- There's a lot of talk about AI,
Artificial Intelligence these days.
AI is gonna change the world, and that might well be true.
If you're building a startup right now
it's relevant to know what industries
are gonna be disrupted by AI.
So that's what we're gonna look at today.
What three industries are next to be disrupted by AI?
(upbeat music) This is Raw Startup.
I'm the founder of Vivino,
the world's largest wine app and community
with over 16 million users all over the world.
And I've bought on an expert for this.
Yannic Kilcher is a developer and YouTuber.
With a channel that covers artificial intelligence
and machine learning.
He knows what he's talking about.
- The AI system's going to be so competent
that some humans just can't compete at anything anymore.
- Disruptions always create opportunities,
opportunities for startups, new startup ideas,
and you'll see a lot of that in this video.
Also, throughout this video,
I will only use images created by AI
so you can see what they actually can do.
In the end we have a chat about
what AI is gonna do to the world.
Is it gonna make the world a better place or not?
So stay tuned for that.
With that, let's get started.
Number one, creatives.
This is what's called generative AI.
You give the AI some instructions
and it builds something totally from scratch.
For example, I can say,
yellow car drives alone on a highway and in seconds
we have a new original picture created by the AI.
Pretty darn impressive.
The area specifically affected by generative AI
are images, writing, music and video.
So what has happened lately with generative AI?
- It has always been a bit like a kind of a playground
but now these things really have quality
and they can really be directed.
They understand what you want
and they can give you a nice, meaningful,
crisp, artsy, whatever you want.
A picture out of that.
- Okay give us an example of someone
who's been disrupted by that.
- If you previously had a job as an illustrator
where you took like description of what to illustrate
and you just drew that according to specification,
I think that's kind of like driving a chariot 100 years ago.
Like cars are coming, drivers aren't going away
but certainly chariot drivers are.
- Okay let's talk about what businesses
and creatives are gonna be disrupted and how and when.
- Some are gonna be out of work
but others are gonna even have more work
because a lot of these tools enable artists
to express themselves even to a greater degree
like the interaction between the AI and the artist.
So we now have tools to produce images.
We have tools to produce writing,
to collaborate on writing.
We have tools to collaborate on music
and there's gonna be a whole bunch of other tools
like video, 3D gaming and so on.
- Okay let's talk a little bit more
about how these models are made.
How do they actually learn and become smart?
- The entire visible internet is scraped,
filtered down to like a qualitatively high quality set
and then is ingested into these models.
So they've seen huge amounts of data
and they can draw from all of this.
So what they do, essentially, it's still a bit debated
but essentially what they do is
they kinda take a bunch of stuff they've seen
and they sort of mash it together in a meaningful way
according to what you want.
The question, like some people say
that's not really creative, but then the question is
do you as a human really do something else?
- Yes that is a good question because we also get inspired.
We see something and draw something inspired by that.
So the difference between how AI is inspired
and humans are inspired, maybe not that big.
- I think artists don't need to be worried
because I think the essence of art
is sort of the kind of abstractive reasoning
mixed with maybe a bit of social commentary
or just express human emotion in some way.
And these systems are very far away
from achieving anything like that.
- Okay so let's have a look
at how it gets integrated into some of our tools.
- If I want a PowerPoint presentation
and I want just like a little diagram of a yellow car
because it maybe illustrates my point,
that is going to be fully AI based very, very soon.
Essentially you're gonna have an illustrator,
a person that does illustration according to specification.
You're gonna have that as a plugin in PowerPoint,
in whatever you want.
And you're gonna have the same in Microsoft Word
to help you write some sort of-
If you have some sort of standard copy to write
you're gonna have AI assistance helping you with that.
- Now that is pretty cool.
Let's try and look a little bit further ahead.
- We don't know what the future brings
but it's entirely thinkable
that future movies will not be entirely scripted by a human
but actually could be even a bit interactive,
like a video game nowadays but personalized to you.
Maybe a different ending every time you watch the movie.
Who knows, right?
I think we can't really yet fathom what is possible
with these technologies.
- A lot of services have been released already
but there's so much more to come.
- There are companies doing this right now,
bringing image generation, text generation and so on
into people's workflows.
But there are a whole lot, like 99% of the use cases
of just these models are not yet done
and are just I guess up for grabs.
- So many opportunities in the generative AI space.
There will be 100s if not 1,000s
of new startups built on these opportunities
with new startup ideas.
Number two, driving.
We've been told for years that self-driving
was just around the corner
and we should be doing self-driving by now,
yet we're still driving our own cars.
What's up with that?
- Two things have happened.
One is we have actually become massively better
at self-driving cars.
I think there are demonstrations back to what?
The 1970s of self-driving cars that could just
you know, lane guidance system essentially
on an empty highway.
That was always possible.
But to drive in any kind of environment,
road conditions, here is a construction site there.
Here the lane markings are off,
there's something on the road.
Like these are the hard parts
and we don't even realize when we're driving
how many of those we encounter every day.
With that being said, we have gotten a lot better at that.
And second thing that has happened
is I think that we have toned down,
or at least most of us have toned down
our promises a little bit.
- The thing is this is not binary.
It's not gonna go from we drive
to 100% self-driving overnight.
It's gonna be multiple steps
and some are gonna get disrupted first.
- So I think we can confidently say that in the next years
something like long haul trucking
will be definitely be disrupted, be replaced,
or at least to a large part assisted by AI systems.
There are various propositions.
One is that, for example, you have entire convoys of trucks
with only the front truck being driven by a human driver.
The rest simply is AI followed.
The other systems imagine something like
the trucks as soon as they're on the highway,
they go by themselves
and then as soon as essentially they exit the highway
then a driver from some data center
like essentially a remote control driver takes over
to do the inner city delivery or something like this.
There are various ways in which we can circumvent
these really difficult problems that we spoke before.
These very difficult road conditions,
urban environments and so on.
Because on the highway, especially American highways
they're like always the same, right?
And road conditions are generally quite good.
- I mean take a shuttle that drives the same route
a 100 times every single day at an airport.
That's something that self-driving
can probably do already today.
- This is a controversial opinion in the AI,
let's say space, the machine learning space
because most people have observed the last few years.
Have always noticed that it always takes longer
than we think, it's always harder than we think.
I personally am still optimistic.
I can't even tell you why,
but I personally still think that within five to 10 years
I'll be able to buy an actually fully self-driving car.
Whether it's gonna be legally allowed
for me to own one is a different question,
but I think the technology will get to the point
where I can just say drive me there
and it's gonna drive me 99% of the way.
- Legal is another front we have to cross.
It has to be legal obviously,
and that could take some time.
- There will still be a lot of need for human drivers.
There are many, many routes for goods
and people driving that are simply gonna be too difficult
for machines in this near future.
- [Heini] Short term yeah. - Right?
And so I think it's not gonna be like,
"Oh now Tesla releases FSD
and now every driver is gonna be out of a job."
It will happen gradually and it will happen such that
the drivers who are being quote unquote replaced
will be able to essentially specialize
to be able to do higher quality driving, harder routes.
- Now I think this is a lot of the theme for AI.
The simple tedious task will be disrupted.
If you drive a shuttle bus 500 meters a 100 times a day
you will get disrupted.
If you on the other hand are a very skillful driver,
drive some difficult tasks, you will not get disrupted.
At least not yet.
We're gonna go for the easier tasks first.
And take Waymo, they're based in Phoenix, Arizona.
There's a reason why they're in Phoenix, Arizona.
It's flat, it's mostly sunny,
and all the streets are pretty straight.
Solving that problem is much, much easier
than driving in San Francisco.
It's hilly and messy in all kinds of ways.
Cruise is still based in San Francisco
and do their tests in San Francisco.
Maybe they just like a challenge.
Number three, data entry.
A lot of people work in data entry.
It usually means taking some data from the real world
and putting it into a computer.
Somehow structuring the data so the computer understands it
and computers usually haven't been very good at that.
- It's a very hard problem
and people don't know it's a hard problem.
For example, if you have an invoice, you go to a restaurant,
you pay with your credit card or something,
you get an invoice.
Even that simple thing from a restaurant or a grocery store
it is actually very hard for a computer to read that
and to understand what's going on
because to you everything makes sense.
You see like a bunch of numbers.
You're like, "Oh yeah these are the things I bought."
And then you see like some weird number
with a lot of comma digits, like that's probably tax
because it's like some percentage of something, right?
And that results in a weird number right?
Now if you simply give this to a computer.
It's very hard for the computer
to understand something like this
and extract the information necessary
to put into a digital system like an expense system.
If you go buy something or imagine you know,
like let's say the border.
The border has border guards and whenever you come in
with a good that you need to declare
you need to fill out some sort of form, right?
Now you can have all kinds of goods, right?
And you can have all kinds of countries
where they come from in special circumstances.
And to humans, this is just also natural.
But to computers, it's super hard to then extract,
take that data out of forms,
out of things they see and put them into a specified format.
- Okay, so we have all these challenges.
How is that changing?
- People have thought for a long time that this is easy
and most people, if you ask them,
still think it's easy for a computer.
But only with now the advent of essentially
large scale machine learning, learning from lots of data,
has this become a possibility
to automate to a large degree I would say.
What I think with many, many, many of these data entry jobs,
what's going to happen is that
the human isn't gonna be replaced.
The human is gonna migrate to a position
of a sanity checker for the system.
So the tedious work of actually typing
and copy pasting from one thing to the other,
that's going to be taken over by the AI
but then it's gonna be presented to the human
and the human needs to decide does it make sense?
Right?
Check it, see whether everything has been mapped correctly,
things like this.
So again, we're gonna not see that much of a replacement
but a drastic shift in how work is being done from-
- So it's about training the machine
and also assisting the machine when it's in doubt.
On top of that there's speed.
- Or you can do a 1,000 times more
or higher quality work, right?
Which is ultimately what we hope for
when we deploy these systems.
It's, yeah one part is obviously to save money
and there's an element of that.
But also I think you know with,
for example in manufacturing
precision tooling has brought not only a decrease in cost
but also a massive increase in production quality
as compared to Henry Ford's assembly line
where every worker did that by hand.
- So now the human can work a 100 times faster
and maybe even with a higher accuracy.
Good, now where does that leave us for the future?
- So I am, as you are a,
let's say a techno optimist in that
the general trajectory humanity is
is the better our technology,
the better off everyone is, right?
I believe technology is like a driver for human welfare.
That being said, so far we've always managed
to sort of just take the humans
that are being replaced quote unquote,
be it they were farmers, now they're factory workers,
or they were chariot drivers, now they're truck drivers.
We've always been able to do that,
to shift the humans to more qualitative jobs
rather than just tedious jobs.
The question is, will we always be able to do that, right?
The question is, are the AI systems going to be so competent
that some humans just can't compete at anything anymore?
And it's a question.
I don't believe that's going to happen
because I believe there is a qualitative difference
in a large way from humans to machines
no matter how well we build them but it could be.
- [Heini] Yeah.
- We've never been in that situation
where there's just a bunch of humans where we think,
"Well there's nothing you can provide
that's of economic value, right?
That these AI systems can't do."
Like it's pretty harsh to say,
but we have to think about what to do
if this really happens to be the case.
- So you have all this disruption.
What does that mean for society?
Is it gonna make the world better or worse?
- Both.
Certainly gonna make the world different.
I believe the net will be positive,
just my personal belief.
And so far for technology in general this has been the case,
not for all technologies individually,
but in general it has been the case and I'm very positive
and I can personally see much more
positive use cases than negative use cases.
So I'm pretty excited.
- I think it's the same with most technology
and actually most tools.
They can be used for good and for bad.
Most people use it for good and a few use it for bad.
So here are the three industries
that are gonna get disrupted next.
This will create a lot of opportunities,
startup ideas and new startups.
Also, if you disagree or we miss something,
put it in the comments.
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Thank you very much for watching Raw Startup.
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(soft techno music)