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- It's interesting as you walk the floor here.
there are robots, there's drones.
What you don't see is the data
that is informing all of the robotics
and the artificial intelligence.
Tell me about the project that you've overseen,
the Swarm project at Toyota.
How that started and how it's evolved?
- Our customers, and this is no news,
are living in exponential times.
They're having explosive change
coming to their whole supply chain,
and that's where we from Toyota Material Handling
have the focus onto.
We're seeing that there are more SKUs coming on.
There is e-commerce that is bringing 24/7 needs into it.
Customers are getting very impatient,
they wanna have the product next day.
So the one side there is an explosive demand,
or change in demand.
On the opposite side, there are less and less people
who are willing to work in this environment,
and work as forklift truck drivers
or work in an order picking zone or transport material.
So, customers are sitting there
and, for them, it's getting more and more of a boondoggle.
They don't know how to get out of it.
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So what we have been building is a concept that
should help them and it starts with a very simple
scan of the warehouse of an existing situation.
So we come to see our customers in the future and say
"Show me your warehouse."
We're scanning your warehouse, we're building a
full digital twin, starting with two-dimensional
but then use Bonsai technology to build in the
three-dimensional scan.
Take the software of the truck,
put it into this environment, let it learn there.
Let it learn where to drive, where not to drive,
how to respect pedestrians, how to pick up material,
how to deliver material, all these things,
and practice in a safe environment.
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- We spoke a little earlier about
phone calls that you might get from customers.
You were talking about predictive maintenance and
how AI helps with that.
Tell me the story you told me about those phone calls.
- Yeah, you know, we have a number of cases with
customers that, when you have my type of job,
you're used to getting phone calls from a
very angry customer where the machine has just broken down,
they have fifty-thousand liters of milk
that have a very short shelf life,
and the machine is broken and they can't do anything.
So with predictive maintenance, through AI and so,
it's a lot easier because we call them
four weeks before and tell them that
you know, there is something that might break soon.
So we will come in two weeks and fix it.
So we will not have that very unpleasant phone
conversation four seconds after a big failure has happened.
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- Throughout the book, there are conversations about
conserving energy, saving water.
I wonder if you could say a little bit about AI for good.
- Um, absolutely.
With Osram, we're showing how light and
artificial intelligence can enable greenhouses
in terms of optimization of using less chemicals
and fertilizers, less water, but still be able
to have very nutritious and very healthy,
whether it's lettuce or whatever it is that you're
growing, be in control of that environment
where that engine watches the entire operation
and optimizes it for you.
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- Microsoft is, of course, thought of as a software
company but it is also a manufacturing company, as well.
Where is Microsoft in its AI journey
within manufacturing?
Maybe talk a little bit about Microsoft as a manufacturer.
- We as a manufacturer, one, we're a relatively
sizeable manufacturer. Over 40,000 SKUs shipped to
over one hundred countries.
So it's a sizeable operation.
We are what we call at a predictive phase.
So we get a lot of predictions
not only from our assets in terms of calibration,
tuning, et cetera, but also from our
supply chain where we can follow up.
Any SKU, where it sits in a container,
what is the container, who's carrying it,
a ship, a railroad, a truck, route, driver, insurer,
it's extremely connected and visible.
And then we can predict a weather system coming in
and its impact on it or a strike happening somewhere
and its impact on it.
We can re-route, re-insure, it's just a
fascinating AI-enabled environment.
Now we're moving to a cognitive phase
where we think artificial intelligence
will be able to make 30 to 40 percent
of decisions for us so we unleash leadership capacity.
They manage by exceptions, perhaps, but do not do much
fire-fighting and they focus on the strategic
issues to move the company to the next level.
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