One of the most exciting opportunities in computing is what's called Edge AI. This is
where IOT and AI come together to revolutionize devices. Trillions of devices will be embedded
with sensors, connected to the internet. Data centers running algorithms that infuse them
with intelligence. This is going to be the Smart Everything Revolution.
Just as the phone became the smartphone and revolutionized the industry of communications
and created large industries around it--the same thing is going to happen to devices and things.
Devices with sensors are going to be connected to the internet.
Data centers are going to have amazing algorithms that infuse these
devices with apparent intelligence. These devices are going to be everywhere; whereas
there were only billions of smartphones, there will be trillions of things, and they will
be in all these different industries: agriculture, manufacturing, logistics, retail stores, warehouses,
airports, train stations, streets. We will have sensors all over the world and there
will be intelligence applied to them. The fundamental difference between a smartphone
and these Internet of Things, is the continuation of the sensor information. Whereas most users
interacting with their phones every now and then, in electronic time, the time separation
between clicks is basically infinite. These sensors are on all the time. They're
monitoring, picking up data, reasoning about what they're sensing and taking necessary
action. It's important that the data center is placed close to the point of action, where
the data is being collected. Otherwise the cost of streaming this enormous amount of
data is cost prohibitive. It's also important to put the data center
close by so that you could sense and react to the environment as quickly as possible,
where a few milliseconds make a difference. The speed of light traveling to data centers
far away takes too long. And finally, in many industries there are data privacy and data
sovereignty issues. In the future, there will be millions of data
centers all over the world, close to the point of action, close to where the data is generated
and sensed and processing AI instantaneously. These data centers are going to be very much
like the cloud data centers today. They're cloud native, very powerful, and most importantly,
secure. We created a computing platform for this edge AI application. We call it the NVIDIA EGX.
EGX was made possible by two advanced processors.
The first is the Ampere GPU, which has been designed for high speed AI processing, but
there are other capabilities that Ampere provides. The first is secure and authenticated boot,
so that you know that this computer is authorized to be on the network and run the applications.
The second is a new security engine for confidential AI. The AI algorithms are sensing, reasoning
and taking action, so it's vitally important that we know it hasn't been tampered.
This secure confidential AI enclave is going to protect the AI model so that it's encrypted.
And if it's tampered in any way, the program will not be allowed to run.
The second processor is the NVIDIA Mellanox ConnectX-6 Dx. It's a dual 100 Gb/s Ethernet
or InfiniBand. It has a crypto engine to process security protocols, TLS/IPSec at line speed.
It has ASAP2 accelerated security and packet processing with single root IO virtualization
that allows this computer to be secure and virtualized. And it has a brand new capability
called Time-Triggered Transmission, which connects the EGX server with the 5G radio
antenna and synchronizes the transmission between them. The combination of these two
processors makes up the NVIDIA EGX, and by installing the EGX into a standard x86 server,
you turn it into a hyperconverged, secure, cloud-native, AI powerhouse. It's basically
an entire cloud data center in one box. The NVIDIA EGX card is the starting point.
What makes it amazing is the software stack on top. We call it the EGX stack. The magic
of NVIDIA EGX comes alive because of the software stack -- fully integrated, fully optimized.
It has four major pillars. The first is that it's cloud native: designed for Kubernetes,
orchestrating containers, managed from afar, the ability to update software without rebooting
the computer. Second, it's the world's first GPU-accelerated 5G baseband radio. Our first
partner is Ericsson who is already developing 5G stack on top of NVIDIA. Third, a fully
optimized high-performance AI processing pipeline that we are world famous for. And then lastly,
this entire stack is optimized for networking, storage and, most importantly, security.
This one box is essentially a state-of-the-art, cloud-native data center that is secure, and
could be managed from afar. It is tamper-proof; data is protected in motion and in place;
it is authenticated before it can come onto your network, and as a result you could manage
a fleet of data centers, and all of those data centers are sprawled out, all over your
geography and all over your market, connected to sensors, applying intelligence to the products
and services that you offer. The EGX stack comes with several reference applications.
The 5G reference application is one. Another reference application is called Metropolis.
Metropolis is designed for connecting multiple high-speed cameras or high-speed sensors to
process the streaming data and do AI processing on top of that. Metropolis also comes with
a library of pre-trained state-of-the-art models. These pre-trained models have been
trained with a great deal of data. We also provide Transfer Learning tools to adapt these
models to your use case. This end to end system is what we call NVIDIA EGX. This is a demonstration
of live cameras feeding multiple streams of video, which then goes into a 5G radio emulator,
which turns the live video into 5G packets. The 5G packets comes into the EGX stack, which
runs the 5G Aerial SDK: GPU software baseband radio. Aerial and Metropolis is running on
top of the EGX stack, which is running Kubernetes is running CUDA, AI processing, network processing,
security processing and storage processing -- all completely optimized, running on one
computer. End to end. Let me show you another application of NVIDIA EGX.
This is factory automation. The reference application we developed for this is called Isaac.
It starts with Isaac SIM, a virtual reality environment that obeys the laws of
physics, appears photo realistic. In that world, a robot thinks it's in the physical
real world. We're going to teach it skills, refine its skills. Once the robotics model
is developed, we would run it on the NVIDIA EGX computer, running the Isaac robotics stack.
The Isaac robotics stack includes sensing models, localization, articulation and navigation
models. It receives sensor information streamed over 5G from the fleet of robots. It does
the robotics processing, sensing, reasoning, and action and sends the actuation commands
back over 5G to the fleet of robots, with extremely low latency, which is one of the
features of the 5G protocol. Isaac is end to end from the virtual reality environment
we call Isaac SIM, the robotic stack we call Isaac SDK, the computer NVIDIA EGX, and the
environment for 5G and the robotics stack on top controlling a fleet of robots to automate
factories of the future. Let me show it to you.
Isn't that incredible? Ladies and gentlemen, today I have really exciting news. We've been
working together with one of the world's leaders in building amazing machines.
Ladies and gentlemen, BMW. BMW has chosen NVIDIA to build the factories of the future.
BMW manufacture some of the most amazing machines in the world, and they do it in volume. But
what you don't realize, each one of these cars, they have 40 different models, have
a hundred options every single day. 30 million raw parts comes in from nearly 2000 suppliers.
It goes to 30 factories around the world, and those 30 factories assemble one car every
56 seconds. These 30 million parts comes in, sent over to the workspace just in time for
the craftsmen to assemble those parts into the car.
The empty crate's taken away; a new crate arrives. Each and every step of the way, a
robot will be involved. The splitting, the picking, the placing, the delivery, the picking
up of the empties. This is really a logistics miracle and is one of the great challenges
of automated factoring today. And this is the future. You're going to have a factory
that's going to be designed as a robot: mass production, customization, going hand in hand,
and what makes it possible is artificial intelligence and robotics. I can't be more delighted to
work with all of the great people at BMW in this great challenge to invent the future
of automated factories. As I mentioned, the fusion of IOT and artificial
intelligence is going to create this whole new computing space we call edge AI and the
applications for it will be in so many industries. We've already announced previously that we're
working with Walmart on automated retail. We've also talked about how we're working
with USPS, the world's highest volume, highest speed sorting system, is now powered by NVIDIA EGX.
Today I announced our partnership with BMW to apply EGX, IOT, AI, and robotics technology
to reinvent the future of factories. Well, these industries are large. The number
of sensors around the world is going to be enormous -- trillions of them, collecting
and processing data continuously. The vast majority of the world's data will be created
and AI processing will be done. The NVIDIA EGX stack has so many partners from operating
systems, security processing, network processing, and one of the most important is the 5G stack
and our partnership with Ericsson and Mavenir. In each of the vertical industries are great
partners we're working with to develop applications of specific types of AI and specific skills,
from industrial to medical to robotics to intelligent video analytics.
This is one of the most exciting computing platforms we've built, bringing together NVIDIA's
great AI processing and Mellanox's great network storage and security processing. We've created
a computing platform that has the power of clouds, but could be used and deployed everywhere at the edge.
NVIDIA EGX.