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

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29 Comments

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  • mbucdn - Monday, April 12, 2021 - link

    Why bother having an announcement we have no products on the shelf. This company is wasting time with a keynote speech. Reply
  • mode_13h - Monday, April 12, 2021 - link

    I'm pretty sure the products and services discussed in the talk *are* available, of course with the exception of the explicitly unreleased ones.

    This high-margin stuff is where a lot of the production capacity is going.
    Reply
  • Peskarik - Monday, April 12, 2021 - link

    Unicorn with integrated Unicornlink. Reply
  • jamesindevon - Monday, April 12, 2021 - link

    Just a FYI: the headline reads "The NVIDIA GTC 2021 Keynote Live Blog (Starts at 8:30am PT/16:30 UTC)", but it started at 15:30 UTC. Since UTC doesn't have daylight savings, the conversion was wrong. Reply
  • Ryan Smith - Monday, April 12, 2021 - link

    Oh for the love of Pete...

    Thanks!
    Reply
  • yannigr2 - Monday, April 12, 2021 - link

    "NVIDIA will not stop supporting x86
    Instead they'll support both Arm and x86"

    For now. Nvidia is in it's final face to create a 100% Nvidia ecosystem, something they started with their first Tegra. And they want to finish ARM's acquisition before moving against the X86 platform.
    Reply
  • mode_13h - Monday, April 12, 2021 - link

    I'm sure they'll continue to support x86 as long as it holds a significant marketshare. Reply
  • UltraWide - Monday, April 12, 2021 - link

    CPU + GPU + DPU, they are going hard after the last piece of the data center: Intel's high-margin CPUs. Reply
  • Alistair - Monday, April 12, 2021 - link

    They are not going hard, they basically don't have a product for the next 4 years even... Reply
  • Alistair - Monday, April 12, 2021 - link

    Hey nVidia, the only care you have on the shelf is the GT 1030, less performance than the GTX 750 from 2014 for more money, $100 USD. Start with releasing decent entry level cards and get them on the shelf. GTX is everything that is wrong with nVidia. MONEY MONEY MONEY. You, gamers, pay for nVidia to enter the datacenter and machine learning. There's a lot of opportunity for some company one day to actually focus on making a video card again. Reply

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