a war it's about the atmosphere in which these parliamentary and local elections are taking place like sound of phenomena that in the serbian capital above. right. thank you very much for the summer and that's it for me in the news team for now we'll have an update for you at the top of the don't go went up next kind of artificial intelligence. help protect animals, threatened please extinction. and that's an off tech show shift right after the break. i'm good. how about the imagine that you're eating a hamburger and as you're biting into this juicy burner, your dining companion says to you, actually that hamburger is not made from the house. it's made from golden retrievers. 2 should we. 2 2 2 2 2 2 2 in

meeting cultures around the world, people learn to classify small handful of animals with edible and all the rest they classify as disgusting. w series about a complex relationship with animals. the great debate. what's, you know, on youtube, dw documentary. the, we're living in an area of mass extinction, one unmatched, and the last 6 to 6000000 years since the dinosaurs were wiped out over a quarter of all mammals species and one in a species are on the brink. but kenny, i help save them today on shift it is not only natural, these offices and climate change that threatened wild life po, chose, for example, to over $20000.00 african ellison's every year ranges and national parks have been struggling to prevent the practice. but that's non profit organizations,

heck the planet has develop in a camera system to detect pushes and sound the alarm in real time and a triggered warning view as might find some of the following imagery distressing. african ellison populations have fallen drastically in the last century. one major cause poachers, they want their ivory to stuff them, the nonprofit organization, the heck the planet as found a way to modify the existing camera trips these uh, these cameras, we call them the dump cameras. we. we make them smarter, so we modified, i'm a little so um, so that they are unable to communicate with a box that we created. we manufacture these amazing, able to communicate and send the photos wirelessly. and we analyze these photos using ai. so we have a machine learning algorithm on there and analyzes the photo, and then we immediately know what's on the photo if it's a human or it's,

and allison's if a person is detected and alert, sent to rangers immediately, this way they can react quickly to potential poachers, which wasn't possible before these range are units, oftentimes they just find an edison's carcass. uh and, you know, then, then the poachers are already gone, like maybe one week or 2 weeks ago. and they don't have any information to go from . because it, you know, they don't know where they came in or where they went out. because it's such a huge area. the smart devices make it much more likely to catch in traders and real time they work via satellite and don't need why fi countries like come on. sam b, as in bob way, have already implemented the smart camera trends for the endangered african elephants and those who protect them. the technology could mean the difference between life and death. in india, allison's and killed

a different dangers to around 20 of them. i ship and killed by trains every year. that's why in a i warning system is being installed a long railroad tracks. sense of identifying operations on the ground caused by elephants and sent a warning signals to prevent collisions. it's undoubtedly an issue, but one was by the threat of global warming. 2023 was characterized by devastating fires around the world. greece, spain, hawaii, canada. in australia. hey i technology is now being used to help protect animals like the kangaroo and the koala from the effects of bush fires. a koala is on the move under the cover of night, just like these wallabies, the congress smaller because the for australian wildlife conservation of these images are a small victory. using camera traps,

they are trying to find out how well different animal species are recovering from bush fires. so the camera takes the animals by a combination of movement and hate from the animals. so as the animal looks past, the camera, usually around with the bite spacing, is if it gets triggered and takes 5 quick photos of the animal as it comes to pass to get on the karen greenville researches in the conic blue mountains west of sydney. the area is a tourist drive, but is also prone to bush fires. that's why it was included in w w. f. us really is large scale camera sensor project i is on recovery of about 1100 camera traps were installed all over the country, especially in areas damaged by the bush fires of 20192020. the cameras generate millions of photos helps researchers analyze the data. ready

the artificial intelligence is actually enabling them to sort through these images much more, much more rapidly. so it's basically improving their efficiency so they can go out and do you know, the work of the work that they need to do to manage that of species recovery, for instance, after collecting the photos from the cameras, researchers upload them to an a model called wildlife insights the google powered platform has a database of over 35000000 images and is being used by wildlife organizations all over the world. detects what kind of animal is seen within an image and labels that accordingly helping research move along more quickly. ready that we find ourselves in this point in time where climate change is is meaning we're having more frequent fires, not just in australia, but across the entirety of the world. so projects like eyes on the cover that

developed technology that can help us to assess impacts more rapidly just absolutely crucial for understanding future fire events in australia and across the world. well, the blue mountains look lushin green. now, it is just a matter of time before the push fires return and the animals suffer. the system won't save the animals in the event of this aspect, but knowing where they live and how many they are is extremely important for conservation. but how do the databases work? we asked them to explain it for us. it's as easy as drag and drop, or researchers upload photos to one's life insights within seconds, image recognition, i identifies the animal. so when a research or a biologist uploads their camera trap data to the wildlife insights platform in our

artificial intelligence model, most of the images and based upon what we, what we shown it before, it makes a prediction on what it thinks it sees inside the image the i matches the photos to animals that has been trying to recognize the database contains entries for over 3000 animal species. a value of one means absolute certainty. so 0.99, just from this image of an elephant, the trunk is very close. indeed. va isn't always that confident, for example, when distinguishing a leopard from a judge you are on so platforms d, i can even recognize individual anonymous sharks, for example, of unique patterns on their skin, which allows them to be identified algorithms, then much to patterns like facial recognition software. ready

wireless can be clearly distinguished by their tail fins, allowing researchers to learn more about their movements box and turn can lead to better conservation for the marine jones. but sometimes pictures alone, the enough waves, for example, rarely come to the surface. that's why scientists also use sounds to find out more about them. sounds like this. what do you hear a because of the barriers weight of specie is recorded in the alaska sound samples like these, collected worldwide, the problem microphones, folding victim to interference. but with the use of a i, we so it says that able to filter at the end of he runs out and see a that calls and our feeling is mostly an efficiency thing. if you apply a i, it kind of figures out the easy decisions for you, and then it lets your expert look at the areas where they,

i'm so sure. and it allows the experts do with the past to validate. and the a, i really takes a lot of the like fruit for us out of the. so we've estimated that it saves as much as like 96 percent of our time. the sounds can even be assigned to individual way of specie is sped. why is this important? well, some specie is like this right away here. critically and they just, we found a call like just kind of a cryptic call. we didn't know who it belonged to, but we thought it might be a, essentially right, we'll call. we're able to search our entire dues, we would never been able to do that without a i, and for a population of 30, you know, every data point counts because they're super rare, you really don't expect to find them. so having, having tools that allow you to call these huge datasets, leave no stone on terms is essential for populations like that. but it's not just the ocean designs that are threatened with extinction. insights in particular addressed european populations are declining sharply, but a i can help you too,

by showing us what these really needs to try to design their own garden. it would look like this. at least according to alexandra daisy ginsburg, the garden in front of berlin's natural history museum as her art project. as an algorithm, as chosen, which plans start to grow here? every time we run the algorithm to create a new prompting scheme, the algorithm is optimizing the tom thing choices and arrangements to have the most diverse group upon and 18 species possible. so these were most and many more following the algorithms, certifications, ginsburg, and our team planted 7000 plants here in the heart of berlin. the project is called pollinate, or pass maker to develop the algorithm, ginsburg and her team researched the exact needs of local pollinators. the

algorithm then generated a planting schematic with $150.00 plants. species even calculates how the garden will change throughout the year. the, the algorithm chooses plots that are appropriate for each location for the soil conditions, sunshine, so on. and then it arranges, it takes a subset to create unique schemes every time and then a range of them and ways that see different charging style up to my business as a whole. different insect pollinators locate their food in different ways. some insects, such as bees, memorize the locations of flowers and develop efficient flight routes to visit thousands a day. the i will look most on the algorithm anticipates the pollinators flight path. so most of us with the planting pattern is based on the data for the men, special olga, when the voice all of the above,

it looks unusual to the human eye, but it's designed around the weight and sex. moved around the garden in the garden, just i don't answer then you can use the algorithm yourself to calculate a plan for an insect friendly garden, free of charge. the web based tool is optimized for your opinion, wildlife, but models for other regents could soon follow hey, i can go through a huge amounts of data very quickly helping us understand lots of greenery and even large and complex eco systems. this new technology has become an integral part of conservation. that's all from me. take care to next time by the

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