And so there you go. Direct from my kitchen, GTC 2020. We talked about a lot of stuff.
Let me quickly summarize.
The first thing we talked about was how accelerated computing is accelerating a momentum
and that we're taking it to the next level to data center scale computing where accelerated
computing and data processing and networking are both vitally important.
I'm delighted that Mellanox and NVIDIA are officially one company.
The second was how real time ray tracing after
all of these years has enabled next generation of computer graphics. An Omniverse could
be created with portals for designers with different tools in different places doing
different parts of the design at the same time. They're able to do that because the
world is interactively lit, it is physically based, it obeys the laws of physics,
and it could be created in real time.
We call that Omniverse and we're shipping it on RTX server.
The third thing we talked about, was NVIDIA AI.
Machine learning is the greatest challenge of HPC today and
machine learning has three basic stages. The data preparation, the training of the model
and the inference, the deployment, the production of the model.
I spoke about the data preparation of the
machine learning pipeline and how the amount of data that is being processed
is going from tens of terabytes to hundreds of terabytes to very, very soon petabytes of data.
The leading compute engine is called Spark.
Spark takes an entire data center and it turns it into a compute engine, partitioning the
data into small chunks that are processed in clusters of computers. After several years
of endeavor today we announced the acceleration of Spark 3.0
NVIDIA now has the entire pipeline of machine learning from data processing to
inference through training, all completely accelerated.
I also spoke about two of the most important machine learning pipelines of the world today.
The recommender system, the machine learning system that predicts user preferences for
billions of people and trillions of items. Collecting an enormous amount of data about
objects, about users, about usage patterns. And by doing so, create a predictive model of your preferences.
We created an application framework called NVIDIA Merlin. That simplifies this enormously
complicated distributed computing, machine learning pipeline recommender systems, NVIDIA Merlin.
We also spoke about conversational AI, recent
Recent breakthroughs in speech recognition, natural language understanding and speech synthesis
has made it possible for us for the very first time to imagine creating an AI model that allows you to have
natural conversations. We created a conversational AI framework that codifies the entire pipeline with
state of the art AI models that are pre-trained and optimized and tuned for performance and
fast response. The entire pipeline can respond in just a couple of two, 300 milliseconds.
As a result, you can have a reasonable conversation, an interactive conversation with an AI agent.
Jarvis is used by enterprises around the world to adapt it to their domain.
Answer healthcare related questions, insurance questions, financial services services questions
It is now possible to retrain Jarvis for your domain.
Conversational AI is now democratized.
And right here from my kitchen, we announced
the shipment of our Ampere GPU and the data center GPU, A100. Ampere is a miracle.
Ampere is the largest, the most complex processor the world has ever made. TSMC 7nm, 54 billion
transistors connected to 1.5 terabytes of HBM2 memory on a 3D package called CoWoS.
This processor goes into DGX 1. As a third generation Tensor Core has a peak throughput
20 times greater than Volta. The most advanced processor in the world today. A100 is 20 times
the peak for training, 20 times the peak for inference of V100. It has a new architecture
called MIG multi-instance GPU. It could be configured as one or seven or something in
between. MIG allows Ampere to be used as scale up for data analytics or training as well
as scale out for public cloud instances or inference. This is our first GPU that has
such incredible throughput and has the ability to configure itself into a large or small GPU.
It's connected also by our next generation NVLink, 600 gigabytes per second, 10 times
the bandwidth of PCI Express Gen4. DGX A100 is the most advanced AI instrument
in the world. It is designed for the entire pipeline of machine learning from data processing
to training to inference. It is the first computer we've ever built that is unified
for all of those workloads. Whether scale up or scale out. The NVIDIA DGX A100 is in
production today has the equivalent performance of 150 high end servers over a million dollars.
DGX A100 is available today for $199,000. The more you buy, the more you save.
We talked about the coming together of IOT, the internet of things and artificial intelligence
creating this brand new opportunity called edge AI. This is the beginning of the smart everything
revolution. There will be trillions of things connected to the internet with intelligent
AI services. You could just imagine the scale of this. You have already heard us announce
in previous keynotes how we're working with Walmart, who is using NVIDIA EGX for smart
retail or USPS using NVIDIA EGX for the highest logistics sorting operations in the world.
Today I announced that BMW has selected NVIDIA and the EGX and the Isaac robotics platform
to create their next generation factories
That was a busy GTC. It is great to have all of you.
I want to thank all of you for partnering with us and particularly recognize all the researchers, scientists,
artists, and designers that take advantage of our platform to invent a future.
One more treat for you. This is something that I'm supremely proud of and NVIDIA is
one of the companies in the world that has assembled a great team of designers, architects,
software programmers, scientists, AI researchers, computational mathematicians, as well as incredible
artists. The fusion of art, engineering, and science all under one roof is one of the things
that really inspires me. I want to share with you the behind the scenes
of the creation of the video, I am AI. I think you're going to love it.
Please enjoy and see you next time.