The Six Five Team discusses Google Cloud Next 2023.
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Transcript:
Patrick Moorhead: Google Cloud Next 2023. And Dan, as you know, I like to call my own number-
Daniel Newman: You do. You are selfish.
Patrick Moorhead: … when I’m hosting it, and let’s dive in. So as you would expect, Google Cloud Next 2023, the primary volume knob was set to generative AI. And this has essentially been the norm since November when Microsoft and OpenAI got together, boards, board edicts on, hey, what is our generative AI offering? What is our story? And everybody has been in pandemonium since then. Analysts love pandemonium because people are looking for our feedback in a big way, and they’re looking for not only the enterprises, but also the technology companies, markets. Everybody wants to know.
I mean, we’ve seen stocks go up $100 billion, stocks go down $200 billion. But hey, Google Cloud Next. So Google, their cloud business has really picked up steam over the last couple of years ever since TK joined, and he was very clear that, Hey, we’re going to meet customers where they are in their journey as opposed to asking them to go through different hoops or rev their software every year like the consumer side of Google has. But this year did not disappoint on generative AI.
And Dan, I think it’s fair that we gave Microsoft the early lead because they had done public previews open before anybody else, and I have to give Google credit here where Duet AI, which is essentially the generative AI agent, is GA for Google Workspace and I believe for Google Cloud. And I think that is a big deal and what a turnaround. And I think you and I were both universally in agreement that this is not a sprint, it’s a marathon, and being first with GA or being first with Preview or being first with this, and that is great for kind of chest thumping, but it doesn’t necessarily determine who in the end is going to win.
Now, Microsoft does have a massive business lead over Google Cloud right now, but what I find fascinating is that at least, again, probably every 10 days I talk to an enterprise and invariably they tell me, “Hey, Google Cloud is not our primary cloud provider, but we’re using them for some sort of analytics or AI capability,” and I think that Google has the ability to pick up market share here if you fundamentally believe that generative AI is the new basis for applications to come out. This is Google Cloud’s big play here, and I was super impressive to see that they went GA.
I still have a little bit of research to do because what I have found, at least on the workspace side, is that GA doesn’t necessarily mean it’s going to show up immediately. In fact, I waited a year to get Threads into Gchat after it supposedly went GA. Again, I need to get my facts straight on that, but my backend is workspace. My front end is primarily Microsoft, so my team is chomping at the bit to be able to press one button and convert that document into a presentation and that presentation into a document. And that is a killer app if you ask me. Some of the stuff that went on in the background were new C instances. We saw two new instances. One is AMD fourth gen, which is in preview, and then we saw Amphere with the AmpereOne that is an upcoming preview, I think it said previewing next month. And that adds to Intel’s fourth gen Xeon that is generally available.
One thing that I need to really drill down on is the TPU. I had people, probably some Google people hitting me up on social media telling me that the TPU Google does 90% of their training on the TPU. And by the way, every year I go and ask, “Hey, what percent of workloads are done on TPU?” And it has never been higher than 20%. And I think the difference here is, and again I do the double click on this, Google consumer, the ads business, search uses the TPU a lot for the type of things that do primarily for machine learning and deep learning. There was a nice chart out of the archive that was shared, and I’ll put this in the show notes that puts that out. I don’t get the feeling that the TPU is used a lot in Google Cloud, otherwise I think that Google would be doing a much bigger job to promote it.
On the other hand, I was told this week that the TPU is sold out, so I’m trying to get my hands around this. I think that this matters to me because first of all, Nvidia is selling H100s with supposedly 1,000% gross margins, if like AWS does with Trainium and Inferentia, you can move a lot of your customers to your own custom silicon where you don’t have to make merely 1,000% gross margins, right? You can make 100% gross margins and keep a good business, you’re going to keep a lot more profit for yourself. And you could also, if you want to do the cost mode to get market share, you could go down that angle as well. Microsoft, on the other hand, with Azure doesn’t have a custom GPU, an inference or for training, and I think that’s going to become an issue for them over time if they don’t figure that out.
Back to the C instances, I cannot wait to see the performance that AmpereOne brings out. Google does not do comparisons to Intel, at least publicly. And it’s funny, it was AMD versus AMD. It was Amphere versus Amphere, and it was TPU versus TPU. So a lot of work to do, a lot of research to do. It was a very professionally run analyst track that they did. It was great to spend time with Thomas Kurian.
As I’ve said before, one of my biggest research methodologies personally is to better understand senior leadership. And if I don’t meet with senior leadership and get a good feeling about what the future looks like, I have to talk about that. I did get a good feeling from Thomas on growth in my conversation with him, and this is not NDA or proprietary, so I feel like I can share this. He was very surprised at how many customers were coming to him with very specific asks and to see if generative AI can help with those. I think it’s a really good sign for the industry. I think it’s a really good sign for Google.
Daniel Newman: Yeah, good analysis there. I’m going to macro this thing, because that’s what I do best. First of all, Google Cloud has found itself in a moment, and this is the moment where we’ve seen a shift away from traditional compute where other cloud providers have had tremendous strength to AI focused compute, where Google, not exactly like an Nvidia, but similarly, has been built for a very long time. Remember, Google is brain, Google is DeepMind.
Google has been doing recommendations and generative, by the way, if you’ve been using workspace for any period of time, there was this little generative feature that Google has been doing for a long time where it would complete your sentences. I know that until November of last year when a large language model was deployed and made public and people were using ChatGPT, no one knew that, but that was a generative capability right there, generative text.
So this wasn’t brand new. The company had been developing Bard and Palm for a long time. It did it in secret. It didn’t come to market. It was pushed into coming to market. It fell on its face severely in its initial come to market. But I actually think, as I say to my children all the time, it’s not about the mistakes, it’s how you come back from them. And so it made a big mistake. It raced to compete. And you mentioned something when you were talking about the race for GA. and in some cases being GA and being first isn’t as important as you’d think.
It’s interesting now because kind of seeing how this is trading in market, Microsoft came out with an open AI or ChatGPT powered search, and there was this very bullish sort of sentiment about market share, and it didn’t at least so far amount to very much. And by the way, on the other end of things, Google has raced out with its early to GA duet capability, and they have what? About 10 million workspace users? Which is, it’s palpable.
Patrick Moorhead: Paid.
Daniel Newman: Paid.
Patrick Moorhead: Student, yeah, real paid.
Daniel Newman: Good call. But what I’m saying is that’s a pretty small fraction to the number of paid Office users. And the reason I point that out is we’ll see if putting the ability to generate your emails, write your documents, create your PowerPoints, moves the needle of people off of Microsoft or if we’re just trading early GA. But I was impressed by the fact that Google did get this into market first. And yes, we also use workspace as part of our backend, and I don’t have it yet, so I don’t know what GA means, but it’s not DA, meaning Dan available at this point yet. So if you all could make that happen, feel me. Feel me, I’d like to play with this a little bit.
Other things that really caught my mind, because you covered a lot of ground, Pat. One was the strength that Google has for the longer tail based upon its winning ways with generative unicorns. Now, you and I had a chance to be part of a small group and some private interactions with Thomas and the non-NDA part of it was we talked to him, I asked him a question, why are they winning? And I thought he did a very good job of being able to explain why 70% apparently of gen AI unicorns are building on Google. Now, he wasn’t declarative whether or not they’re using exclusively Google, which was something I want to know, but of course I don’t think anyone in his shoes would’ve answered that question, but we can’t help but ask, right? That’s our job.
But what he basically did say is one, the economics of Google are very good, meaning the economics have enabled startups to very efficiently deploy their AI projects. Two, the Vertex environment, powerful software, highly capable. And then the third thing he really focused on was Google’s impressive developer ecosystem. Now, I think other companies could make that same argument as well, but you do need to repeat that number, Pat. 70% of the unicorns, meaning billion dollar valuation plus companies building gen AI tools, technologies, and software are using Google Cloud. So a very impressive number. And I’ll end my thoughts here as we did talk to … Pat, you talked about talking to enterprises.
I won’t say whom we talked to, but we did talk to a large financial data institution and we did get some interesting feedback. At least it was interesting to me because of how we’re hybrid cloud people. And it was very interesting to talk to a large data company that’s dealt with major security issues in the past to find out that they are all-in on cloud. So there is a story to be told, that some big companies absolutely hook, line and sinker, maybe it’s multicloud, but by the idea that their entire enterprise can be run all in the public cloud path. And I thought that was kind of an interesting way to end our event talking to a customer, hearing that, because you and I still struggle, I think, to see how that can be done based upon the complexity of data and infrastructure environments inside of an enterprise.
Patrick Moorhead: Yeah, this company had a burning platform and that they were hacked big time and were looking for answers, but it was interesting. Great analysis, Dan. Just the final boomerang that I wanted to add here was people forget that albeit Google Cloud is the number three or number four cloud provider, and I think Thomas said what? It’s a top five software firm. If you look at revenue with a little hint that he might move forward there, they have the largest infrastructure on the planet of any company out there, bigger than Microsoft, bigger than AWS. But they don’t only talk about that, because they don’t want to potentially scare people off given their consumer capabilities.
I think the time’s over, I think they need to come out and start leveraging that and flexing their planet scale infrastructure out there. Maybe being a little bit more forceful with talking about the TPU.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
