1 00:00:01,639 --> 00:00:03,840 Speaker 1: It's been one month since the changing of the guard 2 00:00:03,840 --> 00:00:07,000 Speaker 1: at the top of Amazon Web Services, with Matt Garman 3 00:00:07,160 --> 00:00:10,080 Speaker 1: becoming CEO, and he joins us now for an update 4 00:00:10,119 --> 00:00:12,239 Speaker 1: on how things are going and to lay out his 5 00:00:12,400 --> 00:00:16,920 Speaker 1: vision for AWS, the leader in the cloud market. Missus Garman, 6 00:00:16,960 --> 00:00:19,520 Speaker 1: good morning to you. Let's start with the basics. What 7 00:00:19,560 --> 00:00:22,000 Speaker 1: have you spent the last thirty days or so doing 8 00:00:22,560 --> 00:00:25,240 Speaker 1: and how quickly have you tried to implement changes that 9 00:00:25,280 --> 00:00:28,400 Speaker 1: you think were helpful important AWS? 10 00:00:29,360 --> 00:00:31,040 Speaker 2: Oh, thank you and thanks for having me this morning. 11 00:00:32,240 --> 00:00:35,080 Speaker 2: It's been a great first month. I've been diving into 12 00:00:35,360 --> 00:00:39,680 Speaker 2: various teams and understanding where all the teams are working on. 13 00:00:39,880 --> 00:00:43,199 Speaker 2: In particular, I'm excited about the opportunity in front of us. 14 00:00:43,240 --> 00:00:46,599 Speaker 2: I've spent some time sitting down with customers and understanding 15 00:00:46,600 --> 00:00:49,320 Speaker 2: what's important to them. Spent a bunch of time last 16 00:00:49,320 --> 00:00:51,839 Speaker 2: week in Silicon Valley talking to some small startups to 17 00:00:51,920 --> 00:00:53,960 Speaker 2: understand what's going on in the general of AI space. 18 00:00:54,480 --> 00:00:57,760 Speaker 2: And there's a lot of excitement about new technologies that 19 00:00:57,800 --> 00:01:00,360 Speaker 2: are coming and the potential for where business as go. 20 00:01:00,520 --> 00:01:05,200 Speaker 2: So I'm incredibly excited and looking forward to the business. 21 00:01:06,000 --> 00:01:09,160 Speaker 1: Now we will talk about generative AI. But your background 22 00:01:09,200 --> 00:01:13,000 Speaker 1: is so interesting because you've held pretty long periods of 23 00:01:13,040 --> 00:01:17,840 Speaker 1: both engineering and sales responsibilities in the cloud market at AWS. 24 00:01:18,280 --> 00:01:21,000 Speaker 1: You know, before we were talking about AI, the story 25 00:01:21,040 --> 00:01:24,080 Speaker 1: with cloud was really clear. There was this massive total 26 00:01:24,120 --> 00:01:27,760 Speaker 1: addressable market where companies all around the world had not 27 00:01:27,920 --> 00:01:32,640 Speaker 1: yet transition workloads and storage to the cloud. And increasingly 28 00:01:32,640 --> 00:01:35,160 Speaker 1: we're actually talking about on prem being back a little bit. 29 00:01:35,640 --> 00:01:38,320 Speaker 1: Just talks to me about your strategy for going after 30 00:01:38,400 --> 00:01:41,160 Speaker 1: that addressable market the basics of cloud computing. 31 00:01:42,319 --> 00:01:45,520 Speaker 2: Yeah, the opportunity ahead is really enormous for the business. 32 00:01:45,560 --> 00:01:47,280 Speaker 2: If you look out there and you actually talk to 33 00:01:47,319 --> 00:01:50,400 Speaker 2: most customers, the vast majority of their workloads aren't yet 34 00:01:50,440 --> 00:01:52,960 Speaker 2: in the cloud. Some estimates are only ten to fifteen 35 00:01:53,000 --> 00:01:56,080 Speaker 2: percent of workloads have actually transitioned to the cloud. And 36 00:01:56,120 --> 00:01:59,360 Speaker 2: actually we hear from customers that, if anything, they're looking 37 00:01:59,400 --> 00:02:02,040 Speaker 2: to accelerate that transition to the cloud. If you think 38 00:02:02,080 --> 00:02:05,600 Speaker 2: about genitive at AI or other technologies, most customers are 39 00:02:05,600 --> 00:02:08,000 Speaker 2: finding that it's hard to actually take real advantage of 40 00:02:08,000 --> 00:02:10,080 Speaker 2: some of these new technologies that are out there if 41 00:02:10,120 --> 00:02:12,160 Speaker 2: their data is not out in the cloud. And so 42 00:02:12,600 --> 00:02:15,040 Speaker 2: when we talk to a lot of customers, they see 43 00:02:15,080 --> 00:02:19,240 Speaker 2: this new era of generative AI as a accelerator for reasons, 44 00:02:19,240 --> 00:02:21,000 Speaker 2: to get their data in the cloud, to put it 45 00:02:21,040 --> 00:02:23,240 Speaker 2: in a data lake, and to be organized in a 46 00:02:23,280 --> 00:02:26,640 Speaker 2: secure and safe environment where they can actually go and 47 00:02:26,639 --> 00:02:30,519 Speaker 2: innovate and deliver value for their business. And so we're 48 00:02:30,520 --> 00:02:33,320 Speaker 2: actually seeing this as an accelerator. Actually, when I talk 49 00:02:33,320 --> 00:02:35,440 Speaker 2: to most customers, they're trying to find ways that they 50 00:02:35,480 --> 00:02:38,040 Speaker 2: can migrate more of their workloads and more of their 51 00:02:38,080 --> 00:02:40,320 Speaker 2: data into the cloud faster than they ever have before. 52 00:02:41,000 --> 00:02:43,000 Speaker 2: And so we think that that's a huge opportunity for 53 00:02:43,080 --> 00:02:45,760 Speaker 2: AWS business. But we also think that's a big opportunity 54 00:02:45,760 --> 00:02:49,720 Speaker 2: for our customers as they can gain agility and can 55 00:02:49,760 --> 00:02:52,800 Speaker 2: innovate faster for their own customers once all those workloads 56 00:02:52,840 --> 00:02:54,760 Speaker 2: are in the cloud and they can focus on delivering 57 00:02:54,800 --> 00:02:55,959 Speaker 2: value to their own customers. 58 00:02:56,480 --> 00:03:00,360 Speaker 3: Alphabet and Microsoft and IBM and all that is also 59 00:03:00,440 --> 00:03:03,760 Speaker 3: see this as their opportunity too, Matt, And I'm interested 60 00:03:03,760 --> 00:03:06,160 Speaker 3: as someone who basically helped build cloud as a business 61 00:03:06,160 --> 00:03:08,240 Speaker 3: model back from two thousand and five, when you're intenning 62 00:03:08,360 --> 00:03:11,959 Speaker 3: how you think Amazon and AWS is different at this moment. 63 00:03:13,000 --> 00:03:13,600 Speaker 4: Yeah, you're right. 64 00:03:13,600 --> 00:03:16,400 Speaker 2: So, and as you mentioned, I've been working in AWS 65 00:03:16,400 --> 00:03:18,680 Speaker 2: since two thousand and five, two thousand and six, since 66 00:03:18,680 --> 00:03:21,760 Speaker 2: we started AWS, and so if you look about where 67 00:03:21,760 --> 00:03:24,160 Speaker 2: we're different, there's a couple of things that I would 68 00:03:24,520 --> 00:03:27,240 Speaker 2: focus on. Number one is we have a lot of 69 00:03:27,280 --> 00:03:30,440 Speaker 2: experience going and helping customers in the cloud world. 70 00:03:30,720 --> 00:03:32,280 Speaker 4: And from the very beginning, when. 71 00:03:32,120 --> 00:03:35,760 Speaker 2: We very first started AWS, we said Priority zero for 72 00:03:35,880 --> 00:03:39,240 Speaker 2: us is security. Customers are trusting us with their business, 73 00:03:39,280 --> 00:03:42,520 Speaker 2: they're trusting us with these critical workloads, and so security 74 00:03:42,680 --> 00:03:43,800 Speaker 2: is first and foremost. 75 00:03:44,120 --> 00:03:45,640 Speaker 4: Second is operational excellence. 76 00:03:45,800 --> 00:03:48,360 Speaker 2: And so we know that for our customers, if we 77 00:03:48,440 --> 00:03:50,720 Speaker 2: have to be secure and we have to perform an 78 00:03:50,800 --> 00:03:54,400 Speaker 2: outstanding way, so performance security, those are the two things 79 00:03:54,440 --> 00:03:56,600 Speaker 2: that we focus on. And then we think about how 80 00:03:56,640 --> 00:03:59,160 Speaker 2: do we help customers innovate, And we really like to 81 00:03:59,200 --> 00:04:01,400 Speaker 2: partner with our custom We want to lean in. We 82 00:04:01,440 --> 00:04:04,440 Speaker 2: want to understand where their struggles are, where they're having 83 00:04:04,480 --> 00:04:07,360 Speaker 2: problems with their on prem environments, or where they're slowing 84 00:04:07,400 --> 00:04:10,680 Speaker 2: down because they're doing too much of the muck we 85 00:04:10,760 --> 00:04:13,200 Speaker 2: call it, instead of actually innovating for their customers. And 86 00:04:13,200 --> 00:04:15,120 Speaker 2: then we deliver a really rich set of services. And 87 00:04:15,120 --> 00:04:18,120 Speaker 2: if you go look at AWS, we have by far 88 00:04:18,279 --> 00:04:22,000 Speaker 2: the widest set of services and capabilities that allow customers 89 00:04:22,000 --> 00:04:24,719 Speaker 2: of all sizes, whether they're startups or enterprises or governments, 90 00:04:24,720 --> 00:04:27,240 Speaker 2: to go and innovate out there for customers. And so 91 00:04:27,520 --> 00:04:30,200 Speaker 2: when you have that baseline of security and operational excellence 92 00:04:30,240 --> 00:04:33,279 Speaker 2: and then you have the broadest set of capabilities, it's 93 00:04:33,320 --> 00:04:35,240 Speaker 2: for many customers and most customers out there, it's a 94 00:04:35,240 --> 00:04:38,039 Speaker 2: no brainer as to what's the optimal platform to go from? 95 00:04:38,440 --> 00:04:42,480 Speaker 3: And so, yeah, so is that no brainer? Meaning you're 96 00:04:42,520 --> 00:04:45,640 Speaker 3: still accelerating for AWS growth as we see that pivot 97 00:04:45,680 --> 00:04:48,599 Speaker 3: point in the previous quarter. Are you still accelerating profits too? 98 00:04:49,080 --> 00:04:49,640 Speaker 4: Absolutely? 99 00:04:49,839 --> 00:04:52,600 Speaker 2: AWS is still growing faster than any other cloud provider 100 00:04:52,600 --> 00:04:56,039 Speaker 2: out there on an absolute basis, and we see customers leaning 101 00:04:56,040 --> 00:04:59,159 Speaker 2: in and so we see again this is such early 102 00:04:59,240 --> 00:05:01,440 Speaker 2: days for the cloud. It's really is early days, and 103 00:05:01,480 --> 00:05:04,840 Speaker 2: so we see massive growth and acceleration ahead of us 104 00:05:05,160 --> 00:05:06,839 Speaker 2: and huge opportunity for the business. 105 00:05:08,279 --> 00:05:11,080 Speaker 1: Matt, since you've been in the job for thirty days, 106 00:05:11,360 --> 00:05:14,000 Speaker 1: what's your understanding of what a run rate in the 107 00:05:14,040 --> 00:05:18,200 Speaker 1: billions of dollars tied to generative AI actually meaning what 108 00:05:18,320 --> 00:05:20,640 Speaker 1: have you come to see across your desk? Is that 109 00:05:21,120 --> 00:05:23,760 Speaker 1: being a business of Yeah? 110 00:05:23,839 --> 00:05:27,200 Speaker 2: And as you mentioned, general AI is already a multi 111 00:05:27,200 --> 00:05:29,960 Speaker 2: billion dollar business for AWS, and so it is a 112 00:05:29,960 --> 00:05:31,880 Speaker 2: big business for us today. And when you sit down 113 00:05:31,920 --> 00:05:33,800 Speaker 2: with customers, I think you look at kind of where 114 00:05:33,839 --> 00:05:37,280 Speaker 2: this transition has gone. It started out called a year 115 00:05:37,360 --> 00:05:40,640 Speaker 2: year and a half ago with chat GPT, and everybody 116 00:05:40,680 --> 00:05:43,479 Speaker 2: thought this was a fantastic technology, and it. 117 00:05:43,320 --> 00:05:44,000 Speaker 4: Is and it was. 118 00:05:44,520 --> 00:05:46,360 Speaker 2: And then so the first thing that everybody did is 119 00:05:46,400 --> 00:05:49,400 Speaker 2: they basically built chatbots for their website, right. And so 120 00:05:50,000 --> 00:05:52,800 Speaker 2: as customers, though, are transitioning, they're trying to say, where's 121 00:05:52,839 --> 00:05:55,640 Speaker 2: the real enterprise value for me? How am I delivering 122 00:05:55,720 --> 00:05:58,200 Speaker 2: value to my customers? And so when again when they 123 00:05:58,200 --> 00:06:01,279 Speaker 2: think about AWS, they say, I have a platform that 124 00:06:01,320 --> 00:06:03,719 Speaker 2: I can build on. It's secure at the baseline, it 125 00:06:03,720 --> 00:06:05,840 Speaker 2: has a bunch of capabilities that I can actually go 126 00:06:05,880 --> 00:06:08,520 Speaker 2: and build value for my customers. And so we increasingly 127 00:06:08,560 --> 00:06:10,960 Speaker 2: are seeing customers say, how do they get real value 128 00:06:10,960 --> 00:06:14,200 Speaker 2: for their business? How are they delivering revenue growth? How 129 00:06:14,200 --> 00:06:17,359 Speaker 2: are they delivering real cost savings? How are they completely 130 00:06:17,400 --> 00:06:20,280 Speaker 2: transforming their business? That's just different than how anyone has 131 00:06:20,279 --> 00:06:23,640 Speaker 2: done their industry before. And I think that's the real potential. 132 00:06:23,680 --> 00:06:26,279 Speaker 2: Even though today it is a multi billion dollar business. 133 00:06:26,600 --> 00:06:29,840 Speaker 2: I think it really is the nascent part of this 134 00:06:29,920 --> 00:06:33,960 Speaker 2: technology because it's what it's capable of doing. Is progressing 135 00:06:34,040 --> 00:06:37,160 Speaker 2: so quickly that I think a year two years from 136 00:06:37,200 --> 00:06:39,719 Speaker 2: now you're going to see many industries out there have 137 00:06:39,800 --> 00:06:42,600 Speaker 2: completely changed how they think about work, how they think 138 00:06:42,640 --> 00:06:45,640 Speaker 2: about delivering value to their customers. And it's a super 139 00:06:45,680 --> 00:06:48,919 Speaker 2: exciting time for innovation and for technology as a whole. 140 00:06:49,800 --> 00:06:52,440 Speaker 1: For our Bloomberg television and radio audiences around the world. 141 00:06:52,520 --> 00:06:56,680 Speaker 1: We're speaking with the AWSCO Matt Garman thirty days into 142 00:06:56,720 --> 00:07:02,240 Speaker 1: the job. An important development your predecessor was the anthropic investment, 143 00:07:02,360 --> 00:07:06,040 Speaker 1: most recently the Aqua hier so to speak of a 144 00:07:06,120 --> 00:07:09,240 Speaker 1: debt labs, which is more focused on non AWS at Amazon. 145 00:07:09,640 --> 00:07:11,960 Speaker 1: How much do those deals indicate that Amazons had to 146 00:07:12,000 --> 00:07:15,600 Speaker 1: bring in engineering talent to work on large language models. 147 00:07:17,120 --> 00:07:19,440 Speaker 2: How we think about it is the potential is massive, 148 00:07:19,560 --> 00:07:22,160 Speaker 2: and we think that if you look at the AI space, 149 00:07:22,400 --> 00:07:25,280 Speaker 2: there's not going to be one solution for everyone. There's 150 00:07:25,280 --> 00:07:27,240 Speaker 2: not going to be one model that's perfect for all 151 00:07:27,360 --> 00:07:30,200 Speaker 2: use cases. Our view is that customers are going to 152 00:07:30,240 --> 00:07:33,400 Speaker 2: need a variety of capabilities, They're going to need large 153 00:07:33,440 --> 00:07:36,160 Speaker 2: models to do reasoning. And the anthropic models, by the way, 154 00:07:36,200 --> 00:07:39,800 Speaker 2: are fantastic, and the new claud three point five sonnet 155 00:07:39,840 --> 00:07:42,120 Speaker 2: model is by far the best in the world right now, 156 00:07:42,400 --> 00:07:44,720 Speaker 2: and that's fantastic and we love working with that team. 157 00:07:45,160 --> 00:07:47,440 Speaker 2: But a lot of customers, we find are combining those 158 00:07:47,520 --> 00:07:50,840 Speaker 2: large models with small models, and then they also need capabilities, 159 00:07:50,920 --> 00:07:53,120 Speaker 2: and one of the areas that we're really excited about 160 00:07:53,240 --> 00:07:56,400 Speaker 2: is agentic workloads, where models are actually going to be 161 00:07:56,440 --> 00:07:58,200 Speaker 2: able to call out and do things out there in 162 00:07:58,240 --> 00:08:01,880 Speaker 2: the world, real world, not just summarize data or give 163 00:08:01,920 --> 00:08:05,400 Speaker 2: you information, but actually go and perform actions. And that's 164 00:08:05,440 --> 00:08:09,000 Speaker 2: part of where we're really excited about the technology from ADEPT. 165 00:08:09,080 --> 00:08:10,720 Speaker 4: And so we think that there's a lot of these 166 00:08:10,760 --> 00:08:11,520 Speaker 4: different components. 167 00:08:11,520 --> 00:08:12,960 Speaker 2: Many of them are going to be built in house 168 00:08:13,000 --> 00:08:15,840 Speaker 2: and have been built in house with AWS. Many of 169 00:08:15,880 --> 00:08:19,320 Speaker 2: them come from external capabilities, and we think that there's 170 00:08:19,360 --> 00:08:21,880 Speaker 2: going to be a really rich ecosystem of capabilities that 171 00:08:21,920 --> 00:08:23,480 Speaker 2: customers are going to want to build from. And many 172 00:08:23,520 --> 00:08:25,560 Speaker 2: of them are partners with us, and many of them 173 00:08:25,600 --> 00:08:27,160 Speaker 2: will provide US first party offerings. 174 00:08:27,400 --> 00:08:31,880 Speaker 3: A rich ecosystem needs rich infrastructure and energy. At that map, 175 00:08:32,320 --> 00:08:35,400 Speaker 3: how are you seeing the need for energy growing an aws, 176 00:08:35,440 --> 00:08:36,520 Speaker 3: how are you satisfying it? 177 00:08:36,559 --> 00:08:36,679 Speaker 1: Then? 178 00:08:36,760 --> 00:08:38,520 Speaker 3: Much talk about nuclear for example. 179 00:08:39,760 --> 00:08:42,200 Speaker 2: Yeah, it's a great point, and it does need a 180 00:08:42,200 --> 00:08:46,080 Speaker 2: lot of energy, and that's why if you rewind even 181 00:08:46,120 --> 00:08:49,880 Speaker 2: several years ago, we're the single largest purchaser of renewable 182 00:08:50,000 --> 00:08:52,000 Speaker 2: energy in the world for many years in a row now, 183 00:08:52,720 --> 00:08:54,960 Speaker 2: and part of that is we saw this coming and 184 00:08:55,000 --> 00:08:57,280 Speaker 2: we've been thinking about how do we build up enough 185 00:08:57,320 --> 00:09:01,040 Speaker 2: power in a sustainable way that's carbon neutral that we 186 00:09:01,080 --> 00:09:04,439 Speaker 2: can support the energy needs for technology. 187 00:09:04,480 --> 00:09:04,760 Speaker 4: And so. 188 00:09:06,320 --> 00:09:08,480 Speaker 2: We think that that growth is going to be significant, 189 00:09:08,600 --> 00:09:10,280 Speaker 2: and there's a lot of work that's going to go 190 00:09:10,360 --> 00:09:13,120 Speaker 2: forward in continuing to make sure that we have enough 191 00:09:13,160 --> 00:09:15,920 Speaker 2: power to power the workloads that our customers need. 192 00:09:16,200 --> 00:09:17,079 Speaker 4: But that's part of. 193 00:09:17,000 --> 00:09:18,880 Speaker 2: What I think we bring to the table. We've spent 194 00:09:18,960 --> 00:09:21,199 Speaker 2: a lot of time getting good in this space. We've 195 00:09:21,240 --> 00:09:22,880 Speaker 2: spent a lot of time thinking about how do we 196 00:09:22,880 --> 00:09:25,280 Speaker 2: make sure that we have enough sustainable power, how do 197 00:09:25,320 --> 00:09:27,560 Speaker 2: we make sure that we have enough components in our 198 00:09:27,559 --> 00:09:29,960 Speaker 2: supply chain, and how do we manage that spend. As 199 00:09:30,000 --> 00:09:33,400 Speaker 2: you mentioned, it's a pretty significant infrastructure investment. How do 200 00:09:33,440 --> 00:09:35,600 Speaker 2: we make sure that we manage that in a reasonable way, 201 00:09:35,840 --> 00:09:37,880 Speaker 2: so that it's good for the AWS business and that 202 00:09:37,920 --> 00:09:40,720 Speaker 2: we're being responsible with how much capital we spend. But 203 00:09:40,760 --> 00:09:43,800 Speaker 2: we can also grow the power footprint that the world 204 00:09:43,840 --> 00:09:46,640 Speaker 2: needs in a sustainable way. I think that's an important 205 00:09:46,640 --> 00:09:48,080 Speaker 2: thing of what ABS brings for people. 206 00:09:48,200 --> 00:09:51,520 Speaker 3: Can I ask about therefore that profitability because there has 207 00:09:51,600 --> 00:09:55,480 Speaker 3: been marked improvement in profitability, But the question is at 208 00:09:55,480 --> 00:09:58,240 Speaker 3: the time of investment, are you managing this by cutting 209 00:09:58,280 --> 00:10:01,160 Speaker 3: costs by alsomny having let go of people, You're managing 210 00:10:01,160 --> 00:10:04,440 Speaker 3: to equate it more by just more higher pricing for 211 00:10:04,480 --> 00:10:06,120 Speaker 3: these AI related services. 212 00:10:07,480 --> 00:10:10,000 Speaker 2: Now we think about this business like this business will 213 00:10:10,000 --> 00:10:12,600 Speaker 2: have ebbs and flows over time, particularly as we make 214 00:10:12,720 --> 00:10:15,839 Speaker 2: large financial investments in the future, whether it be large 215 00:10:15,840 --> 00:10:18,840 Speaker 2: investments in power or data centers or components and things 216 00:10:18,880 --> 00:10:21,600 Speaker 2: like that. So the profitability of the business will go 217 00:10:21,679 --> 00:10:23,240 Speaker 2: up and down over time. But long term, we think 218 00:10:23,240 --> 00:10:25,840 Speaker 2: that AWS will continue to be a very profitable business 219 00:10:25,840 --> 00:10:29,240 Speaker 2: for Amazon. But for us, it's all about investing in 220 00:10:29,240 --> 00:10:31,199 Speaker 2: the future and making sure that we have the right team, 221 00:10:31,440 --> 00:10:33,520 Speaker 2: that we have the right setup in place, and we 222 00:10:33,559 --> 00:10:35,360 Speaker 2: have a long term vision of what this business is 223 00:10:35,400 --> 00:10:38,560 Speaker 2: going to be. So we're not thinking about particularly short term, 224 00:10:38,559 --> 00:10:40,920 Speaker 2: but we're thinking about how do we really go after 225 00:10:41,000 --> 00:10:44,160 Speaker 2: that long term potential so that AABS continues to grow 226 00:10:44,200 --> 00:10:46,080 Speaker 2: at a rapid rate for many, many years. And we 227 00:10:46,080 --> 00:10:47,400 Speaker 2: want to make sure that we have that right team 228 00:10:47,440 --> 00:10:49,920 Speaker 2: in place, we have the right infrastructure in place, and 229 00:10:49,960 --> 00:10:51,720 Speaker 2: we have the right investments in place so that we 230 00:10:51,760 --> 00:10:53,840 Speaker 2: can be there for customers when they need us. 231 00:10:54,960 --> 00:10:57,520 Speaker 1: Now, we dedicate a lot of time on this program, 232 00:10:57,559 --> 00:11:03,400 Speaker 1: covering your proprietary silicon efforts Trainium for example, So we've 233 00:11:03,440 --> 00:11:07,160 Speaker 1: done that. Could we focus on Nvidia and in discuss 234 00:11:07,200 --> 00:11:10,080 Speaker 1: with me your relationship with that company, how supply of 235 00:11:10,120 --> 00:11:13,400 Speaker 1: their AI accelerators is, and whether you actually will give 236 00:11:13,440 --> 00:11:16,960 Speaker 1: us a forecast of how many accelerators you think you'll 237 00:11:17,000 --> 00:11:20,160 Speaker 1: take from Nvidia in the next twelve months or calendar 238 00:11:20,200 --> 00:11:20,680 Speaker 1: twenty four. 239 00:11:22,559 --> 00:11:25,360 Speaker 2: It's a great question. And Nvidia is an incredibly important 240 00:11:25,400 --> 00:11:30,160 Speaker 2: partner of ours. They make a fantastic processor, They have 241 00:11:30,280 --> 00:11:33,240 Speaker 2: executed incredibly well and have by far the world's best 242 00:11:33,240 --> 00:11:35,920 Speaker 2: technology in this space and have for the last couple 243 00:11:35,960 --> 00:11:38,920 Speaker 2: of years. And we believe that AI technologies are going 244 00:11:38,960 --> 00:11:42,120 Speaker 2: to rely on Nvidia and GPUs for many years to come, 245 00:11:42,160 --> 00:11:43,920 Speaker 2: and so we think that they're a super important long 246 00:11:44,000 --> 00:11:47,560 Speaker 2: term partner of ours. In fact, we're getting deeper and 247 00:11:47,600 --> 00:11:52,199 Speaker 2: deeper with them. Jensen has said on stage that AWS 248 00:11:52,280 --> 00:11:54,880 Speaker 2: is their technology partner that they're building their own models 249 00:11:54,880 --> 00:11:57,440 Speaker 2: on top of. They believe that, and they've seen that 250 00:11:57,520 --> 00:12:00,640 Speaker 2: AWS has by far the best performing technolog whether it's 251 00:12:00,679 --> 00:12:03,560 Speaker 2: on the network side or the availability of the GPUs, 252 00:12:03,559 --> 00:12:06,400 Speaker 2: which actually is a super important part of building models. 253 00:12:07,120 --> 00:12:09,880 Speaker 2: And so Nvidia trusts AWS to go and build their 254 00:12:09,920 --> 00:12:12,280 Speaker 2: long term models, and we lean in on Nvidia for 255 00:12:12,360 --> 00:12:15,720 Speaker 2: that too and learn about what's working well, what in 256 00:12:15,760 --> 00:12:18,120 Speaker 2: the next generation technology will they need from our data 257 00:12:18,120 --> 00:12:20,959 Speaker 2: centers and networking, And we really have a great collaboration 258 00:12:21,040 --> 00:12:24,040 Speaker 2: there to ensure that our AI customers can jointly take 259 00:12:24,080 --> 00:12:26,760 Speaker 2: advantage of the best technology that Nvidia has to offer 260 00:12:26,880 --> 00:12:29,880 Speaker 2: and AWS has offer in a combination so that they 261 00:12:29,880 --> 00:12:33,040 Speaker 2: can really deliver the best technology for the world. 262 00:12:33,640 --> 00:12:36,599 Speaker 3: Partnerships being built. Matt Common, thank you so much for 263 00:12:36,679 --> 00:12:39,280 Speaker 3: joining us today, awsk you for having mea