1 00:00:02,480 --> 00:00:07,000 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:07,760 --> 00:00:10,280 Speaker 2: Hey, our Bloomberg Tech team is there on the ground 3 00:00:10,280 --> 00:00:13,880 Speaker 2: at the annual Consumer Tech summit known as CEES. Right now, 4 00:00:13,960 --> 00:00:17,760 Speaker 2: Bloomberg Tech co host Caroline Hyde sitting down with Christiano Amman, 5 00:00:18,000 --> 00:00:19,520 Speaker 2: CEO and President of Qualcom. 6 00:00:19,520 --> 00:00:25,240 Speaker 1: Caroline, take it away, Carol, thank you. It is a 7 00:00:25,239 --> 00:00:28,080 Speaker 1: party vibe out here at CES and a man who 8 00:00:28,120 --> 00:00:31,000 Speaker 1: knows all about music from his hometown in Brazil, you'll 9 00:00:31,000 --> 00:00:33,000 Speaker 1: be able to cope with the noise level, Christiano. But 10 00:00:33,400 --> 00:00:36,760 Speaker 1: you're part of not the noise, but the statements being 11 00:00:36,800 --> 00:00:39,120 Speaker 1: made here at the moment robotics, when it comes to 12 00:00:39,120 --> 00:00:41,960 Speaker 1: a future of autonomous driving, when it comes to physical AI, 13 00:00:42,600 --> 00:00:45,240 Speaker 1: talk to us about robots. Where's your technology really leading 14 00:00:45,240 --> 00:00:45,839 Speaker 1: the charge there? 15 00:00:45,960 --> 00:00:49,280 Speaker 3: Yes, Look, we're incredibly excited about this is a new chapter. 16 00:00:49,640 --> 00:00:52,760 Speaker 3: I think of the Qualcom expansion and diversification. I think 17 00:00:52,760 --> 00:00:56,720 Speaker 3: we're going to robotics. We like robotics a lot because, 18 00:00:56,880 --> 00:01:01,360 Speaker 3: by definition, is an EDGEAI problem to solve, not different 19 00:01:01,400 --> 00:01:04,200 Speaker 3: than what we did in automotive. You cannot put a 20 00:01:04,240 --> 00:01:06,800 Speaker 3: server in a robot. You need battery life, you need 21 00:01:06,800 --> 00:01:10,120 Speaker 3: a lot of integration, a sensors and physical AI is 22 00:01:10,160 --> 00:01:14,600 Speaker 3: a massive opportunity and it's an EDGAI opportunity. So as 23 00:01:14,640 --> 00:01:17,480 Speaker 3: we look at this transition of qualcom into new industry, 24 00:01:17,520 --> 00:01:21,400 Speaker 3: we went to automotive to PC to industrial to data center. 25 00:01:21,680 --> 00:01:25,160 Speaker 3: Now robotics this is next opportunity. We actually have a 26 00:01:25,240 --> 00:01:29,920 Speaker 3: number of robots here at our booth at CS demonstrating 27 00:01:30,280 --> 00:01:36,160 Speaker 3: training humanoids industrial. I think we started the year working 28 00:01:36,200 --> 00:01:39,480 Speaker 3: with some of the you know, great companies German, Kuka, 29 00:01:39,600 --> 00:01:42,160 Speaker 3: figure AI, and I think it's going to be a 30 00:01:42,200 --> 00:01:47,160 Speaker 3: great opportunity and robotics it's perfect for you to have 31 00:01:47,560 --> 00:01:51,200 Speaker 3: high performance computing and low power connectivity is an edge 32 00:01:51,320 --> 00:01:54,200 Speaker 3: AI problem and I think it's going to be the 33 00:01:54,240 --> 00:01:56,440 Speaker 3: next big wave of AI physical. 34 00:01:56,080 --> 00:01:58,800 Speaker 1: AI and how soon is that reality? Already we have 35 00:01:59,280 --> 00:02:02,920 Speaker 1: robots in manufacturing and industrials, but how soon is it 36 00:02:02,960 --> 00:02:05,200 Speaker 1: fully autonomous robots? How soon do we start to have 37 00:02:05,240 --> 00:02:06,840 Speaker 1: the humanoid versions in our houses. 38 00:02:07,040 --> 00:02:10,840 Speaker 3: Look the way we think about this is things that 39 00:02:10,880 --> 00:02:13,880 Speaker 3: you didn't well possible to do with a robot, you 40 00:02:13,960 --> 00:02:16,520 Speaker 3: can do it right now use an AI. I think 41 00:02:16,680 --> 00:02:20,560 Speaker 3: industrial robot is the big largest opportunity that we see 42 00:02:20,600 --> 00:02:23,400 Speaker 3: in front of us, and it's probably started as early 43 00:02:23,560 --> 00:02:28,720 Speaker 3: as twenty twenty six. When you use AI to train 44 00:02:28,760 --> 00:02:33,640 Speaker 3: a robot on one given task, it's a very well 45 00:02:33,680 --> 00:02:36,040 Speaker 3: defined problem, and you can do this and you put 46 00:02:36,080 --> 00:02:39,639 Speaker 3: into production consumer robot, the one that is going to 47 00:02:39,680 --> 00:02:41,200 Speaker 3: be in your house and do everything for you. It's 48 00:02:41,200 --> 00:02:43,240 Speaker 3: gonna take a little bit of time, but it's going 49 00:02:43,280 --> 00:02:45,400 Speaker 3: to happen, and it's going to be a big opportunity. 50 00:02:45,440 --> 00:02:48,040 Speaker 3: I like to do this parallel that we saw with automotive. 51 00:02:48,560 --> 00:02:52,560 Speaker 3: When we start talking about autonomous cars, a lot of 52 00:02:52,600 --> 00:02:54,480 Speaker 3: companies went in and said, we're just going to get 53 00:02:54,480 --> 00:02:58,520 Speaker 3: this full autonomou robotaxing. But until you get there, you 54 00:02:58,600 --> 00:03:01,639 Speaker 3: can do assisted riving to every car in the road, 55 00:03:01,960 --> 00:03:04,000 Speaker 3: assuming that the driver is there to pick it up. 56 00:03:04,000 --> 00:03:08,880 Speaker 3: And we've seen Adas level two, Level three Highway Highway autopilot. 57 00:03:08,919 --> 00:03:12,079 Speaker 3: That's what we're doing. I think the same parallel applies 58 00:03:12,080 --> 00:03:15,639 Speaker 3: to robotics. First, you have a lot of enterprise in 59 00:03:15,680 --> 00:03:19,079 Speaker 3: the industrial applications. We see companies, for example, in retail 60 00:03:19,440 --> 00:03:22,200 Speaker 3: at night, robot go to the aisles of the supermarket 61 00:03:22,280 --> 00:03:26,760 Speaker 3: and restart the shelves, something very simple. That opportunity is 62 00:03:26,800 --> 00:03:29,800 Speaker 3: happening right now. Over time, we're going to have the 63 00:03:29,840 --> 00:03:31,720 Speaker 3: domestic robot that will do everything for you. 64 00:03:31,840 --> 00:03:34,720 Speaker 1: Okay, let's go to your car focus though, because your 65 00:03:34,800 --> 00:03:37,880 Speaker 1: DNA is mobile. But then it has indeed gone to robotics. 66 00:03:37,880 --> 00:03:40,640 Speaker 1: But also this is where you've dominated. Look, we've just 67 00:03:40,720 --> 00:03:42,920 Speaker 1: had Jenson Wim on stage saying, hey, I'm getting into 68 00:03:42,920 --> 00:03:45,880 Speaker 1: the world of autonomous driving platforms too. How do you 69 00:03:45,920 --> 00:03:48,320 Speaker 1: see that ecosystem involving Okay. 70 00:03:48,440 --> 00:03:52,640 Speaker 3: The most important thing is to really understand what's happening car. 71 00:03:52,760 --> 00:03:58,560 Speaker 3: Car becomes a digital product. So from Qualcom we're going 72 00:03:58,640 --> 00:04:01,120 Speaker 3: to have a slightly different perspect We think that the 73 00:04:01,160 --> 00:04:04,600 Speaker 3: most important part of the car digital experience is the 74 00:04:04,640 --> 00:04:09,080 Speaker 3: digital cockpit, because the digital cockpit became a new computing surface. 75 00:04:09,360 --> 00:04:11,840 Speaker 3: Like your phone is a computing surface, the laptops a 76 00:04:11,840 --> 00:04:14,560 Speaker 3: computing service. Now the car and when you think about 77 00:04:14,640 --> 00:04:19,880 Speaker 3: AI coming into the car agentic experiences, that is very natural. 78 00:04:19,960 --> 00:04:22,400 Speaker 3: Voice is very natural. That's going to happen to the 79 00:04:22,400 --> 00:04:26,240 Speaker 3: cockpit today. I think we're just announced we have now 80 00:04:26,320 --> 00:04:29,120 Speaker 3: seventy five million cars now in the road with the 81 00:04:29,200 --> 00:04:33,760 Speaker 3: call on digital cockpit. Our pipeline is transforming into revenue 82 00:04:33,800 --> 00:04:37,640 Speaker 3: and we're designed in with virtually every car company using 83 00:04:37,640 --> 00:04:43,120 Speaker 3: the digital cockpit. The next car is what's happening in autonomy. 84 00:04:43,640 --> 00:04:48,760 Speaker 3: And in autonomy you have this transition you can bring 85 00:04:49,080 --> 00:04:53,719 Speaker 3: to bring safety and reduce accidents. You can bring assistem 86 00:04:53,760 --> 00:04:57,240 Speaker 3: driving to every car starting with level two all the 87 00:04:57,279 --> 00:04:59,640 Speaker 3: way up, and then you're going to have full autonomy. 88 00:05:00,120 --> 00:05:05,120 Speaker 3: So we have been actually driving the processor for this 89 00:05:05,240 --> 00:05:07,720 Speaker 3: assisted driving, and now with a stack that we develop 90 00:05:07,760 --> 00:05:12,200 Speaker 3: with bmwe launch it's available. People are testing the car 91 00:05:12,320 --> 00:05:15,320 Speaker 3: here at CES and he's available to every OEM to 92 00:05:15,400 --> 00:05:18,800 Speaker 3: have assisted driving in every car, every car model, and 93 00:05:18,880 --> 00:05:22,119 Speaker 3: eventually you're going to get in a couple of years 94 00:05:22,160 --> 00:05:26,080 Speaker 3: to our fully autonomous cars. Yes, I think Tesla is 95 00:05:26,080 --> 00:05:30,280 Speaker 3: probably ahead. I will say the other solutions a couple 96 00:05:30,360 --> 00:05:32,360 Speaker 3: of years out, but you're going to get to it. 97 00:05:32,400 --> 00:05:35,720 Speaker 3: I think fully autonomous cars, but you're going to have 98 00:05:36,240 --> 00:05:38,880 Speaker 3: out some level of autonomy in every single car. 99 00:05:39,120 --> 00:05:41,880 Speaker 1: And you talk about Tesla being ahead, like you know, 100 00:05:41,960 --> 00:05:44,800 Speaker 1: Moscus said he's not losing sleep over Jensenwan coming after 101 00:05:44,839 --> 00:05:46,479 Speaker 1: that piece of the pie. And of course they have 102 00:05:46,880 --> 00:05:50,680 Speaker 1: a client relationship to who can win and how many 103 00:05:50,680 --> 00:05:51,479 Speaker 1: players can win. 104 00:05:52,640 --> 00:05:55,880 Speaker 3: Look, there's gonna be different types of car ownership. Some 105 00:05:55,880 --> 00:05:58,640 Speaker 3: people wanted to drive the car. Some people wanted to 106 00:05:58,680 --> 00:06:02,000 Speaker 3: have an assisted driving, people want to not own a car, 107 00:06:02,080 --> 00:06:05,760 Speaker 3: some people want to robotex It's a it's a big opportunity. 108 00:06:05,800 --> 00:06:08,480 Speaker 3: I think there's going to be multiple players that are 109 00:06:08,480 --> 00:06:13,200 Speaker 3: going to win. I feel the issue of fully autonomous cars, 110 00:06:13,320 --> 00:06:16,600 Speaker 3: the biggest feature that you have to sell is safety. 111 00:06:17,000 --> 00:06:20,159 Speaker 3: How safety, How safe is your solution is? And I 112 00:06:20,200 --> 00:06:22,800 Speaker 3: think those takes time and one of the advantages. Teslas 113 00:06:22,839 --> 00:06:24,760 Speaker 3: have been doing this for longer, so they have a 114 00:06:24,800 --> 00:06:28,320 Speaker 3: lot of miles or real word miles, not only simulation 115 00:06:29,320 --> 00:06:30,520 Speaker 3: to perfect the solution. 116 00:06:30,760 --> 00:06:31,560 Speaker 2: But it's going to happen. 117 00:06:31,600 --> 00:06:33,839 Speaker 3: It's going to be a reality of many car companies 118 00:06:34,360 --> 00:06:35,360 Speaker 3: in the next few years. 119 00:06:35,560 --> 00:06:37,400 Speaker 1: And of course you've got a strong relationship with Google 120 00:06:37,440 --> 00:06:40,440 Speaker 1: when it comes to being within the auto as well 121 00:06:40,480 --> 00:06:43,400 Speaker 1: in many ways. Take us there for where you see 122 00:06:43,440 --> 00:06:46,880 Speaker 1: the next innovations. Robots were almost there, cars were already there. 123 00:06:47,360 --> 00:06:50,560 Speaker 1: Everyone I'm seeing is getting excited about the wearables, the pennons, 124 00:06:50,600 --> 00:06:53,680 Speaker 1: the jewelry. Where does quankom play in that, because that's 125 00:06:53,680 --> 00:06:54,320 Speaker 1: an edge device. 126 00:06:54,360 --> 00:06:59,719 Speaker 3: Yes, this is another area of excitement for Qualcom because 127 00:07:00,240 --> 00:07:03,560 Speaker 3: we are probably now willing to make a statement that 128 00:07:03,720 --> 00:07:07,560 Speaker 3: is the evolution of mobile platform. Phones are not going anywhere. 129 00:07:07,600 --> 00:07:10,440 Speaker 3: Phones are incredibly useful. They will continue to be useful 130 00:07:10,480 --> 00:07:12,960 Speaker 3: in the same way that when the smartphone arrived, your 131 00:07:13,040 --> 00:07:16,880 Speaker 3: laptop didn't go anywhere. However, when you think about AI 132 00:07:17,200 --> 00:07:21,360 Speaker 3: and agentic experiences, this AI agent that is with you 133 00:07:21,560 --> 00:07:23,840 Speaker 3: all the time and you're gonna ask a question and 134 00:07:23,880 --> 00:07:26,360 Speaker 3: you'll answer, will help you navigate, help you do your 135 00:07:26,440 --> 00:07:31,360 Speaker 3: daily fan that's gonna happen with wearables. Humans already decided 136 00:07:31,360 --> 00:07:33,720 Speaker 3: what they're gonna wear. They're gonna wear glasses and jewelry 137 00:07:33,760 --> 00:07:36,440 Speaker 3: and watches and rings, and you can put an agent 138 00:07:36,640 --> 00:07:40,280 Speaker 3: connect to it give you context because something you wear 139 00:07:40,320 --> 00:07:43,640 Speaker 3: all the time. So we're starting the immersions of those 140 00:07:43,640 --> 00:07:47,400 Speaker 3: smart wearables personal AI devices. We're excited about it because 141 00:07:47,600 --> 00:07:49,880 Speaker 3: this require for you to make something that is small, 142 00:07:50,960 --> 00:07:55,520 Speaker 3: a lot of performance, low power. So every major AI 143 00:07:55,600 --> 00:07:58,960 Speaker 3: company that is doing a device is designing with Callcom 144 00:07:59,040 --> 00:08:01,960 Speaker 3: right now. We have redesign and some of those are 145 00:08:02,000 --> 00:08:04,640 Speaker 3: being announced CS, some will be announced through of the year. 146 00:08:05,000 --> 00:08:08,800 Speaker 3: But personal devices are the neo mobile platform. 147 00:08:09,040 --> 00:08:10,680 Speaker 1: Wow. Okay, So if that's the way we're going to 148 00:08:10,720 --> 00:08:14,160 Speaker 1: be doing wearables, where is the future PCs? Because that 149 00:08:14,360 --> 00:08:17,880 Speaker 1: was the first sort of broadening out and AIPCS has 150 00:08:17,880 --> 00:08:19,840 Speaker 1: it really caught on and people wanting to go there. 151 00:08:19,920 --> 00:08:22,840 Speaker 1: Is it more enterprise adoption versus a consumer adoption. Yes. 152 00:08:23,200 --> 00:08:28,040 Speaker 3: So the Microsoft just launched the new version of Windows 153 00:08:28,040 --> 00:08:30,280 Speaker 3: with agents, and I think we've all been kind of 154 00:08:30,320 --> 00:08:33,400 Speaker 3: waiting for this moment, and you're starting to see a 155 00:08:33,400 --> 00:08:37,320 Speaker 3: lot of the SaaS companies there are being spent the 156 00:08:37,400 --> 00:08:40,920 Speaker 3: past deck decade going to the cloud creating agents as well. 157 00:08:41,400 --> 00:08:43,720 Speaker 3: So I think we're just at the beginning of the 158 00:08:43,720 --> 00:08:48,120 Speaker 3: inflection point of AIPCS is more at an enterprise play 159 00:08:48,320 --> 00:08:50,960 Speaker 3: than the consumer play, even though it will be part 160 00:08:51,080 --> 00:08:54,319 Speaker 3: of a lot of consumer use cases, and I remain 161 00:08:54,360 --> 00:08:57,040 Speaker 3: optimistic about it. Our PC business were just started. We 162 00:08:57,120 --> 00:08:59,000 Speaker 3: have about one hundred and fifty designs. Most of our 163 00:08:59,000 --> 00:09:02,040 Speaker 3: designs is because people wanted to do a thin and 164 00:09:02,880 --> 00:09:06,199 Speaker 3: light and multi day battery life. But now that you're 165 00:09:06,240 --> 00:09:08,760 Speaker 3: going to put AI running all the time, that's where 166 00:09:08,760 --> 00:09:12,760 Speaker 3: we're gonna shine of unplugged performance and it's gonna happen. 167 00:09:12,880 --> 00:09:16,720 Speaker 3: I think it's gonna happen, and the enterprise boom of AI. 168 00:09:17,000 --> 00:09:20,199 Speaker 3: You're going to see a lot of AIPCS associated what 169 00:09:20,360 --> 00:09:21,959 Speaker 3: is happening on the data center as well. 170 00:09:22,080 --> 00:09:24,080 Speaker 1: So Christiana, for all those people out there who are like, 171 00:09:24,520 --> 00:09:27,960 Speaker 1: this is a bubble, this is the real return on 172 00:09:28,120 --> 00:09:30,920 Speaker 1: AI investment isn't coming yet. What do you say to 173 00:09:30,960 --> 00:09:31,679 Speaker 1: that sort of critique? 174 00:09:31,720 --> 00:09:35,040 Speaker 3: Not for us. I think we're doing We're doing things 175 00:09:35,040 --> 00:09:37,360 Speaker 3: on the edge, the stuff that humans are buying, and 176 00:09:37,400 --> 00:09:39,960 Speaker 3: I think when we're going into the data center is 177 00:09:40,000 --> 00:09:44,880 Speaker 3: for inference. But here's the answer to your question. Everybody's 178 00:09:44,920 --> 00:09:47,600 Speaker 3: playing to win, right, so we've seen this movie before. 179 00:09:48,080 --> 00:09:52,520 Speaker 3: Everybody's playing to win. Everybody's building capacity to win. Will 180 00:09:52,559 --> 00:09:56,600 Speaker 3: everybody win? Probably not. There are gonna be few winners. 181 00:09:56,640 --> 00:09:59,160 Speaker 3: And I think the way to think about this is 182 00:10:00,520 --> 00:10:05,160 Speaker 3: maybe maybe in the short term you could argue that, 183 00:10:05,720 --> 00:10:09,160 Speaker 3: you know, maybe there's an overinvestment. I think it's a 184 00:10:10,200 --> 00:10:12,880 Speaker 3: it's a natural consequence of everybody playing to win. But 185 00:10:12,920 --> 00:10:16,280 Speaker 3: in the long run, I still believe AI is under hype. 186 00:10:16,679 --> 00:10:19,240 Speaker 3: And the way I'll do the parallel for you. The 187 00:10:19,240 --> 00:10:21,800 Speaker 3: Internet in the year two thousand was probably over hyped. 188 00:10:22,160 --> 00:10:24,640 Speaker 3: But in the year two thousand, when people thought what 189 00:10:24,679 --> 00:10:28,160 Speaker 3: the Internet would be today was a fraction, It's much 190 00:10:28,200 --> 00:10:30,240 Speaker 3: bigger than what they thought it would be, and I 191 00:10:30,280 --> 00:10:31,640 Speaker 3: think AI is going to be the same thing. 192 00:10:32,080 --> 00:10:35,640 Speaker 1: Christiana Aman so great to get your ultimism and here 193 00:10:35,960 --> 00:10:37,400 Speaker 1: right on the floor of CS