a lot of projects and they've been adapted for a lot of things. And so, like, and now we're getting into more human-wildlife conflict and kind of non-lethal deterrence. So we have, now we're putting together... Talk about boombox Disco. Oh, well, there's Boombox Disco. Actually, we're doing a high-powered, large, amplified version of Boombox, which is called Blaster. Blaster? Yeah, so it's kind of like the ghetto blaster.

Ah, okay. Love it. And then, but yeah, we're doing like, there's like, Meredith had mentioned there's different modalities too. So we added extensions to do lights along with the sounds. There's a smell, so we used a nebulator. Oh, wow. Basically, I mean, they're just like ultrasonic piezoelectric actuators that will... The little fog machine things.

Yeah, ultrasonic humidifiers use them. Yeah. Like those cheap USB ultrasonic humidifiers. But you can actually nebulize different water-soluble things. And so the first thing that people always ask me is like, have you tried pee? Have you tried nebulizing the pee? And I'm like, oh no, I'm not going to do that in my lab. I have done a lot of work with pee. I did before the boombox. I spent a lot of time wandering around fields with buckets full of wolf urine. So don't diss the pee. It does the job.

Like ecologists are fine with that. They're fine with that. They're fine with sticking, like shoving their hand into like a giant mound of poop and then kind of. I've done that. Yeah. Well, yeah, you need to see what it ate. Yeah, I mean, totally.

And like, you know, so I think there's different, yeah, I guess, you know, it's quite interesting. It's fun hanging out with ecologists because they're like really into like, they're a quirky bunch of people. We're gross, that's what you're saying. Can I actually jump in really quickly and just pick up on something that you said there? As you mentioned that the devices that you were integrating into these boom boxes were cheap and I think that's something I really want to underscore the importance of cheap for ecologists as well.

Because not only do these devices have to be rugged, like they have to endure, like you were saying, Chris, like wind and rain and sun and dust and ants and like hyenas, hyenas, but also we're ecologists. Our budget every year is like a hundred bucks, maybe not a hundred bucks, but I've definitely had years where like I have $5,000 in my pocket and I have to save the tigers, right? And that's I think a problem with a lot of technology and also a problem with developing and scaling technology, right? Is that it's not a cheap process necessarily. And so the work that Akiba has done and other people in the conservation technology space,

not only to make these devices work, collect the data we want, work for us in the field, but also be accessible at a price point for both academics and researchers in developing economies and the global south, places where we have biodiversity, that is incredibly important as well. And something that I spend a lot of time when I interface with technologists kind of underscoring is again, we have such important work to do as conservationists, but our budget is, you know, monopoly money, essentially. We don't have a lot to work with. So these, you know, like low cost open source,

like Arduino, Raspberry Pi kinds of devices are game changing for us. I would also say like, because there is a huge problem in financing conservation and, you know, we're actually giving a talk next week in Thailand with the UNDP on biodiversity finance. And there's a lot of really interesting things happening in looking for novel ways to finance like biodiversity initiatives.

And I think so there's a lot of discussion at the moment about exactly what Meredith was talking about. Going back to the human predator interaction, human bio interaction, what I understood- Human wildlife conflict? Yes. So, we don't want people to kill off lions and other cool animals because they're really cool. But for us, it isn't a matter of them eating our house and home. It's a matter of going to visit them and seeing, oh, they're cool. But there are a lot of people who don't want lions nearby because they're dangerous. And so I saw on the freeclabs.org website that the boombox works with that as

well. Do you wait for a lion to come up and then you play a lion roar from somebody else and so the lion wanders off thinking this is covered territory? Or how does that work? How do you warn off predators so that they stay away from humans? Is that a goal? So I think it's kind of a Meredith question, but I can answer part of it, which is that like boombox, so we don't really advertise that it tackles deterrence directly because the thing is that, you know, deterrence is really, I feel like is highly dependent on the specific animal. So I think it's more, but I think you can look at what things could potentially scare off an animal. Like I think lions, they don't get really scared by much though. Meredith, I

think you have a much better idea on that though. Yeah. So that's not what I use the boot box for. Again, I'm interested in scaring prey more than I am in scaring predators, and human-wildlife conflict is a little outside the direct work I do. It's a consequence of the work I do, but not something I work on specifically. We do get predators in our boombox videos responding to other predators, and it's mostly with curiosity. So we do have some great videos of things like lions coming up and investigating the boomboxes because they're curious to see what's making these noises. Traditionally, when you do, so like one way of counting predators is to do a playback where you play the call of an unfamiliar lion or hyena and that actually brings out the lions or

hyenas to come investigate that call. So I don't think playing calls of predators is going to deter predators. I think maybe the lights and sounds of some of these like new boom boxes could be used as deterrents. I think Akiba, isn't Justin Cerati doing boom boxes in New Zealand to scare cats away from endemic birds? Like I do think there's some utility there, but it's not something I've worked with myself specifically. Yeah, so that was one of the projects we helped out on also. And it was basically to deter feral cats to prevent them from hunting endangered birds during the nesting, the breeding season. And it was really interesting because one of the things that are scariest to feral cats are people talking in normal voices.

We're terrifying. You should totally play this podcast for them. I mean, it would probably work. One of of the sounds were just like two women having a conversation, and it would be terrifying to the feral cats. It was just like, oh my God. So I think humans are probably one of the main animals that most other animals are scared of. Changing subjects. Meredith, you mentioned that your tip was to back up your data in three places and a

hyena's gut. But you on your website have a link to data dryad, which I had never seen. Could you tell us about it? Oh, yeah, no, of course. So going back to what we were talking about earlier about camera traps, before the boom box and during the boom box and since the boom box, a lot of the work that I have done has been in deploying these large-scale wildlife monitoring networks. And so I have helped set up and run sensor networks of hundreds, thousands, thousands, thousands of cameras across Eastern and Southern Africa and North America, so

all around the world. And we're setting up these networks. I'm interested again in predator-prey interactions and conservation. But the thing with these sensors with camera traps is that they're not just snapping pictures of wildebeest and lions, they're getting aardvarks and zaryllas and ground hornbills and giraffes and armpit birds. They're capturing these entire wildlife communities. It's more data than I could ever process or analyze or be interested in doing. I need lifetimes to answer all the questions that we could ask using all of this data we're collecting. And so my lab and myself personally, we're big advocates of desiloing data, of sharing

our data with other researchers. There's been a bit of a paradigm shift in the field of ecology in the last decade, where before when we didn't have these sensors and these technologies and these tools helping us collect, again, like quote unquote big data, to get the data we need to do our theses, to answer our questions, to write our papers. We are spending decades in the field, in a tent, away from our families, eating rice and beans three meals a day. You put your blood, sweat, and tears. Baboons will destroy your tent and shit on your pillow. That stuff happens. That data is valuable. You don't give that data up. You don't share that data with other researchers because you put your life into that.

But now we're getting all of this big data. Researchers are collecting a lot of data. We're collecting it a lot more easily. And we're realizing the potential to really use these data to address biodiversity questions at scale. And so now, again, there's this movement where researchers are sharing their data with other researchers. And so there's sites like DataDryad, like DarwinCore, like Wildlife Insights, like Lila.science is the big one we use, where we have put up, you know, hundreds of thousands of camera trap photos for anyone to use. And so we get other ecologists using those. We also get a lot of computer scientists using these data sets to develop computer vision models. I'd say those were one of our biggest audiences.

But yeah, so all of our data, our research information goes online. We love to collaborate, we love to share that data. We wanna see research coming out of this information. And yeah, we're really moving into this kind of like warm and fuzzy phase where collaboration is the name of the game in ecology. And we are here to work together to answer these big questions before it's too late. And if I wanted to just look at stuff, which one should I start with?

Oh, if you want to just look at stuff. If you don't want to just look at stuff, how about this? Let me sell you on this idea. You don't want to just look at photos. You want to help researchers analyze data, right? You want to go on your armchair safari, but also contribute to conservation science at the same time. Okay. Okay? Okay. I'll buy that. Yeah, I do. I mean, I do. Okay. So what we do, what we do. So one thing that we, again, thousands of camera traps collecting millions of photos

a year, right? How do I, as one researcher, look at a hundred million photos and write down what's in each photo, right? Interns. There are not enough interns in the world. But believe me, we rely a lot on interns. But it takes, I once calculated it that like for one single project, for example, that we run in the Serengeti, it's 200 camera traps. If I or an intern, they actually measure this in grad student hours. This is a unit of measurement that I find really sad and really funny. But if I was to sit down and extract the data I need, not doing analysis, not doing insights,

but just like this image contains a giraffe, from all of the images we collected at that one site, it would take me seven years to process a single year's worth of data. It's bananas. So now, we do rely a lot on AI to help us analyze what's in those photos. But there's some things that AI just can't do at the moment. Like camera trap photos aren't great. They're not like that snapshot you take at a wedding. It's not an animal perfectly framed with wonderful lighting.

It's like an animal two kilometers away behind a tree in the rain in the evening and you just see a tail. So there's some things where we really still do have to, you know, we use AI, but we still rely on the power of the human brain. And so what we do with those images is we crowdsource them, we put them online. And so anyone can go to our websites and look at all of our photos. And while you're looking at them, there's a little sidebar with some filters and some tools to help you kind of like understand what animals we have in these different sites. But you just

tell us, like you look at a photo, it's a beautiful zebra. You tell us it's one zebra, it's having a snack, it has a baby, you know, like there's some ecological information we want from that photo. You enter that information, we show you another photo. And that's such a good way we call that citizen or participatory science is the term we use now. But you can go and look at any of our photos, Snapshot Safari is the website that links to again, like dozens of camera trap projects we run around Africa. You can go look at all of our photos but while you're looking at them, help us out. Tell us what's in them. You know, it's real data we use in our research and it's, you know, the help of

members of the public, of volunteers who look at those photos is something that keeps the wheels of our research running in a really important way. It has direct on the ground conservation impact and we're so grateful for everyone who tunes in. Yeah, it helps us look at all of those photos because there's a butt ton of them. Are the camera traps devices that are kind of taking advantage of continuing to technology development and things getting less expensive? Or I feel like for some of these things, it's like, OK, here's the camera trap 2000 from literally 2000 and one company makes it and they're the only ones who make it. But is this something that is getting cheaper and easier or is it kind of a legacy technology that you have to buy from one place or something like that?

I would say that actually they're they're really cheap and like There it's like a commodity product from China. And you know, I think there's only like Truthfully from the research I've done I think there's only like maybe three or four factories that actually make all of the different variations of brands of camera traps. They're actually called trail cams and they're made for hunters. We stole them. Ecologists stole them. Ecologists' fever here is very high.

We're resourceful. I think, yeah, there's totally a huge amount of innovation within ecology. But yeah, the trail cams, I take them apart all the time. They basically use image processors from a single company. And the big thing, there's ways of, you can actually make your own camera trap as well, but the problem is that you run into this weird intersection where you need to have like very low power and then a very fast response time waking up from a deep sleep mode. And so like you can't get that with like, a lot of people try to do Raspberry Pi cameras and stuff, but you just can't get that because you have to boot up a Raspberry Pi.

For a little context on that is like the camera traps, we're not checking them every day, right? We're checking them every three months or every six months, which is where the power resourcefulness has to come in and the going in and out of sleep mode. Because the point of these sensors is to be remote and deployed in the field and be undisturbed. So we leave them in the field for months on end. And if the batteries die in the first five days, then we're screwed, right? So that kind of like low resource environment is really key. So somebody goes out in the middle of nowhere and drops a camera and then three months later comes back, swaps out the SD card, swaps out the battery and leaves it there?

Yeah. So it's not just, you know, like, so I get asked this question, like, I think there's a lot of things, again, that technologists think there's easy solutions to this and there's really not. I get asked a lot, why don't you just ping the photos over the GSM network or send them to a satellite? Why do you need to go check the cameras at all? Send the data over the 2G network that's available.

But that's, okay, A like, okay, like A, that's ridiculously expensive because each camera's picking up thousands of photos a day. Like B, the cameras that are enabled to do that are so expensive and we lose 10% of our cameras every year to things like hyenas, weather, poachers, like hippos. We can't afford those cameras. But also, vegetation will grow up in front of the camera.

We do have to physically visit the camera every couple of months to trim the grass so that the camera continues to have that really great field of view for taking photos. And so there's these trade-offs between we could use really fancy, expensive, high-tech stuff where we'd never have to visit the field, but actually we would have to visit the field and it would all get stolen anyway. I would also clarify that because a lot of researchers don't just take still images with these trail camps. And so one of the big... That's actually not a very difficult problem to solve to do still images. But what's really hard is to do video. And so like most of the camera traps do H.264.

And we're looking at trying to implement like H.265. But I think like the, like that's one of the big issues where you just use up a ton of bandwidth. And so video over communication networks like LoRa or cellular just doesn't exactly make sense. Or Saddle. Remember, our budget is like $200. So like an iridium subscription, we'd blow through that in two days.

Yeah. Okay. So I do have a question that's related to the cell modems. How do I get a live stream with the Lion point of view camera? You give me a grant for two million dollars and then I'll set that up for you. I think I remember the National Geographic has an explorer technology team which basically implements a lot of the kind of conservation technology for NatGeo. And they actually have set up action cams that go on animals, like you just strap it

to an animal and then it just kind of goes and takes pictures of everything that and takes video of everything the animal sees. Unfortunately, the larger problem is the battery life. So if you're just constantly recording, then it's not going to last very long. So whereas you can have like a streaming camera and so they do that. They have the great ones with the grizzlies and like especially for Fat Bear Week. Yeah, there's a lot of like webcams set up at water holes around Africa that you can tune into and take a look. They're not for research, they're for fun. Again, because like streaming that much data is just so exorbitantly expensive. And the questions that we're trying to ask, or the questions that I'm trying to ask, you don't necessarily need real-time data.

I think there are some conservation questions. There are acoustic devices, for example, that detect gunshots and send real-time alerts to anti-poaching units or detect chainsaws. I think there is a role. I think Panthera is a conservation organization that makes a device called the poacher cam, which has embedded AI when it detects a poacher. Like a person, it will transmit that image real time to HQ so they can deploy the men, I don't know, to go find that poacher. So there are some conservation tools that

are real time, but they're deployed very strategically in the field, again, because it is so resource intensive to do that. I trade off in my research kind of like the scale of data I collect. I collect a big data, a lot of data across big spatial and temporal scales. I don't need that data in real time, so I don't do live streaming. But that's not to say that there aren't devices for conservation specifically that don't do that and there is a very big role for that. It's a different use case in a different audience, but those devices do exist. I would also add that because there's a lot of discussion about like say AI on the edge

or you know AI on camera traps and things like that. I think from a practical practitioner standpoint though the problem is that like it's so energy intensive to use these AI models and there's like not a massive benefit because you take such a big hit to the battery life. So a massive benefit because you take such a big hit to the battery life. So it's actually, like the practice still is basically just use larger SD cards and collect more data and then go pick it up rather than using AI to select the specific animal and then stream that up to the internet or something. And as good as that is now, it seems like that would, you would miss stuff, right? You want all the data.

100%, I was just gonna say there's concerns about false negatives and false positives. And so like missing critical incidents because the AI doesn't recognize it. But also, again, speaking with my ecologist hat on, AI only recognizes things it's been trained to recognize at this point, right? And so my armpit birds wouldn't have been recognized by AI, right?

Because we would have never have known to train AI to look for birds hanging out in some things. Armpit. You know, so like that's also a big concern for us is like missing data and missing critical events with using AI. If it is something like a person like a poacher, AI is very good with like people and vehicles. I think those are tasks that are quite simple to use edge or embedded AI on for alerts. But for some of the natural history stuff, we just want all the data we can get.

And that that problem extends to your post-processing problem of seven years for one year of data because the same issues exist. You might miss stuff. Like you might say, okay, I want to filter all of this for a lion's, but it might not be good as you said, seeing a lion behind a tree or whatever. So that's why we use the humans in the loop, right? And things are developing there. There's new ML techniques that incorporate new things.

But we've just put out some really cool papers on large language models and large multimodal models and generative AI and exploring their applications in the field of ecology. So I think that there's a lot of exciting stuff with things like zero-shot learning that are going to revolutionize how we use AI to help process data like this. But at the moment, it really is this beautiful partnership between AI taking a pass and people taking a pass as well. Which seems like the appropriate way to do it. I would also say, I think what's really interesting is that within conservation and also ecology,

there's real and impactful applications of a lot of the bleeding edge technology that's coming out. I think it's just, there's a gap between people that understand and can implement the technology and the people that actually understand and can implement the technology and the people that actually really need and use it. And I think that that's and can use it. And so that's where I think it's kind of starting to close, but there's a lot of issues. There's like huge research, there's huge funding gaps. But I think the challenge, like what I really like is you get to work with like these really big messy problems and there's just like,

you know, and you can, and yeah, there's just so many of them. I could just throw a stone and find like eight different applications that need to be implemented or done. Oh, amen. And that's why we need people like you, Akiba, in this space. I think there's a lot of people like me in the technology space. Not people who are willing to listen to ecologists and again work with us in our tiny little budgets and with our difficult problems. And I find it so frustrating as an ecologist, I do a lot of work probably more so with AI computer engineers than I do with hardware people. But people will come in and they'll take

our messy data and they'll develop something amazing and new, like a new algorithm that solves all our problems. And they'll write the code up in TensorFlow and put it on GitHub and then they will like publish it and disappear. And I'm there in the Serengeti in the field with my Windows 95 PC and my Tanzanian field technician who's never gone to high school and we don't have internet and we don't have power and I'm looking at this code and it's like, well, I can't actually put this into practice. This amazing breakthrough in computer vision

is great for computer vision as a field, but the implementation gap, like Akiba was saying, is so frustrating because we need people who are willing to translate those achievements in these kind of more academic spaces and actually wrap them up into tools that we can deploy on the ground. That does not happen enough.

It is so frustrating. It's so hard as a conservationist to look at this amazing world of technology, and I can look at my phone and it recognizes my face. The technology that we need is there, but dragging it down into the field of conservation and making it accessible to practitioners, not enough is happening in that space. And we really do like, shout out to any engineers out there, you know,

like, please come help us because we need the support of people in your spaces to come and like hold our hands and make those tools work for us. Okay, so I'm going to ask a question that's been on the tip of my tongue and you've set it up beautifully. If people say a burned out engineer who's tired of working on boring things or something, boring BLE nonsense, light bulbs that connect to the internet, how does somebody get into working with conservationists or science in general in a kind of a collaborative way that might not be super well compensated but might be very fulfilling?

I wonder who you're talking about. How did I find you Akiba? I think there's a lot of different avenues into it. I think I'd recommend, yeah, it's a little bit difficult to say because I kind of fell into it. And there are sites like Wildlabs. So if you check that out, wildlabs.net or... Anyways, there are sites like Wildlabs that focus on conservation and conservation technology. But I mean, if you really wanted to get into it, I think it's like within different schools

or even finding something you're passionate about about like if you're interested in volcanoes, like hanging out in the volcanologist community and then seeing what's needed. Because I think there's so many, like volcanoes are actually quite fascinating, but there's so much technology that's needed in so many different areas. And like it's not that easy to, not that hard to get involved in the development. I think the larger problem is really the longevity, being able to stay involved. And especially because a lot of other industries don't have, say, the technology pay scales. The funding is much lower.

So that becomes tricky. Like the one thing I would say though, is that I think it's really interesting because I never really expected engineering to be, you know, as I guess, exciting as going into the field and like truthfully kind of risking my life in a lot of situations. Like in international development,, exciting as going into the field and truthfully kind of risking my life in a lot of situations. In international development, we'd be going into conflict zones in order to check out water infrastructure in order to automate water distribution. So I think it's like, but there's so many different problems like that.

And I think it's really about like, part of the journey is searching out what has meaning to you in order to apply your skills. And I think, and I feel like that's, I guess it's kind of general for a lot of things. But I do think that, I mean, there's different paths. I guess the way that I'd put it is there's different pathways in. I don't think there's a set pathway and it's kind of not a common route to follow. But there are a lot of scientists out there who need the technology transfer. And some of them have at least a little bit of grant money to pay for it. And a lot of them do have power needs that aren't being

met by people who are grad students because the grad students need to focus on their own things. So you said wildlabs.net, is that a place that people post for wild things? Yeah. They're actually quite a large community of people that are kind of somewhere in between conservation and technology. So there's a lot of technology people, a lot of conservation ecology people. I think like Meredith was saying, though, it's like the longevity.

And so when I was working at World Bank, there was a, or when I was working at World Bank, there was, or when I was working with World Bank, there was a concept called, I think, the parachute. I forgot what it was. But basically, it's like people that kind of parachute in, do something, take a lot of pictures about what they do, and then kind of, and then leave. So I think, and I think that happens a lot. So I think it'd be, but to have like meaningful

impact, I think it would probably take like three to five years of consistent effort at like, you know, at a project where then you'd start seeing real kind of impact and change. I once went to a conservation technology conference and I went to a talk for technologists that was literally like how to work with ecologists and the opening statement, like the opening premise was like ecologists are really annoying and kind of hard to work with, so this is what you need to know. They have no money. They do these field seasons. The prototypes never work. It takes years. Honestly, that was so helpful I think to see that laid out because like Akiba was saying, it's not like a quick fix. It's an iterative process like we discovered with the boombox. Yes, we whipped up, we,

Akima, and just ended up whipped up an amazing prototype in three months, but there's been subsequent years of refinement on that program. And so, you know, again, like- Was it three months? It felt like three weeks. Everything felt so rushed. Okay. Three months is a much more workable timeline. I felt every second of that three months. My PhD was writing on that. But yeah, so I would plug wild labs quite a bit. I think it's, you know, as an ecologist, where do I go to find engineering support? And when I was looking for support to develop, you know, the concept of the boombox, I went to my university, I went to our engineering department, I looked around our town at commercial

businesses and there wasn't anyone really who could help me do what I needed to do to do this innovation, this prototyping. So wildlabs.net was a place I went. I think I'd also like to plug Sarah Beery, who's a researcher at MIT, runs an AI for conservation Slack, which is another kind of community that brings together engineers and technologists and ecologists and conservationists into one place. But yeah, I think that those melting pots are far and few between. And so I think that conversations like the ones we're having now, like highlighting

the needs that these different communities have and what each community can bring together are so important for making people aware that this is a problem we'd like help solving and then directing people to those places. And so even going to universities, I think going to ecology departments and asking if you're a technologist, what are researchers working on? What do you need help doing? I think a big part of the problem we have as people who aren't necessarily in technology is we only think inside the box and we're not recognizing

the potential of emerging technologies. We don't really know what's possible. And so I think, you know, I'd love to see a world where technologists spend more time just going to ecology talks and just being like, there's so many conversations I've had with technologists where a problem that's taken me, you know, data I've collected over 10 years, someone's been like, oh yeah, if you just daisy-chained that with Bluetooth, you could have done that in five minutes. And it's like, oh, I didn't even know that was a technology that existed. Right? So I think like...

That would be Elisa and Chris, I think. You know, we need that because we, you know, we don't know what's possible. We need some help thinking outside the box. And I'd love to see more of those conversations happening. That would be fun. Okay, I have one more listener question from Sahil who requested the funniest field debug story. And there is a pun in there, but I wasn't sure whether it was field or bug. So Akiba,

do you have one? Is the question, sorry. No, no, go ahead. Oh, if the question is, have I ever had a camera trap full of ants? The answer is yes. I think like E. College, I remember Mary told us this weird story about a friend of hers that was cultivating a parasite inside of him or something like that also. And I think those are like-

Oh, isn't this the fly that all ecologists have to have? Oh, yes. I've had a bot fly too. Okay, well, it's been a good show. I already knew. You don't want to talk about buttholes for five more minutes. Well, botflies aren't, those are just things that you host because you're a weird ecologist who decides that sure, lay your eggs in me. What?

Nothing can go wrong with that plan. It's like a child. But no, I think the friend to keep is talking about, he films the entire process. It's on YouTube. His name is Peter Nisarecki. It's a beautiful, heartwarming video about his botfly child, and I cannot recommend it enough. Ten stars. Please go see.

That's a literal debugging, I suppose. Like, I guess one of the field stories, I guess there's so many, but one of the field stories is because on our deployments here, like I'm in Melbourne right now, and we have deployments in the Australian bush. And so our wireless sensor nodes that we put up, what happens is there's this gap in the back of them that's a really great habitat for the Australian redback

spider, which is one of the most poisonous spiders in Australia. Everything there is venomous. Yeah. Even the cockatoos try and throw plant pots at you from the roof or something. So it's a... And the drop bears. Huh.

I mean, it's, I guess that would be my... It's not funny though. It's just more like when we, every time, like almost every device that we kind of decommission and pull off off we have to check the back because there's always these redback spiders on them and so before we do it bare-handed now we have to wear gloves have you considered covering that hole just a thought no it's a it's a it's a kind of like a gap there's like the mounting pole and there's like the small gap that um yeah I mean I guess

you know a concave thing right so it's not that it's all yeah yeah yeah so it's like uh it is open to both ends and I guess like they nest there and like other animals come in and they just eat them I guess because the cameras are warm probably so all right I should have I should have really emphasized the field instead of the bug part of that. I think now we can... Meredith, do you have any thoughts you'd like to leave us with? I mean, if you don't want to talk about bugs, I kind of don't have anything. Go ahead. Bugs, buttholes, whatever you want. No, going back to the field debugging, I do think like some of my, the wonderful world of electronics that Akiba introduced me to had me lugging suitcases full of soldering

irons and wires and bits and pieces like into the depths of Mozambique. And you know, you're sitting there in your tiny tent, forgetting of course that the power voltages are different in different countries, blowing out multiple soldering irons, trying to hook them up, desperately trying to rewire a camera trap that fell apart in the bush plane in transit to the field because you didn't solder it right the first time. There's definitely been a lot of those fun moments, which is like such a beautiful marriage for the traditional field ecology that I do, which is tents and dirts and bugs and what have you with this like, you know, kind of more like lab technical

sterile like cracking open a camera trap and there's a shiny circuit board and I'm trying to solder things together. And it's really interesting like juxtaposing one into the other. And I've had a lot of fun with that. Not a lot of success per se, doing field repairs, but a lot of fun. So like, yeah, I think my closing thought then is just like a massive thanks to Akiba for the work he's done both on my project and it's clearly as you've heard been kind of a game changer for a lot of different ecologists and conservationists around the world. And yeah, just like very excited to kind of see over the lifetime, the course of my research, the tides turn in terms of, you know, creating these sensors and devices and experimentation units that allow us to explain

the unexplainable. You know, I think that's, that's, we've never been able to answer these questions before. And that's so cool. Like, I don't have a more profound thing to say other than that. It's like really cool that we can do this now. Yes. And yeah, it's so exciting to me as an ecologist to see this happening.

Akiba, do you have any thoughts you'd like to leave us with? I think it's really interesting hearing Chris talk about like a burned out engineer. And because I was one of those burned out engineers. I think back in my life as more in commercial technology, I was always wondering what is the purpose of all of this stuff that we're developing and all of the hours and days that go into learning these new technologies.

I think I feel that I'm really lucky to have an opportunity to collaborate with a lot of really interesting people in a different domain like learning from them. And I think that like and getting to work on like these really big messy problems that we're facing and it gives me it's a chance to really, it's a chance to really kind of hone my skills in technology. And I think like and feel like I'm having some kind of an impact. And I think one of the reasons I think I'm doing it is because I'm it's also helping me to I guess find and probably deepen my relationship to technology rather than seeing it as just an income source. So I'm so I'm not really. It's still kind of like an ongoing thing for me, but I guess that's what kind of attracts me to this. And you get to

see a lot of cute animals too. But apparently not pet them? You do get to scare them. The scaring them is the best bit, guys. Our guests have been Dr. Meredith Palmer, a scientist currently at Yale University who specializes in predator prey research and behavioral ecology. And Akiba is the CTO of Freak Labs, an organization specializing in technology for wildlife conservation, ecological restoration, and international development. We'll have lots of links in the show notes, so please check those out. Thanks to you both.

This was really fun. Thanks, everyone. It's great to finally get to meet you and Elysia. Thanks for the opportunity. It was great to talk a little science with you guys. Thank you to Christopher for producing and co-hosting. Thank you to our Patreon listeners Slack group for their questions. Thank you to Mouser for their sponsorship.

And thank you for listening. You can contact us at show at embedded.fm or hit the contact link on embedded FM. And now a quote to leave you with. This is from David Koeman. He writes a lot about science and ecology and biodiversity. And his latest book, Wild Thoughts from Wild Places, is a lot about conservation. Humanity badly needs things that are big and fearsome and homicidally wild. Counterintuitive as it may seem, we need to preserve those few remaining beasts, places

and forces of nature capable of murdering us with sublime indifference.