Hello, and welcome
I'm Alicia and I work at BBC Research & Development.
Oi oi savloy! Guess I'll just introduce myself, then.
'cause no one else is gonna.
our job is to investigate how we can make things for the BBC
using new and exciting technology.
Today we're going to take you behind the scenes of Springwatch and explain
What artificial intelligence is all about.
Hi, I'm Oscar from BBC Research & Development. Springwatch is a nature show where
we get to know the animals that we have here in the UK, and that includes birds you
might see in your gardens, such as robins or great spotted woodpeckers.
But also some of the more elusive ones such as otters.
Hm. What about the best bird?
AKA, me?
If you've ever tried taking a photo of a wild animal
you know, just how shy they can be.
Missed it! On a show like Springwatch
lots of cameras are used to try and capture video of the different
animals, and when using lots of cameras there is a lot of video footage
that's generated, and I mean a lot of footage. WOAHHH!
There's only 24 hours in the day and even with a team
of people they're not able to go through and
try to find all the animals. This is where BBC R&D can help out.
We've got a piece of technology that can assist the production teams.
Oooohhh, here comes the best bit.
We've created a piece of software, so a computer program
that is able to detect mammals and birds. When it detects
it even draws a rectangular box around them.
Ooh! Me! Me! I wanna box! I wanna box!
Sure, we can add that. Come on, come on!
That was not as good as I was thinking it would be.
Why don't we take a look at what this software looked like when it
was applied to footage from Springwatch, Autumnwatch and
Winterwatch from the last 12 months.
Here we see the detection software running on some footage of a bird feeder.
Notice how the birds as soon as they're detectedd by the software
get the rectangle drawn around them.
The software also works on night vision footage, as seen here.
It even works on video footage were the animal is just running through the scene really quickly. Like here.
Now we can see that's one of the problems solved.
We now know where in the video, that there are animals present.
But as anyone who has ever been birdwatching
knows, we're also interested in
what species the bird or the mammal is. Like I'm a pigeon?
Exactly. Some of the other species you might know about could be
maybe goldfinches or barn owls. We've created a second
software, which is enable to focus on something else. And that's
distinguishing between different species of birds. Now it might sound a bit weird,
but the second software can't actually detect any birds or mammals.
It can just differentiate between species.
But, that's how this software works. It focuses on one very specific job
and tries to do it as well as possible.
Let's take a look at what happens when we apply this species
software to the footage from earlier.
It doesn't always get it right. Because this is a really challenging task
even for a computer, but in this case
it does a pretty good job. We could even try on some footage
of some bigger birds and it works well here too.
Now, you can see how this is helpful for the production team. They no
longer need to sit through and watch footage of empty fields and emoty nests
they can focus on the interesting bits when something's happening.
This sounds really smart actually. How does this intelligent
software work then? The process used to create this software is known as
machine-learning and it generates something that's known as artificial
intelligence so you could in one sense say it is smart, but it's
not smart in the human sense and things can very easily go wrong.
My colleague Alicia's gonna talk in a bit more detail about how machine
learning works. So stay perched infront of your screens, and pigeon
why don't you head over and hear what she's got to say?
What?! If I must then. See you later.
We are now going to try to explain a bit about
how artificial intelligence, or AI works,
using birds. And pigeons! We built this app,
which helps recognising and identifying birds in your photos.
You upload a photo of a bird.
Hey, that's my sister! And ask the machine to identify it.
The AI tell us its best guess as to what is in the photo
In this case it thinks it's most likely to be a wood pigeon, but it may be a dove
or a jay. That's not a dove! The AI thinks it knows what the bird is
but it's not 100% sure
just like humans it can sometimes get things wrong.
Let's try a different bird. This is a photo of a flamingo.
They're pretty easy to spot. Even I know that.
What's going on? It's pink and standing on one leg.
It's obvious. The problem here is the
AI has never been shown a flamingo before, it knows nothing about them.
It doesn't even know there is such a thing as a flamingo.
This is because AI system need to be trained on examples
of things you want them to identify. They need to learn.
So we show the AI thousands of millions of photos of birds.
Maybe 100s of photos of each species and importantly for each
photo we tell it exactly what species it is. A bit like going to a school
that only told you about what birds look like. That would be pretty boring.
Ooh. Let's try it on photos of humans.
OK, here's Springwatch's Chris Packham.
Oh, and as Oscar mentioned earlier, this bit of AI Software,
only do very specific jobs.
This one knows about UK garden birds, not flamingos, not humans and
definitely not Chris Packhams, but it still makes a guess at the bird.
it doesn't know what it doesn't know. So, what have we learnt? A particular AI
usually does one thing only like detect animals or identify birds species,
but it can be pretty good at it and very fast. An AI is never certain
it's always making a best guess based on what it has been told.
An AI only knows about what it has learnt just like humans.
You've probably seen AI portrayed in films as super smart,
world dominating robots. But really right now, they are not
even as smart as pigeons. WHAAAT?!