KARNO TENOVUO: The mission is to make autonomous
ships a commercial reality.
When we originally set out to do that,
we thought that it would happen a bit later, 2025-ish.
Now we see that the market disruption is actually
happening much faster.
And we need to take into account many activities.
So we start from the intelligent awareness,
basically giving the ice to the vessel.
We are also working on connectivity solutions,
so transforming the data from ships to shore.
We're building remote operations centers.
So basically the infrastructure that you
need in order to operate vessels from shoreside
and monitor them.
And then we are developing autonomous systems
starting from navigation systems,
but also, then, later on moving into machinery systems,
so basically covering the whole vessel that will
be made autonomous one by one.
We're looking to basically automate the data flow
from censoring to data warehousing to annotation,
and then to machine learning models and training the models.
And we're looking to automate that data flow,
and really, Google is the best partner for that.
Autonomous ships will affect, basically, safety, reliability,
and efficiency.
Those are the three main drivers, safety, reliability,
and efficiency.
That is basically driving the whole development.
On the safety side, you will have
a lot of accidents that are happening today
are happening for the crew on board the vessels.
And now we can save a lot of accidents
from happening when we are actually moving the work
to shoreside, or then making that work
more automated in the future.
So that is one thing.
And of course, reliability comes, that there's
a lot of breakdowns today.
The systems onboard the vessels are not reliable.
So they have to do a lot of maintenance while in operation
today.
In the future, when the systems are more autonomous,
they also need to be more reliable so there isn't
so much need for the kind of maintenance work
that you have on board the vessels today.
And then on the efficiency side, you can, of course,
now have the same team of experts sitting
in a good office environment supporting multiple ships
or tens of ships instead of having technical expertise
in each of the ships.
So the work is the same but now more efficient.
We can already use a lot of the solutions that
have been created for other industries in the machine
learning space, and we can now apply them to change
the shipping world as well.
There is a lot of things we haven't done yet.
So we need to, for example, create now
the machine learning models and train them for marine use.
We need to basically gather the data
so that we can train the models, also, for example in nighttime
and in different weather conditions
and different viewing angles.
That kind of data set we need to create so we can have the best
models out there.
In ships you have a wider area to cover.
We're using LIDAR, we're using radar, HD cameras.
We have to cover a wide area because there
can be very unpredicted movements of a lot of vessels.
That requires a high computing power on board the vessel.
And the good thing is that they have a bit more time
to do the analysis, for example, compared to cars.
Some of the Google Cloud technologies we're using
include, for example, TensorFlow processing unit
that we can have on board the vessels.
You have data jobs.
You have HyperTune, and then data labs.
Those are the tools and solutions
that have immediate benefit for the autonomous ships.
Key takeaway is basically speed and flexibility
to bring this to the market fast.
So don't try to do too many things in house.
Partner, use open platforms and collaboration
to drive this innovation fast.