as someone who is generally skeptical of things that get marketed as "X...but with AI" this seems like a genuine success story:
as someone who is generally skeptical of things that get marketed as "X...but with AI" this seems like a genuine success story:
In 2018 a team of researchers at Cornell University boosted the capabilities of a tracking technology called BirdCast to monitor and predict mass movements of birds on the wing. The original project began in 1999, but the technology lacked automation and required hundreds of hours to analyze and predict migration. The platform now monitors birds as they glide over the U.S. using radar from the National Weather Service. A.I. models trained on years of historical data pull out live bird migration data in minutes and forecast their movements at the county level up to three days in advance. Five years since the innovative tool’s update, we checked in with researchers to hear how it is helping with science and conservation.
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An academic project at its core, BirdCast is still being used to study birds. According to its website, the team that runs BirdCast at the Cornell Lab of Ornithology has published two dozen scientific articles related to the platform since its 2018 update. Some researchers have used the system to investigate the factors that put birds most at risk of hitting a building, or to potentially make aviation safer by building models of when planes hit birds.
I am also that way with AI, especially for superficial things like writing emails or papers or other things in the same vein. But AI for stuff like BirdCast is what AI is supposed to be used for,...
as someone who is generally skeptical of things that get marketed as "X...but with AI" this seems like a genuine success story:
I am also that way with AI, especially for superficial things like writing emails or papers or other things in the same vein. But AI for stuff like BirdCast is what AI is supposed to be used for, helping researchers cut back the hours that they used to do, like analysing hundreds of hours of data. And helping people for the greater good and not for a paper that someone did not want to write for an assignment in school or for their work or generating "art."
Because writing emails or papers or the like are what most of the population will be doing, and those are also the sort of tasks that ChatGPT is really good at, which is corpo talk. Bird flight...
Because writing emails or papers or the like are what most of the population will be doing, and those are also the sort of tasks that ChatGPT is really good at, which is corpo talk.
Bird flight tracking is a very specialised application of machine learning that required you to actually have the data of their flight behaviour, which is why it took them so long to do (quote "years of historical data"). The insight here is that moment in time when the decision to design how and what to track was made. Imagine the program director just said, "Meh, machine learning and AI just feels like a gimmick to me. I won't authorise a budget for this."
as someone who is generally skeptical of things that get marketed as "X...but with AI" this seems like a genuine success story:
I am also that way with AI, especially for superficial things like writing emails or papers or other things in the same vein. But AI for stuff like BirdCast is what AI is supposed to be used for, helping researchers cut back the hours that they used to do, like analysing hundreds of hours of data. And helping people for the greater good and not for a paper that someone did not want to write for an assignment in school or for their work or generating "art."
Because writing emails or papers or the like are what most of the population will be doing, and those are also the sort of tasks that ChatGPT is really good at, which is corpo talk.
Bird flight tracking is a very specialised application of machine learning that required you to actually have the data of their flight behaviour, which is why it took them so long to do (quote "years of historical data"). The insight here is that moment in time when the decision to design how and what to track was made. Imagine the program director just said, "Meh, machine learning and AI just feels like a gimmick to me. I won't authorise a budget for this."