This is Bird Note.

Scientists can now forecast bird migration based on weather and how it affects bird flight.

But weather isn't the whole story.

Habitat's on the ground also influenced the bird's journeys, says Ph.D. student Miko

Jimenez.

If there's forest cover or if there's a city, that's going to really impact where birds

are taking off from, where they're flying, where they're going to land, where they're

going to stop over.

Miko and his colleagues are working to add all kinds of landscape features into the

migration forecast model to improve it.

And they're using machine learning to tie together all these different types of info.

A type of artificial intelligence, machine learning can find patterns in huge amounts

of data much faster than a person can, and then use those patterns to make predictions.

Still, Miko says it's not as simple as computers to the rescue.

I think it's really important to make this point that machine learning is making these

huge advancements, but there's also people that are behind all of those really important

milestones that we've had.

What machine learning offers, he says, is the chance to solve complex problems that until

recently were just out of reach.

It feels like everyone's kind of working on this huge jigsaw puzzle in their own section,

where at that point where we're starting to put these big sections together and figure

out this bigger picture.

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