Q1 2023 NVIDIA Corp Earnings Call

As for future financial results and business. Please refer to the disclosure in today's earnings release, our most recent Form 10-K, and 10-Q and the reports that we may file on form 8-K, with the Securities and Exchange Commission.

All our statements are made as of today May 26, 2022 based on information currently available to us.

Except as required by law, we assume no obligation to update any such statements.

During this call we will discuss non-GAAP financial measures you can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website with that let me turn the call over to Colette.

Thanks, Simona, we delivered a strong quarter driven by record revenue in both data center and gaming with strong fundamentals and execution against a challenging macro backdrop total revenue of $8 3 billion was a record up 8% sequentially and up 46%.

Rent year on year.

Data center has become our largest market and we see continued strong momentum going forward.

Starting with gaming revenue of $3 6 billion rose, 6% sequentially and 31% year on year powered by the <unk> Archie X 30 series product cycle.

Since launching in the fall of 2020, the RPX 30 series has been our best gaming product cycle ever the gaming industry has grown tremendously with 100 million new PC gamers added in the past two years According to news.

And Nvidia RPX has set new standard for the industry with demand from both first time GPU buyers as well as those upgrading their Pcs to experience the 250, plus RPX optimized games and apps doubled from last year.

We estimate that almost a third of the <unk> gaming GPU installed base is now on our TX <unk>, TX has brought tremendous energy into the gaming World and has helped drive a sustained expansion in our higher end platforms and installed base with significant runway still ahead.

Overall end demand remained solid through Doe mixed by region and demand in Americas remained strong. However, we started seeing softness in parts of Europe related to the war and the Ukraine.

And parts of China due to the Covid lockdowns.

We expect some ongoing impact.

As we prepare for a new architectural transition later in the year, we are projecting gaming revenue to decline sequentially in Q2.

Inventory has nearly normalized and we expect it to remain around these levels in Q2.

The extent in which crypto currency mining contributed to gaming demand is difficult for us to quantify with any reasonable degree of precision.

The reduced pace of increase in Ethereum network hash rate likely reflects lower mining activity on Gpus, we expect a diminishing contribution going forward.

Laptop gaming revenue posted strong sequential and year on year growth driven by the ramp of the Nvidia Archie X 30 series lineup with this years spring refresh and ahead of the upcoming back to school season. There are now over 180 laptop models, featuring our TX 30 series G.

<unk> and our energy efficient thin and light <unk> technologies up from 140 at this time last year.

Driving this growth are not just gamers, but also to fast growing category of content creators from whom we offer dedicated in video studio drivers. We've also developed applications and tools to empower artists.

<unk> for advanced breeding and collaboration to broadcast for live streaming to canvas for painting landscapes with AI.

The creator economy is estimated at 100 billion and powered by 80 million individual creators and broadcasters.

We continued to build out our G Force now cloud gaming service gamers can now access our T X 30, 80 cost streaming our new top tier offering where subscription plans of $19 99 a month.

We added over 100 games to the G Force now library, bringing the total to over 1300 games and last week, we launched Fortnite on G Force now with touch controls for mobile devices streaming through the Safari web browser on iOS and the G Force now Android App.

Moving to pro visualization Q.

Q1 revenue was 622 million was down sequentially, 3% and up 67% from a year ago demand remains strong as enterprises continued to build out their employees remote office infrastructure to support hybrid work sequential growth in the mobile workstations.

<unk> Gpus was offset by lower desktop revenue.

Strong year on year growth was supported by the Nvidia RPX Amp peer architecture product cycle top use cases include digital content creation at customers, such as Sony Pictures animation and medical imaging at customers such as Medtronic.

In just its second quarter of general availability, our omni versus enterprise software is being adopted by some of the worlds largest companies Amazon is using <unk> to create digital twins to better optimize warehouse design and flow and to train more intelligent robots.

Kroger is using <unk> to optimize store efficiency with digital twin stores simulation and Pepsico is using omni versus digital twins to improve the efficiency and environmental sustainability of our supply chain on.

Hanmi versus also expanding our GPU sales pipeline driving higher end and multiple GPU configurations.

The omni versus ecosystem continues to rapidly expand with third party developers and the robotics industrial automation through design and rendering ecosystems developing connections to omni versus.

Moving to automotive.

Q1 revenue of $138 million increased 10% sequentially and declined 10% from the year ago quarter.

Our drive Orin Soc is now in production and kicks off a major product cycle with auto customers ramping in Q2 and beyond for.

<unk> has great traction in the marketplace with over 35 customer wins from automakers truck makers and robo taxi companies in.

In Q1, BYD, China's largest EV maker and lucid and an award winning EV pioneer with the latest two announced that they are building their next generation fleets on drive Oren.

Our automotive design win pipeline now exceeds $11 billion over the next six years up from $8 billion, just a year ago.

Moving to data center.

Record revenue of 3.8 billion grew 15% sequentially and accelerated to 83% growth year on year revenue from Hyperscale and cloud computing customers more than doubled year on year, driven by strong demand for both external and internal.

<unk> workloads Custer.

Customers remain supply constrained in their infrastructure needs and continue to add capacity as they tried to keep pace with demand.

Revenue from vertical industries grew a strong double digit percentage from last year top verticals driving growth. This quarter include consumer Internet companies financial services and telecom.

Overall data center growth was driven primarily by strong adoption of our E 100, GPU for both training and inference with large volume deployments by Hyperscale customers and broadening adoption across the vertical industries.

Top workloads include recommended systems conversational AI large language models and cloud graphics.

Networking revenue accelerated on strong broad based demand for our next generation 25, 50, and 100 gig Ethernet adopters customers are choosing and videos networking products further leading performance and robust software functionality.

In addition, networking revenue is benefiting from growing demand for <unk> Super pause and cross selling opportunities customers are increasingly combining our compute and networking products to build what are essentially modern AI factories with data as the raw material input and intelligence.

As the output.

Our networking products are still supply constrained, though we expect continued improvement throughout the rest of the year.

One of the biggest workloads driving adoption of Nvidia AI as natural language processing, which has been revolutionized by transformer based models.

Industry breakthroughs traced to Transformers include large language models like GPT, three Nvidia Mega more Bart for drug discovery and deep mine Alpha fold for a protein structure prediction.

Transformers allow self supervised learning without the need for human labeled data they enable unprecedented levels of accuracy for tasks such as tax generation translation summarization and answering questions to do that transformers views enormous training datasets.

And very large neuron networks well into the hundreds of billions of parameters to run these giant models without sacrificing low inference times customers like Microsoft are increasingly deploying Nvidia AI, including our Nvidia Ampere architecture based Gpus and full software stack.

Jack.

In addition, we are seeing a rising wave of customer innovation using large language models that is driven by increased demand for Nvidia AI and GPU instances in the cloud.

At GTC, we announced our next generation data Center GPU. The H 100 based on the new or upper architecture.

Packed with 80 billion transistors, H 100 is the world's largest most powerful accelerator offering an order of magnitude leap in performance over the 100, we believe <unk> 100 is hitting the market at the perfect time, H 100 is ideal for advance.

<unk> large language models and deep recommended systems, the two largest scale AI workloads today.

We are working with leading server makers in hyperscale customers to qualify and ramp H 100.

Ed as well as the new <unk> H 100, AI computing.

Computing system will ramp in volume late in the calendar year.

Building on the H 100 product cycle go we are on track to launch our first ever data Center CPU Grace in the first half of 2023 graces the ideal CPU for AI factories. This week at Computex, we announced that dozens of server models based on grades.

We brought to market by the first wave of system builders, including <unk> Fox column gigabyte.

UCT supermicro and why when these servers will be powered by the Nvidia <unk> CPU Super Chip, which features two Cpus and the Grace upper Super Chip, which pairs and Nvidia upper GPU with an Nvidia Grace CPU.

Integrated model.

We've introduced new reference designs based on Grace for the massive new workloads of next generation data centers.

T Gx for cloud graphics, and gaming <unk> for digital twins, or omni versus an <unk> for <unk> and AI.

These server designs are all optimized for and videos rich accelerated computing software stacks and can be qualified as part of our Nvidia certified systems lineup.

The enabler for the Grace Hopper and Grace Super chips is our ultra energy efficient low latency high speed memory coherent interconnect called NB link, which scales from die to die chip to chip and system to system within the link we can configure Grace and Hopper.

To address a broad range of workloads.

Future Nvidia chips, the Cpus Gpus, Cpus Nicks, and Soc will integrate and the link just like Greece, and Hopper based on our World class <unk> technology.

We are making and be link open to customers and partners to implement custom chips that connect to Nvidia as platforms.

In networking, we're kicking off a major product cycle with the introduction of spectrum for the World first 400 gigabit per second.

<unk> and Ethernet networking platform, including the spectrum for switch connect <unk> smart neck Bluefield, three GPU the Docker software.

Built for AI Nvidia spectrum for Orion as data centers are growing exponentially and demanding extreme performance advanced security and powerful features to enable high performance advanced virtualization and simulation at scale.

Across our businesses, we are launching multiple new GPU, CPU, GPU and S. Oc products over the coming quarters.

With a ramp in supply to support the customer demand.

Moving to the rest of the P&L GAAP gross margin for the first quarter was 65, 5% and non-GAAP gross margin was up 67, 1% up 90 basis points from a year ago and up 10 basis points sequentially.

We have been able to offset rising costs and supply chain pressures, we expect to maintain gross margins at current levels in Q2.

Forward as new products ramp and software becomes a larger percent of revenue we have opportunities to increase gross margins longer term.

GAAP operating margin was 22, 5% impacted by a 1.3 dollars $5 billion acquisition termination charge related to the arm transaction.

non-GAAP operating margin was 47, 7% we are closely managing our operating expenses to balance the current macro environment with our growth opportunities and we've been very successful in hiring so far this year and are now slowing to integrate these new employees.

This also enables us to focus our budget on taking care of our existing employees as inflation persists.

We are still on track to grow our non-GAAP operating expenses in the high 20 range. This year, we expect sequential increases to level off after Q2 as the first half of the year includes a significant amount of expenses related to the bring up of multiple new products, which should not reoccur in the second half.

During Q1.

We repurchased $2 billion of our stock our board of directors increased and extended our share repurchase program to repurchase an additional common stock up to a total of $15 billion through December 2023.

Let me now turn to the outlook for the second quarter of fiscal 2023, our outlook assumes an estimated impact of approximately 500 million relating to Russia, and China Covid Lockdowns we.

We estimate the impact of lower sell through in Russia, and China to affect our Q2 gaming sell in by $400 million.

Furthermore, we estimate the absence of sales to Russia to have a $100 million impact on Q2 in data center.

We expect strong sequential growth in data center and automotive to be more than offset by the sequential decline in gaming.

Revenue is expected to be $8 1 billion, plus or minus 2% GAAP and non-GAAP gross margins are expected to be 65, 1% and 67, 1%, respectively, plus or minus 50 basis points.

GAAP operating expenses are expected to be $2 $4 6 billion non-GAAP operating expenses are expected to be $1 75 billion.

GAAP and non-GAAP other income and expenses are expected to be an expense of approximately $40 million, excluding gains and losses on non affiliated investments.

GAAP and non-GAAP tax rates are expected to be 12, 5% plus or minus 1% excluding discrete items.

And capital expenditures are expected to be approximately 400 million to $450 million.

Further financial details are included in the CFO commentary and other information available on our IR website.

In closing, let me highlight the upcoming events for the financial community, we'll be attending the Bofa Securities Technology Conference in person on June seven where Jenson will participate in a keynote fireside chat.

Our earnings call to discuss the results of our second quarter of fiscal 2023 is scheduled for Wednesday August 24, we will now open the call for questions. Operator could you. Please poll for questions. Thank you. Thank.

At this time I would like to remind everyone in order to ask a question Press Star then the number one on your telephone keypad. We ask that you. Please limit yourself to one question, we'll pause for just a moment to compile the Q&A roster.

We will take our first question from C. J Muse with Evercore ISI. Your line is open.

Yes, good afternoon, and thank you for taking the question I guess would love to get an update on how youre thinking about the gaming cycle from year businesses essentially doubled over the last few years and now we've got some crosswords with crypto falling off channel potentially clearing ahead of a new product cycle.

Talked about macro challenges.

But at the same time only a third of the installed base.

RPX.

And we're moving out from under supply so we'd love to hear your thoughts from here once we get beyond got it.

The challenges around Covid lockdown in the July quarter, how are you thinking about gaming trends.

Yeah C J thanks for the question.

You captured a lot of the dynamics well in your question.

The underlying dynamics of the gaming industry is really solid.

Net of net of the two.

The situation with Covid Lockdown in China and Russia.

The rest of the market is fairly robust and we.

We expect and we expect the gaming dynamics too to be intact.

So simple things that are driving the gaming industry in the last two years alone 100 million new gamers came into the PC industry.

The format has expanded tremendously.

And.

The ways that people are using their Pcs to two.

Connect with friends.

Two.

To be an influencer as a platform for themselves use it for broadcast.

<unk>.

So many people are now using their <unk> as their second workstation, if you will second studio.

Because they're they're also working from home.

It is our primary way of communicating these days.

<unk>.

Need for.

G Force Pcs have never been greater and so I think the fundamental dynamics are really good.

We looked into look into the second half of the year, we look it's hard to predict exactly.

When.

Covid.

The war in Russia is going to go into them.

Be behind Us.

But nonetheless, the governing dynamics with the gaming industries group.

Next we'll go to Matt Ramsey with Cowen.

Your line is open.

Thank you very much good afternoon.

Jensen I wanted to ask you a bit of a question on the on the data center business.

This upcoming cycle with <unk>.

<unk> hundred Theres. Some io upgrades that are happening in servers that I think are going to be a fairly strong driver for you. In addition to what's going on with Hopper and the huge performance leaps that are there.

I wanted to ask a longer question term question, though around your move to NV link with Grace and Hopper and what's going on with your whole portfolio do you envision the business continuing to be sort of car driven attached to third party servers or do you think revenue shifts dramatically or in a small way over time to be more.

Sort of vertically integrated all of the chips together on endy latent and how is the industry sort of responding to that potential move thanks.

Yes, I appreciate the question.

Let's see the first point that you made is a very big point. The next generation of servers that are being teed up right now or old Gen. Five.

The Io performance is substantially higher than what was available before.

So youre going to see a pretty large refresh as a result of that.

Brand, new networking cards from from our company and others.

Gen five.

Of course drives new platform refresh and so so we're we're a perfectly time too.

Ramp into the Gen five generation with with Hopper.

There are a lot of different system configurations, you want to make.

If you.

Take a step back and look at the.

The type of systems that are necessary for data processing scientific computing.

Machine learning and training inference.

Done in the cloud for Hyperscale nature done on Prim for enterprise computing done at the edge each one of these.

Workloads and deploy.

Deployment locations.

Way that you manage would dictate.

A different system architecture. So there isn't a one size that fits all which is one of the one of the reasons why it's so terrific that we support PCI Express.

That we innovated chip to chip interconnect.

Diverse.

Before anybody else did this is Nelson <unk> seven years ago, when our fourth generation of <unk> link.

That allows us to connect two chips next to each other to dyes two chips two modules.

Two.

<unk> <unk> modules to two systems to multiple systems.

So our our coherent shifted shouldn't link <unk> link has made it possible for us to mix and match.

<unk> dies packages systems and all of these different types of configurations, and and I think that over time youre going to see even more types of configurations.

And the reason for that has to do with with a couple of very important new type of data centers that are emerging in your store.

Youre starting to see that now with <unk>.

Fairly large installations infrastructures with Nvidia.

<unk> and Nvidia AI.

These are really AI factories, where you are processing the data refining the data and turning the data into intelligence. These.

These AI factories are essentially running one major workload and theyre running at 24 seven.

Deep recommended systems is a good example of that in the future you're going to see large language models, essentially becoming a platform themselves that would be running 24, seven hosting a whole bunch of applications.

And then on the other end Youre seeing.

Data centers at the edge that are going to be robotics autonomous.

Data centers that are running 24, 7% they were going to be running in factories in retail stores and warehouses logistics warehouses.

All of the World. So these two new type of data centers or.

We're just emerging and they also have different architecture. So I think the net of it all is that the our ability to support.

Every single workload, because we have a universal accelerator.

Work.

Every single workload from data processing to a data analytics to high performance computing to trying to influence that we can support arm and <unk> six so we support PCI Express two.

<unk> multi system NV linked to multi chip NB linked to multi die and be link.

That capability for us is.

It makes it makes it possible for us to really be able to serve all of these different segments.

With respect to with respect to.

Vertical integration I think that the system integration the better way of saying that is the system integration is going to come in all kinds of different ways.

We're going to do semi custom chips as we've done with.

Many companies in the past, including Nintendo.

We will do semi custom.

Triplets as we do with MB link.

<unk> is open to our partners.

And they could bring to any fab.

And connected coherently and toward chip, we could do multi.

Module packages, we could do multi package systems.

So theres a lot of different ways to do system integration.

Next we'll go to Stacy <unk> with Bernstein Research. Your line is now open.

Hi, guys. Thanks for taking my question I wanted to follow up on the sequential so collect I know you said on the $500 million was a 400 million hit to gaming.

And a $100 million hit the data center I'm, assuming that that doesn't mean, the gaming is down $400 million gaming PC gaming actually down more.

Then the actual Russia and locked down yet.

And I guess, just how do I think about the relative sequential of the businesses.

In light of those constraints that you guys are facing.

Sure Let me, let me start first with <unk>.

What does that mean to gaming what does that mean to gaming for Q2, we do expect gaming to decline into Q2, we still believe our end demand remains very strong and peer has just been a great architecture and there's many areas, where we continue to see strength and growth.

In both our sell through and probably what we will see added into that channel as well, but in total Q2 gaming will decline from last quarter from Q1.

It will probably decline in the teens.

As we try and work through some of these lockdowns in China, which are which are holding us up.

So overall the <unk> the.

The demand.

For gaming is still strong we still expect.

And demand to grow year over year in Q2.

Next we'll go to Mark <unk> with Jefferies. Your line is open.

Hi, Thanks for taking my question.

If you listen to if you listen to the networking Oems This earnings season, it seems that.

There was a lot of talk about increased spending.

By enterprises on their data centers.

And sometimes you hear them talking about how this is being driven by AI, Utah.

You talked about your that your year over year growth in your cloud versus <unk>.

Enterprise spending I Wonder if you could talk about what you were seeing sequentially are you seeing in sequential inflection in the enterprise and and can you talk about the the attach rate of software for enterprise versus data centers, and what which which.

Software is is it are you seeing the most interest I know you've talked about is it <unk> is it natural language processing or.

Is there one big driver a bunch of drivers for the various different software packages you have thank you.

Yeah. Thanks, Thanks, Mark we had a record.

<unk>.

Data center business this last quarter.

We expect to have a record another record quarter.

This quarter.

Yeah.

And we're fairly enthusiastic about the second half.

The AI AI and data driven machine learning techniques for writing software and extracting insights from the vast vast amount of data that companies have.

As is incredibly strategic to all the companies that we know because of the final analysis AI is about automation of intelligence and most companies are about domain specific intelligence, we want to produce intelligence.

And there are several techniques that have been created to make it possible for most companies to apply their data too.

To extract insight and to automate a lot of the predictive things that they have to do and do it quickly.

And so I think the.

<unk>.

The trend the you hear other people experiencing about machine learning data analytics data driven data driven insights artificial intelligence harvests describes all exactly the same thing.

And its sweeping and sweeping just about every industry and every company.

Our our.

Our networking business is.

It is also highly highly supply constrained and where demand is really really high.

And it requires a lot of components aside from just our chips components, and transceivers and connectors and cables.

Just it's a really it's a complicated system.

The network and there are many physical components.

So.

So the supply chain has been problematic, we're doing our best and our.

Our supply has been increasing from Q4 to Q1, we're expecting it to increase in Q2, an increase in Q3 Q4 and so so we're.

We're really really grateful for the support from the.

The component industry around us.

And we will be able to increase that with respect to software.

There are two there are two.

First of all there are all kinds of machine learning models computer vision speech AI natural language understanding.

All because robotics applications the most the most.

Notably the largest the most visible one is self driving cars, which is essentially a robotic.

Hi.

And.

And then recently this incredible breakthrough.

From a.

Our motor called Transformers that has led to two really really significant advances in natural language understanding and so theyre. All of these different types of models that there are thousands and thousands of species of.

AI models.

And used in all these different industries.

One of my favorite I will just say very quickly, though I answered. The question about the software one of my favorites is using transformers to understand the language of chemistry.

We're using transformers and using AI models to understand the language of proteins amino acids, which is we're just genomics.

To apply AI to understand to recognize the patterns to understand the sequence and essentially understand the language of chemistry, and biology is really really important breakthrough and all of this all of this this excitement around synthetic biology.

Much of it stems back to some.

Some of these inventions.

But anyhow all of these different models need an engine to run on.

And that engine is called Nvidia AI in the case of in the case of Hyperscale. There's they can cobble together a lot of open source and we provide a lot of our source to them in a lot of our engines to them for them to operate their AI, but for enterprises, they need someone to package it together and be able to supported and refresh it.

Updated for new architecture support old architectures, and their installed base et cetera, all the different use cases that they have and so that engine is called Nvidia AI, it's almost like a sequel engine if you will.

Except as an engine for artificial intelligence Theres another engine that we provide and the.

The engine is called <unk> and it's designed for the next wave.

<unk> AI.

Artificial intelligence has too.

Not just manipulate.

Information like recommend our systems and conversational systems as such but it has to interact with physical systems, whether it's indirectly with physics directly mini robotics or.

Being able to automate physical systems like heat recovery steam generators, which is really important today.

And so so.

<unk> is designed to be able to sit at the interface the intersection between <unk>.

Stimulation and artificial intelligence and this went under versus about <unk> is now let's.

Let's see so some we're still early in the deployment of <unk> for for commercial license.

A couple of quarters analysis, we've released the omnibus.

Enterprise.

And I think at this point, we have 10.

Percent of the world's top 100 companies that are already customers licensing customers.

Substantially more who are evaluating I think has been downloaded nearly 200000 times.

It is being tried in some 700 companies.

<unk> highlighted some of the companies you might see some of the companies that are using.

Using it in all kinds of interesting applications.

<unk> and so so I fully expect that the Nvidia AI engine.

The omnibus engine are going to be very successful for us in the future and contribute greatly to our earnings.

Next we'll go to Vivek Arya with Bofa Securities. Your line is open.

Alright, Thanks, just wanted to.

Clarify collect at your Q2 outlook include any destocking benefits from the new products that you're planning to launch this year and then.

And so my question is for you Youre still guiding data center to a very strong I think close to 70% or so year on year growth. Despite all the headwinds are you worried at all about all the headlines about the slowdown in the macro economy.

Is there any cyclical impact on data center growth that we should keep in mind as we think about the second half of the year.

Yes, let me first answer the question that you asked regarding.

Any new products as we look at Q2.

As we discuss about it most of the ramp that we have of our new architectures, we're going to see in the back half of the year, we're going to start to see for example, hopper will probably be here in Q3, but starting to ramp closer to the end of the calendar year.

So you should think about most of our product launches to be.

Ramping in the second half of the year.

On that I'll turn it over for Jensen for the rest.

<unk>.

Our data center demand is strong and remains strong.

Our hyperscale and cloud computing revenues as you mentioned.

It's grown significantly has doubled year over year, and we're seeing really strong adoption of a 100 <unk> hundred is really quite special and unique in the world of accelerators and so this is one of the really really great innovations as we extended our GPU from graphics to cuda.

Two tensor core Gpus, it's now a universal accelerator and so you could use it for data processing for Etfs for example, extract transform load you could you could use it for data database acceleration many sequel functions or accelerated on Nvidia Gpus, we accelerate rapids.

We accelerate which is the Python version dataset.

Datacenter scale Bridget pandas, we accelerate.

Spark three no.

And.

And so from database queries to data processing too.

Extraction and transform and loading of data before you do training and inference.

And whatever image processing or other algorithmic processing unit can be fully accelerated 100, and so we're seeing great success there.

Foundation.

Core in <unk>.

Closer to what is happening today.

Youre seeing several different <unk>.

<unk> important new AI models that are being invested in a very very large scale and with great urgency.

You probably have heard about deep recommend or systems. This is the economic engine. The information filtering engine of the Internet if not for the recommended system it would be practically.

Impossible for us to enjoy our internet.

Internet experience shopping experience with trillions of things that are changing in the world every day.

Constantly and be able to use your three inch phone too.

Two to even engage the internet and so all of that magic is made possible by this incredible thing called a recommended system. The second thing is conversational AI youre seeing chat bots and website customer service, even live customer service being now supported by AI conversational AI has an opera.

IIT to enhance the customer service on the one hand on the other hand supplement for a lot of labor shortage and then the third is this groundbreaking piece of work is related to transformers that led to.

Natural language understanding breakthrough, but but within it.

It was incredible thing called large language models.

Which embeds human knowledge.

Because it's been trained and so much data and we recently announced <unk> hundred 50 <unk>.

<unk>.

It was a collaboration we did with Microsoft.

Foundation.

They call it touring.

And this language model and others like it like <unk> three.

Are really transformative they take and the new.

Ms amount of computation. However, the net result is a pretreat model that is really quite remarkable.

We're working with thousands of startups.

Large companies that are building.

We're using the public cloud and so it's driving a lot of demand for us in the public cloud.

I think we have now 10000, AI inception startups that are working with us.

Using Nvidia AI.

Whether it's on prem or in the cloud.

It saves money.

Because the computation time has significantly reduced the quality of services a lot better than they could they could do greater things.

So thats driving AI and the cloud and so all of these all of these different factors, whether whether it's just the.

Real recognition of the importance of AI.

The transformative nature of these new AI models.

Rick mentor systems, largely which models conversation really on the <unk>.

<unk> of companies around the world that are using Nvidia AI in the cloud driving public cloud demand work all of these things are driving our datacenter growth. So we expect to see data center demand remains true.

Next we'll go to Tim Arcuri with UBS. Your line is open.

Thank you very much.

I have a question about this $500 million impact for July and whether it's more supply related or demand.

Related and Thats because most.

Others in Chinese or sort of setting this charter stuff in particular is more of a logistics issue. So more of a supply issue, but the language you were using in your commentary you cited lower sell through in gaming and sort of the absence of sales in Russia to me that sounds a little more demand.

Which would make sense in the context of this new.

Free zone.

The hiring that you have so I asked because if its supplier related then you could argue that's not perishable I'd really just timing, but if demand related that.

That might never come back and it's and it could be the beginning of a falling knife. So I'm wondering if you can sort of walk through that for me. Thanks.

Well thanks, Tim for the question, let me try and bet here on the China and Russia, two very different things. The current China Lockdowns that we are seeing interestingly has implications to both supply and demand.

We have seen challenges in terms of the logistics throughout the country things going in and out of the country. It puts a lot of pressure.

And just logistics that were already under pressure from a demand perspective. It has also been hedged from the gaming side you have a very large cities other than full lockdown focusing really on other important things for.

The citizens there so it's impacting our demand we do believe that they will come out of Covid and the.

The demand for our products will come back.

Do believe that will occur the supply will sort it out it's very difficult to determine how now in the case of Russia, we're not selling to Russia.

Something that we had announced earlier last quarter, but there were plans in Russia has been a part of our overall company revenue I'll, probably about 2% of our company revenue historically and a little larger percentage when you look at our gaming business hope that helped.

Next we'll go to embrace <unk> with BMO. Your line is now open.

Hi, Thank you very much for that 10, Jensen and actually really appreciated that you'd call out demand for most chip companies. It seems like it's Harris.

To say the demand is a problem so refreshing to hear that.

I had a question on the second half and as it relates to both.

Data center as well as gaming. So last couple of times you have talked publicly you have made comments that your visibility into the data center has never been better. So I was wondering if you. If you just take out the rest of the impact is that still true on the orders that you had been getting intact and unit.

I'd say that business.

She has strong momentum I just wanted to make sure that statement of confidence you have made stays in them.

On gaming collected we expect second half to be up year over year, just based on the guide for second quarter. It seems like it could be up sequentially, but may not return to unit growth.

Thank you.

Yes <unk>. Thanks.

Thanks for your question.

On first principles.

This should be the case that our visibility of data centers is vastly better.

Vastly better than a couple of years ago.

And the reason for that is several one if you recall a couple of two three years ago.

Deep learning and AI was.

<unk> four is starting to accelerate.

In the most computer science deep companies in the world with CSP and Hyperscale.

And and but just about everywhere else it was still quite decent.

And there was a couple of reasons for that obviously the understanding of the technology is.

Not as not as not as pervasive at the time.

This is the type of industrial use cases for artificial intelligence requires.

Hi.

Labeling of data, that's that's really quite difficult and then now with Transformers, you have unsupervised learning and other techniques zero short learning that allows us to to do all kinds of interesting things without having to have human labeled data, we even have synthetic generated the data with <unk> that helps customers.

Do data generation without having to label data, which is which is either two cost effect to constantly.

Quite frankly oftentimes impossible.

And and so so now the knowledge and the.

The technology has evolved to a place that most of the industries could use artificial intelligence.

Intelligence at a very fairly effective way and in many industries.

Either transformative.

So I think number one.

We went from clouds is hyperscale or two all of industry second we went from trading focused to inference.

Most people thought that <unk> was going to be easy it turns out the differences by Florida harder and the reason for that is because theres. So many different models and theres. So many different use cases in so many quality of service requirements and you want to run these inference models in a smaller footprint as you can and so.

When you scale out the number of users that use the service is really quite high so using acceleration and using a video platform. We could influence any model from computer vision to speech to chemistry to biology, you name it.

And.

And we do it so quickly and so fast.

The cost is very low.

And so the more the more acceleration you do the more money you will save and I think that wisdom is absolutely true and so so the second second dimension is training to inference.

The third dimension is that that we now have so many different types of configurations of systems that we can go from from.

High performance computing systems, all the way to cloud to on Prem to edge and then and then.

And then.

The final the final concept is really this.

Industrial deployment now of AI, that's causing us to be able to.

Just about every industry fund growth and so.

As you know are our.

Cloud and Hyperscale <unk>.

Yes.

Our growing very very quickly however, the vertical part vertical industries, which is.

The financial services, and retail and telco and all of those all of those all of those vertical industries have also grown very very nicely and so and all of those different dimensions, our visibility should be a lot better and then and then starting a couple of years ago.

Adding the <unk> portfolio to our company, we're able to provide a lot more solution oriented end to end platform solutions.

For companies that don't have the skills and don't have the technical depth.

To be able to stand up these sophisticated systems and so our networking business is growing very very nicely as well.

Next we'll go to Harlan sur with Jpmorgan. Your line is open.

Hi, good afternoon, thanks for that.

I ask the question.

Maybe just asked this question a little bit more directly so it's good to see the team being able to drive.

Navigate the dynamic supply chain environment right you had strong sequential.

Sequential growth in data center in April here.

In the July quarter, even with some of the net impact from Russia, right and so as we think about the second half of the year cloud spending is strong and it's actually I think accelerating youre.

We're getting ready to ramp each 100 later in the year.

No not really I think is getting more.

Supply as you move through the year and in General I think previously you guys were anticipating sequential supply and revenue growth for the business.

Through this entire year I understand the uncertainty around game.

Does the team expect continued sequential growth in data center through the remainder of the year.

But.

Either one of US the answer is yes.

The answer is yes, we will.

We see we see.

Strong demand in data center.

Hyperscale to cloud computing to vertical industries.

And Pierre is going to continue to scale out it's been qualified in every single company in the world and so so after two years. It remains the best Universal accelerator on the planet.

And.

And it's going to continue to scale out.

In all these different different different domains in different markets.

Where we're going to layer on top of that a brand new architecture Hopper layer on top of that brand new networking.

Architectures.

Quantum three CX seven Bluefield III.

And.

And we have increasing supply and so so.

We're looking forward to it.

Excellent quarter next quarter again for four for data centers.

Going into the second half.

Next we'll go to Chris Caso with Raymond James Your line is open.

Yes. Thank you.

Wondering if you could speak a little bit about the purchase obligations, which seem like they were up again in the quarter.

And how that.

Yeah.

Our function of.

Longer dated obligations or a higher magnitude of obligations and maybe you could just speak to supply constraints in general you've mentioned a couple of times on the call.

Continued constraints in networking business, what about the other parts of the business where are you still constrained.

Okay.

Yes, So let me start here on the <unk>.

<unk> wants to add more of that.

Our purchase obligations as well as our prepaid have two major things to keep in mind one for the first time ever we are prepaying to make sure that we have that supply in those commitments long term and additionally on our purchase obligations many of them are for.

Long lead time items.

That are a must for us to procure to make sure that we have for the products coming to market a good percentage of our purchase commitments is for our data center business, which you can imagine are much larger system is much more complex systems and those things that we are preparing to make sure we can feed the demand.

Both in the upcoming quarters and further.

Areas in terms of where we are still a little bit supply constrained our networking our demand is quite strong we've been improving at a time, but yes, we still have demand exceeding supply.

<unk> with network and stone there are others that you want to add on Johnson.

No I thought you were perfect.

That's perfect.

Our final question comes from Aaron Rakers with Wells Fargo. Your line is open.

Yes, Thanks for fitting me in most of my questions around gaming and data center have been answered, but I guess I'll ask about the auto segment, while it is still small.

Clearly you guys felt confident in that business starting to see quote unquote significant sequential growth into this next quarter I wondered if you could help us kind of think about the trajectory of that business over the next couple of quarters and I think in the past you've said that that should start to really inflect higher.

As we move into the second half of the year. Just curious if you could help us think about that piece of the business.

Several data points.

We are just starting we have just started shipping in the first quarter of shipping production Oren.

<unk> is a robotics processor is designed for a software defined robotic car or robotic.

Picking placer or robotic.

Mover logistics mover.

We've been designed into 35.

Car and trucks and robo taxi companies.

And more others. If you include.

Logistics movers in la.

Last mile delivery systems and farming equipment in.

The number of design wins for <unk> is really quite fantastic worn as a revolutionary processor.

It's a it's designed as a if you will a data center on a chip.

It is the first data center on a chip that is robotic.

Processes sensor information.

Safe.

The ability to be rather resilient.

It is confidential computing.

<unk> is designed to be secure.

And to be all of those things.

Because these data centers are going to be everywhere and so <unk> is really a technological marvels and production.

We probably experienced very likely the the lowest.

So quarter in some time for some time and the reason for that is because over the next six years or so we have $11 billion and counting of.

The business that we've secured.

Estimated.

And.

So I think I think.

It's a fairly safe.

Thing to say now.

Oren.

Our economists vehicle and robotics business is going to be our next multibillion dollar business. It's on its way surely there.

The.

Robotics autonomous systems, and autonomous machines, whether they move we're not move but.

AI systems that are that are at the physical edge.

Surely going to be the next major computing segment. It is surely going to be the next measure datacenter segment.

Been working in this area as you know for a decade.

A fair amount of expertise in this area.

Oren is just one example of our work here, we are four pillars to our strategy for autonomous systems.

Starting from the data processing and the AI training part of it too.

To train robotics robotics AI.

Second to stimulate robotics, AI, which is diverse third too.

The memory of the robotics, AI, otherwise known as mapping and and then finally.

The actual robotics application in the robotics processor in the system and Thats, where foreign goes but orange is just one of our four pillars of our robotics strategy in the next wave of AI and so so.

Really optimistic and really enthusiastic about the next phase of <unk>.

The computer industry growth and I think a lot of it is going to be at the edge of a lot of it is going to be about robotics.

Thank you I'll now turn it back over to Jensen Huang for any additional closing remarks.

Thanks to everyone the full impact and duration of the war in Ukraine, and Covid Lockdowns in China.

It's difficult to predict.

However, the impact of our technology and our market opportunities remain unchanged.

The effectiveness of deep learning AI continues to astound.

<unk> former model.

Which led to the natural language understanding breakthroughs has been advanced to learn patterns with great spatial sequential and temporal complexity.

Researchers are creating transfer models that are revolutionizing applications from robotics to drug discovery.

The effectiveness of deep learning AI is driving companies across industries to adopt Nvidia for AI computing.

We're focused on four major initiatives.

First ramping our next generation of AI infrastructure chips and platforms Hopper GPU Bluefield GPU.

NV link Infiniband quantum Infiniband spectrum Ethernet networking.

And all of this to help customers build their AI factories and take advantage of new AI breakthroughs like Transformers.

Second <unk>.

Wrapping our system and software industry partners to launch Grace our first CPU.

Third.

Ramping Orient.

Our new robotics processor, and nearly 40 customers building cars Robo taxis trucks delivery robots logistics robots farm using robots to medical instruments.

And fourth with our software platforms.

Adding new value to our ecosystem with Nvidia AI and video <unk> and.

And expanding into new markets with new Cuda acceleration libraries.

These initiatives will greatly advance AI.

And while continuing to extend this most impactful technology of our time to scientists in every field and companies in every industry.

We look forward to updating you on our progress next quarter. Thank you.

This concludes today's conference call you may now disconnect.

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