Okay, can everybody hear me?

So welcome to the AI lecture this semester.

Special welcome also to the people who are still at home because they have visa problems

and are only listening to this online.

I'm very happy that so many of you are actually in the room.

Being actually in the room is a good thing for learning.

So I would like to encourage you, even though in Alangan the weather can be not as nice

as maybe where you're coming from.

On Thursdays the lectures are early.

But there's a very, very good correlation between learning, which is what you're here

for, and actually being here.

So I would like to encourage you to actually come to the lectures.

We can't make you, and we're not going to make you because you're adults.

Just wanted to give you the facts about learning.

So AI1, artificial intelligence.

But I have a show of hands of who of you is an undergraduate?

Meaning still in the bachelor's phase.

There's no wrong or right answer.

Well, there is a wrong or right answer.

Right, so who is in the master's program AI?

That's quite a lot.

Who is in data science?

That's typically also a big portion, and it is today.

And who is something else?

Whatever.

Okay.

I am a computer science master, I should probably say.

Less than expected.

Okay.

Just shout out.

What are you?

The others.

See, this is an important lesson.

You have to go out of your comfort zone sometimes.

Ask questions, give answers, and so on.

So let's try that again.

What are you others?

Math, yes.

Nice.

What else?

Ah, yes.

Interesting.

Yes.

Electromobility.

Yes.

Medical engineering, I heard, and something else I couldn't decipher.

Mechatronics.

Mechatronics, okay.

So you see, you are a diverse crowd.

I've studied mathematics myself, and I still consider mathematics my first love academically.