11:27AM EDT - Thank you for joining us for another year of the NVIDIA GTC keynote live blog

11:28AM EDT - Whether physical or virtual, GTC is inevitab...ly a lot of news in a short period of time

11:29AM EDT - NVIDIA's revenues have doubled over less than half a decade, and with that so has the number of business they're in

11:29AM EDT - Graphics, AI, automotive, HPC, and most recently networking

11:30AM EDT - So it's a lot for CEO Jensen Huang to go over in (ideally) less than 2 hours

11:30AM EDT - This year will be no exception. With a whole year to prepare, NVIDIA is firing on all cylinders ahead of the show

11:30AM EDT - And here we go

11:32AM EDT - With the virtual show, this year's keynote is pre-recorded. So it should keep a tight pace. Still, according to YouTube, we're looking at a 1 hour and 48 minute recording

11:33AM EDT - Rolling the intro video. "I am AI"

11:33AM EDT - And here's Jensen

11:34AM EDT - Starting right off the bat talking about AI

11:34AM EDT - "AI and 5G are the ingrediants to kickstart the 4th industrial revolution"

11:35AM EDT - Jensen's talk will be in 4 stacks: graphics and omniverse, data center AI and server hardware, edge AI and EGX 5G, and automotive/DRIVE

11:37AM EDT - "With just a GeForce, every student can have a supercomputer"

11:38AM EDT - Now recapping some of the things that NVIDIA's clients have been doing with their hardware

11:38AM EDT - By headcount, NVIDIA is primarily a software company (seriously), and there is no shortage of major computer science researchers set to give talks at this year's show

11:39AM EDT - "Let's start where NVIDIA started: computer graphics"

11:40AM EDT - Recapping last year's introduction of second-generation RTX (Ampere) hardware

11:40AM EDT - Now rolling some video of some recently-released games and future games in development

11:42AM EDT - Suffice it to say, game graphical quality has only continued to get better over the years

11:42AM EDT - And NVIDIA wants ray tracing to push that further

11:42AM EDT - But games aren't everything. NVIDIA is also focused on productivity use of graphics

11:42AM EDT - NVIDIA's Omniverse technology

11:43AM EDT - Which was first announced a couple of years back, and went into beta testing late last year

11:43AM EDT - Omniverse is essentially a shared group simulation and graphics software package

11:44AM EDT - Omniverse is server-hosted, and any RTX client can plug in to see it. Or even resort to streaming for those devices that can't render it locally

11:46AM EDT - In other words, shared collaboration and design within a single 3D project. All with an emphasis on high quality physics and rendering

11:47AM EDT - One particular focus of Omniverse is "digital twins"; creating a virtual copy of a real-world project/location

11:48AM EDT - This is one of NVIDIA's big pulls for its traditional professional graphics clients, especially in the movie and TV production industry

11:48AM EDT - But also robotics, R&D, and pretty much any other use case you can think of where a shared, real-time interface to a model might be useful

11:49AM EDT - (Oh good, someone remembered the teapot. It's not graphics without a Utah teapot!)

11:50AM EDT - NVIDIA's Isaac robotics platform can interface with Omniverse as well

11:50AM EDT - Which among other things, can be used to train robots using a digital twin of a factory within Omniverse

11:51AM EDT - NVIDIA has even created a digital twin of a BMW factory

11:52AM EDT - BMW is using this as part of their planning processes

11:53AM EDT - Discussing an example of using the model to optimize an assembly line for productivity and safety by quickly adjusting the line and relocating various tools/stations

11:53AM EDT - BMW is also deploying logistics robots that are using isaac

11:55AM EDT - It all looks impressive. Though I am curious what the required investment is with respect to art. Someone has to create all of these models, items, and their surface textures

11:56AM EDT - Omniverse connector SDKs from major software packages are available now, with more on the way

11:56AM EDT - Omniverse will be available for commercial use this summer under enterprise licensing

11:56AM EDT - Now on to data centers

11:57AM EDT - Currently discussing virtualization, and the impact of doing it on CPUs

11:58AM EDT - GPUs generate a lot of cross-datacenter traffic. Deep learning added even more to that

11:58AM EDT - And thus NVIDIA's networking processors, the Data Processing Unit (DPU)

11:59AM EDT - The Bluefield family of DPUs was inherited from Mellanox, and now a core part of NVIDIA's offerings

12:00PM EDT - Bluefield is designed to offload a major part of network functions, including all the processing that goes with them, such as SSL and security analysis

12:00PM EDT - Today NVIDIA is announcing Bluefield 3

12:00PM EDT - 400Gbps network processor with 22 billion transistors

12:01PM EDT - And NVIDIA is already working on Bluefield 4 for 2024, which will be around 64B transistors, and incorporate NVIDIA's AI acceleration technology

12:01PM EDT - "Software will be written by software running on AI computers"

12:02PM EDT - Now segueing into NVIDIA's DGX server hardware

12:03PM EDT - DGX A100 series ranges from a workstation-like DGX Station box, up through DGX A100 servers and DGX SuperPods comprised of many A100 servers

12:03PM EDT - Announcing the DGX Station 320G

12:04PM EDT - 2.5 PFLOPS, 320GB of VRAM, and all in 1500W

12:04PM EDT - This is essentially the most powerful box NVIDIA can build that can safely be plugged into a standard North American 115V/15A circuit

12:05PM EDT - (PANAMAX for workstations, if you will)

12:05PM EDT - NVIDIA is also updating the DGX SuperPod

12:06PM EDT - The latest generation SuperPod has added Bluefield 2 DPUs

12:06PM EDT - The 80GB A100, first announced last year, is also an option

12:06PM EDT - Pricing starts at 7 million dollars and scales to 60 million depending on the size of the system

12:06PM EDT - Now on to the next subject: transformers

12:07PM EDT - Natural language transformer machine learning models

12:07PM EDT - "We expect to see multi-trillion parameter models by next year"

12:08PM EDT - Transformer models are growing quickly. The bigger the model, generally the better and more nuanced the results

12:08PM EDT - So NVIDIA has developed their own transformer technology: Megatorn

12:09PM EDT - Announcing the Megatron Triton DGX server

12:09PM EDT - Able to repond to up to 16 simultaneous queries in an instant

12:10PM EDT - Now on to NVIDIA's Clara library of machine learning models and technology for medical research

12:10PM EDT - NVIDIA is adding 4 new models to the Clara Discovery library

12:12PM EDT - Among other tasks, one of the new models can be used to recognize DNA sequences

12:12PM EDT - Meanwhile, Jensen is also pitching NVIDIA's hardware and software for drug discovery

12:13PM EDT - And if that's not enough, how about quantum physics simulations running on GPUs? IBM's doing it

12:14PM EDT - Er, excuse me, quantum computing, not quantum physics

12:15PM EDT - NVIDIA is announcing a new software package, cuQuantum, to help research and simulate quantum computers

12:15PM EDT - cuQuantum is optimized to run on NVIDIA's DGX hardware

12:16PM EDT - Jensen wants cuQuantum to do what cuDNN did for deep learning

12:16PM EDT - Now on to data center server architectures

12:17PM EDT - "Processing large amounts of data remains a challenge for computers today"

12:18PM EDT - Discussing the current architecture of GPU server boxes like NVIDIA's DGX: 4 GPUs hooked up to a single CPU via PCI Express

12:18PM EDT - PCI Express is the bottleneck

12:18PM EDT - NVIDIA has NVLink, but no x86 CPU has NVLink

12:18PM EDT - So NVIDIA is making their own data center CPU: Grace

12:18PM EDT - Named after Grace Hopper

12:19PM EDT - Grace is an Arm-based CPU, specialized in hosting NVIDIA's GPUs for bandwidth and AI throughput reasons

12:20PM EDT - "Amazing increase in system and memory bandwidth"

12:20PM EDT - And we're now deconstructing Jensen's kitchen...

12:20PM EDT - Grace in the artist-envisioned flesh

12:21PM EDT - NVIDIA has already lined up a customer for Grace: CSCS, who is building their Alps supercomputer

12:21PM EDT - Set to come online in 2023

12:21PM EDT - NVIDIA is now a CPU, GPU, and DPU company

12:22PM EDT - Each chip architecture will have a 2 year rhythm, with likely a kicker in-between

12:22PM EDT - NVIDIA will not stop supporting x86

12:22PM EDT - Instead they'll support both Arm and x86

12:24PM EDT - Speaking of Arm, NVIDIA is developing an Arm SDK, in a partnership with Ampere (the company)

12:24PM EDT - And jumping subjects again, this time to edge AI

12:27PM EDT - Recapping NVIDIA's various AI libraries and toolkits

12:27PM EDT - Which NVIDIA simply calls "NVIDIA AI"

12:27PM EDT - From PCs and laptops to workstations and supercomputers

12:28PM EDT - But one segment of the market that NVIDIA has not focused on up until now has been enterprise computing

12:28PM EDT - So NVIDIA is announcing their EGX enterprise platform

12:28PM EDT - NVIDIA AI runs on VMware

12:29PM EDT - So NVIDIA AI is available within virtualized environments

12:29PM EDT - "The missing link is 5G"

12:30PM EDT - NVIDIA is putting together another new hardware platform, which they are calling the Aerial A100

12:30PM EDT - An A100 GPU and Bluefield 2 processor on a single PCIe card

12:30PM EDT - For use in 5G basestations

12:30PM EDT - Software defined, with acceleration of PHY, crypto, packet processing, and more

12:31PM EDT - Which will be offered as part of an EGX edge server package

12:32PM EDT - Announcing NVIDIA Morpheus: a data center security product

12:32PM EDT - This is another DPU-centric product

12:32PM EDT - Now rolling an informational video about how NVIDIA is using Morpheus in-house

12:33PM EDT - Morpheus flags when it encounters unencrypted data

12:33PM EDT - Relying on AI, rather than specific pattern matching

12:35PM EDT - And recapping NVIDIA's enterprise hardware offerings, backed by EGX servers

12:36PM EDT - Now on to graphics-related AI projects like DLSS and variouos GANs

12:37PM EDT - NVIDIA sees the next wave of AI including increasingly plug-and-play use of the technology

12:37PM EDT - To that end, NVIDIA is adding even more pre-trained models to their collection for customers

12:38PM EDT - Announcing NVIDIA Tao framework

12:38PM EDT - And NVIDIA fleet commmand for securely controlling AI edge servers

12:39PM EDT - Now rolling a video about a customer using NVIDIA's Tao and Fleet Command products

12:40PM EDT - Starting with a pre-trained model, and then using Tao to re-train the model to better accomodate the specific job site

12:40PM EDT - All of the models are trained in minutes

12:40PM EDT - And the updated models are deployed via Fleet Command

12:41PM EDT - Pick a pre-trained model from NGC, optimize it with Tao, and then deploy it via Fleet Command

12:41PM EDT - Now on to conversational AIs

12:42PM EDT - NVIDIA's Jarvis package is now available for production use

12:42PM EDT - Jarvis has 90% recognition accuracy out of the box

12:42PM EDT - 5 languages supported today

12:43PM EDT - "No more mechanical talk"

12:43PM EDT - Jensen is focusing on the edge use cases for Jarvis, and where it could be run

12:44PM EDT - And NVIDIA is partnering with Mozilla to collect voice samples to better train Jarvis and other future voice AI systems

12:44PM EDT - "I have no idea what I said, but Jarvis recognized it perfectly"

12:45PM EDT - And showing Jarvis doing English to Japanese translations (voice to text to text)

12:45PM EDT - And configurable voice options, including intensity and enthusiasm

12:46PM EDT - Now on to recommender systems

12:46PM EDT - (We're moving at a breakneck pace here. NVIDIA has a lot of subjects to get through)

12:46PM EDT - Announcing NVIDIA Merlin, NVIDIA's end-to-end accelerated recommender system

12:47PM EDT - (A recommender system is exactly what it sounds like: a system that attempts to figure out what a user would prefer, and thus what they should be recommended)

12:47PM EDT - And on to NVIDIA Maxine, NVIDIA's video conferencing technology suites

12:48PM EDT - Which incorporates Jarvis voice recognition and translation

12:48PM EDT - Also showing off an eye contact faker/correcter

12:49PM EDT - A lot of people are videoconferencing these days, to say the least. So NVIDIA is keen on lining up customers in that market with tools to improve the experience

12:49PM EDT - Announcing NVIDIA Triton inference server

12:50PM EDT - Triton schedules models on to hardware. Any model and framework on to the appropriate hardware

12:51PM EDT - And a quick look at biomedical molecule simulations using Triton

12:52PM EDT - And now on to talking about what customers have been doing with NVIDIA's AI technologies

12:52PM EDT - Best Buy, Spotify, T-Mobile, and more

12:53PM EDT - And now on to automotive and DRIVE AV

12:53PM EDT - "AV computing demand is skyrocketing"

12:54PM EDT - Automakers still need more computing power

12:54PM EDT - Recapping NVIDIA's Orin SoC, which is set to arrive next year

12:56PM EDT - And the possibility of using a single Orin system as a central computer for everything within a car. From autonomous driving to dashes and infotainment, all execution segregated

12:56PM EDT - And NVIDIA's next-generation SoC past Orin is already in development

12:56PM EDT - DRIVE Atlan

12:56PM EDT - 1000 TOPS on a single chip

12:57PM EDT - Newly incorporating NVIDIA's AI and DPU technologies on top of the many other existing hardware features

12:57PM EDT - Due in 2025

12:58PM EDT - Now talking about NVIDIA's increasing number of major automotive customers, and what they're doing with NV's tech

12:58PM EDT - The big one, of course: robo taxis

12:59PM EDT - Driverless trucks, anyone?

12:59PM EDT - And now we're reaching the end, and Jensen is looping back to Omniverse

12:59PM EDT - Running NVIDIA DRIVE simulations within Omniverse

12:59PM EDT - And digital twin opportunities

01:00PM EDT - NVIDIA's Drive Sim engine will be available to Omniverse users

01:00PM EDT - Now rolling a video

01:01PM EDT - Showing Drive Sim in action, inside and outside of a simulated car

01:02PM EDT - And now on to the recap

01:03PM EDT - Omniverse

01:03PM EDT - DGX systems and Grace CPUs

01:03PM EDT - Jarvis, Merlin, and edge AI

01:04PM EDT - NVIDIA Tao, Fleet Command, and Triton

01:04PM EDT - And Drive, Orin, and the new Atlan SoC

01:05PM EDT - And that's a wrap. Thanks again for joining us