Hi, Jeroen, thank you for
being here with us. Give us very short introduction on what you have worked on and then we can proceed with some more technical details
Okay, that's fine
I've been working in IT
In finance solutions, database solutions, data science solutions for a long time and
gradually, I moved into the machine learning part. I did a lot of machine learning in the financial world.
I programmed a couple of systems for analysis of various
financial instruments.
And yea for some time I
gained some interest in how these self-driving cars work,
how computer vision works. And that made me start
doing research and so I found ways to
classify things. A lot of people can classify nowadays... like traffic signs on the road if you drive in the car
and kinds of other things that the car needs to know if you want it to drive by itself. In the Netherlands
We already have a couple of buses driving around the campuses. But the main issue is that
especially in
cities like we are now here in The Hague... some streets are very narrow
lots of corners
also lots of other objects in the street and it's very difficult to detect them all to find your way around.
So this will take some time for us
to develop the cars that can handle that.
So as you mentioned before
the way it was done previously with object detection was
not using any kind of neural network architecture, no convolutional networks...
No, there are a couple of bright engineers that divised
various techniques
with detection, for example, you can quite easily
detect whether a line of pixels is changing from bright to dark and if that's on a road it's probably a lane line.
So, that's hand-coded?
It is hand-coded and you can tune it but you have to have a lot of insights
to devise the right classifier. And that's a big difference
when you move to deep learning.
Also, you need to have a lot of insight but
it's on another level you
have to have insight in how
deep learning works and how convolutional networks work
but you leave the learning to the network itself. And you say "OK, if it works, it works!"
Right, so the filters essentially learn on their own what they're supposed to detect.
They learn the features on their own.
You don't have to hand-code the features.
You don't have to hand-code them but on your own it will be a bit too far I would say.
You have to devise what you like...
*Yes*
...and you have to feedback to the network what you don't like.
There's still a lot of engineering
with hyperparameter tuning and everything.
So what kind of algorithm would you use  in this case?
Would you use something like YOLO?
Like with the the bounding boxes?
Well "You only look once"  is of course
a great name
and it's very fast.
It helps a lot
to feed an image through network once
and gain a lot of information, a lot of insight.
You know what's in the image, you know where it is.
Location is even more of a problem
than just signaling that something is in there...
If а bike is in the image you can make a relatively...
... small network that could recognize that.
But if you need to know where it is in the picture
How big are these networks like a network that would be used in an actual self-driving car
that recognizes images and can tell the car to react in time?
Would this be an extremely deep network with like hundreds of layers?
Well it depends...
it depends on what you want to recognize.
There's a lot of two or three step analysis done.
If you find a traffic sign in the in the image then you can
cut it down and feed it to the traffic sign classifier.
So you have a two-step network and those networks don't need to be very deep.
convolutional - okay
But then it could be more than just do step headers
But because then there will be one network to classify traffic signs want to classify other cars vehicles in the world
Maybe another one to classify people or animals
Is it something with several networks all working together one would see like that?
Yeah, all these different editors
You need to know that and you need to program with individuals their society to come drive across 150
That the car doesn't drive all
switches -
there's different parts of
Yeah managing
Car management software that needs to invest in you mention regulations. How far are we accepting?
Driverless cars in vehicles
Because
Computers create accidents, especially when
We take a lot
On the other hand
I think that many people believe that this moves towards self graphic art will
Reduce the fatality s in in traffic
that's it's on a general level is anything but
You won't imagine what happens to a family either if one member is
Question I have is when these some private cars are first trained before they go on the action that they I
From what I've read you first think them in simulations
So you change them to navigate the virtual road and dodge virginal to cover obstacles like stop at traffic lights, etc
and then you would actually have a
crash test dummy car that does these things and then you put on the road after all the screaming but
Is the idea behind that that you would give every possible scenario to the cars that is how you generalize to all these scenarios
So when it is actually on the door, they could see something you haven't seen before and it still be able to
Vacuum question, there's a couple of approaches here and one one of them
Is that the car gets can already drive by itself that it?
needs to learn even more and
then
Someone is driving the car and the car is looking what you're doing and it's a driving school for self-driving cars
That's that's what happening
that's what's happening quite a lot, especially in the California where whistles car are on the road and
They're both house drug resistant video and sensory input and then they never gonna finish the most
Severe extension people. This is
measured and recorded and
also, the behavior of the actual human driver is recorded and
But wouldn't that be limiting the car to
Best human performance and like if you say that that's the standard and if it's a supervisor and proper form
That you think that the car the best performance of the car can achieve is that is how good the tiger is?
So there's something that God could have and yeah, I could have done better. It's not gonna
Be the only thing you do and then I would agree that the car bombs improves
On the driving behavior with the exception that the car is always on and always others actually would you?
like to the character to
Be able to is to recognize
Things you said that happen hasn't seen before. Yeah, and forest use, but it's also very difficult. Yeah, but
He doesn't get to generalize like of course like there's no way you can you can feed yourself
I've got every possible one of the internet scenarios that could happen on the road. Oh, but that's its general thing in AI that we
Not sure how to teach systems that kind of generalization
Quite good at
Sea
Detecting
All kinds of things as we've seen before
Also on data that's alive but if there are completely different data
that's good and especially difficult because
We would have mechanism now to
alert
The system let's roll. This is completely new behavior. What's happening here?
We need to make them and final question
You actually can start on this like did you follow but courses online people is how did you get that done
Then of course was the Udacity they're starting to self-driving cars shiny people or anything. Yep. Oh
No, I like your MIT I
Just started is very important public discourse. Yeah, they're very open
Recommend everybody to take a look at self-driving cars
So you would recommend that any to me
Well, thank you very much
Okay, thank you, yes
Exciting huh? So what do you think? I'm very excited about this. I think this is the first concrete evidence
We have of AI really taking a major role in everyday life
Yeah, it's it's very interesting and I can't wait to have my own driverless car and me too. And yeah, I
Love driving, but I'm pretty sure when it comes to
One or two generations in the future
They won't know how to drive or probably not. Yeah, but well
It's still gonna be
Interesting, especially to avoid traffic and definitely it's gonna be way safer as well. As I said, yeah. Alright
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Bye. Bye
You
