1 00:00:02,360 --> 00:00:07,560 Speaker 1: Bloomberg Audio Studios, podcasts, radio news now to a major 2 00:00:07,600 --> 00:00:12,080 Speaker 1: company story, Armstock. In the headlines, it's posting record quarterly 3 00:00:12,200 --> 00:00:16,160 Speaker 1: revenue but issuing cautious guidance for the current quarter, citing 4 00:00:16,160 --> 00:00:18,919 Speaker 1: the timing of new licensing deals in particular. Meanwhile, the 5 00:00:18,920 --> 00:00:21,960 Speaker 1: Trump administration pans to roll back Biden Nearer ai Chip 6 00:00:22,040 --> 00:00:25,440 Speaker 1: curbs with a new export control framework in the works, 7 00:00:25,440 --> 00:00:27,640 Speaker 1: and that may impact things too. So joining us now 8 00:00:27,640 --> 00:00:30,600 Speaker 1: to discuss it all as ARMS CEO Renee has along 9 00:00:30,600 --> 00:00:33,000 Speaker 1: with Bloomberg Tech co host Carolyn Hyde. 10 00:00:33,000 --> 00:00:34,239 Speaker 2: Carolyn, thank you. 11 00:00:34,240 --> 00:00:37,120 Speaker 3: Bonnie and Renee. It's always wonderful to welcome you to 12 00:00:37,159 --> 00:00:40,160 Speaker 3: Bloomberg Television. And let's just dwell on your numbers, because 13 00:00:40,200 --> 00:00:42,920 Speaker 3: revenue strong, up thirty four percent for your fiscal fourth quarter. 14 00:00:42,960 --> 00:00:45,159 Speaker 3: We saw more than a billion dollars being brought in 15 00:00:45,200 --> 00:00:46,280 Speaker 3: and indeed a profit beat. 16 00:00:46,320 --> 00:00:48,839 Speaker 1: But investors taken with what seems to be. 17 00:00:48,800 --> 00:00:52,680 Speaker 3: This cautious outlook, how uncertain are things from a demand 18 00:00:52,720 --> 00:00:56,120 Speaker 3: perspective that also perhaps you're not giving that annual target 19 00:00:56,120 --> 00:00:56,880 Speaker 3: that someone had hoped for. 20 00:00:57,960 --> 00:01:00,160 Speaker 4: Yeah a hi, Carolin, and thank you for the the 21 00:01:00,240 --> 00:01:04,200 Speaker 4: kind words. Yes, we just came off an amazing end 22 00:01:04,200 --> 00:01:07,559 Speaker 4: of our fiscal year, the first billion dollar quarter, which 23 00:01:07,600 --> 00:01:11,360 Speaker 4: was a record record royalties over six hundred million dollars, 24 00:01:11,440 --> 00:01:14,840 Speaker 4: record licensing over six hundred million dollars, and then we 25 00:01:14,920 --> 00:01:17,600 Speaker 4: finished the year at four billion dollars, which was also 26 00:01:18,120 --> 00:01:19,280 Speaker 4: a record for the company. 27 00:01:20,160 --> 00:01:22,880 Speaker 2: For Q one, we're looking at very good royalty growth. 28 00:01:22,920 --> 00:01:26,840 Speaker 4: Actually, Caroline, we're projecting anywhere between twenty five to thirty percent. 29 00:01:27,480 --> 00:01:29,360 Speaker 4: On the licensing side, I think, as you know, the 30 00:01:29,400 --> 00:01:32,560 Speaker 4: deals can be a little bit lumpy, So as a 31 00:01:32,600 --> 00:01:35,800 Speaker 4: result of looking forward in terms of whether deals closed 32 00:01:35,840 --> 00:01:39,039 Speaker 4: in the June or July timeframe, we decided to be 33 00:01:39,080 --> 00:01:41,360 Speaker 4: cautious and give the outlook that we did just based 34 00:01:41,400 --> 00:01:44,600 Speaker 4: upon licensing. But the overall health of the business is 35 00:01:44,640 --> 00:01:48,800 Speaker 4: really really good. You know, we have obviously coming off 36 00:01:48,800 --> 00:01:51,640 Speaker 4: a great quarter and we have really good visibility into 37 00:01:51,720 --> 00:01:52,320 Speaker 4: the current quarter. 38 00:01:52,360 --> 00:01:53,080 Speaker 2: On royalties. 39 00:01:53,680 --> 00:01:56,560 Speaker 4: The reason we chose not to give the yearly guidance thing, 40 00:01:56,640 --> 00:02:00,600 Speaker 4: as you know, now vast majority of our businesses increasinglyyalties, 41 00:02:00,680 --> 00:02:04,080 Speaker 4: and that really comes from people who make either the 42 00:02:04,280 --> 00:02:07,760 Speaker 4: end ship or the end equipment, and that in the 43 00:02:07,800 --> 00:02:10,440 Speaker 4: next two to three quarters is a little hard to predict, 44 00:02:10,440 --> 00:02:12,680 Speaker 4: and in fact, we're not seeing that guidance coming from 45 00:02:12,680 --> 00:02:13,320 Speaker 4: our partners. 46 00:02:13,720 --> 00:02:14,320 Speaker 2: So as a. 47 00:02:14,280 --> 00:02:18,120 Speaker 4: Result, given that their visibility isn't as strong as it 48 00:02:18,160 --> 00:02:21,440 Speaker 4: usually is around that we decided not to go forward 49 00:02:21,480 --> 00:02:24,160 Speaker 4: and give a guidance beyond justice first quarter, and. 50 00:02:25,040 --> 00:02:27,240 Speaker 3: Just for the people who always need to be reminded 51 00:02:27,240 --> 00:02:29,760 Speaker 3: of the business model you are designing. Ultimately, people that 52 00:02:29,840 --> 00:02:33,519 Speaker 3: are licensing using these designs, you are not directly impacted 53 00:02:33,919 --> 00:02:36,200 Speaker 3: by tariffs, but of course the people that make the 54 00:02:36,240 --> 00:02:39,640 Speaker 3: smartphones eventually might be. Are you hearing anything about a 55 00:02:39,680 --> 00:02:42,080 Speaker 3: worry on demand in the future. Are you thinking that 56 00:02:42,160 --> 00:02:44,080 Speaker 3: we'll will see a downward trajectory for some of the 57 00:02:44,120 --> 00:02:47,200 Speaker 3: electronics parts that you've diversified the business into. 58 00:02:48,080 --> 00:02:50,239 Speaker 2: Yeah, thank you for pointing that out. 59 00:02:50,280 --> 00:02:53,440 Speaker 4: Yet exactly, we are a provider of the designs that 60 00:02:53,520 --> 00:02:57,440 Speaker 4: go into chips that go into end products like your iPhone, 61 00:02:57,919 --> 00:03:01,000 Speaker 4: your Ford f one fifty, your earbudd it's the AI 62 00:03:01,120 --> 00:03:04,240 Speaker 4: data centers. So we're not directly impacted, but we are 63 00:03:04,280 --> 00:03:08,079 Speaker 4: certainly indirectly impacted, and that would come on the royalty 64 00:03:08,120 --> 00:03:10,359 Speaker 4: side to your question, are we. 65 00:03:10,360 --> 00:03:14,800 Speaker 2: Seeing anything relative to folks? 66 00:03:15,120 --> 00:03:17,919 Speaker 4: Not clear in terms of where the terrorifts are coming from. 67 00:03:18,240 --> 00:03:20,280 Speaker 4: What we're seeing is kind of a lack of clarity 68 00:03:20,680 --> 00:03:23,280 Speaker 4: as opposed to any one indicator or the other. So 69 00:03:23,280 --> 00:03:26,040 Speaker 4: that's just really driving and it's just the lack of 70 00:03:26,120 --> 00:03:28,080 Speaker 4: visibility that our end partners have. 71 00:03:28,480 --> 00:03:29,000 Speaker 2: Ren I have. 72 00:03:29,000 --> 00:03:33,239 Speaker 1: Any plans on changing how you actually charge your royalties, 73 00:03:33,280 --> 00:03:36,040 Speaker 1: maybe you'll move into a per device basis. And also 74 00:03:36,080 --> 00:03:39,160 Speaker 1: how much pricing power do you have in an inflationary environment? 75 00:03:40,720 --> 00:03:43,800 Speaker 4: Yeah, thanks for asking that question. What we have done 76 00:03:43,920 --> 00:03:47,680 Speaker 4: is transition to more comprehensive products what we call our 77 00:03:47,680 --> 00:03:51,480 Speaker 4: compute subsystems, and think of that as a design that 78 00:03:51,600 --> 00:03:54,080 Speaker 4: not only are we licensing the individual blocks of IP, 79 00:03:54,960 --> 00:03:57,240 Speaker 4: but all of the other blocks of IP required to 80 00:03:57,240 --> 00:03:59,480 Speaker 4: make a subsystem that would go on a chip. 81 00:04:00,280 --> 00:04:03,000 Speaker 2: Those command higher royalties. 82 00:04:03,360 --> 00:04:06,760 Speaker 4: Generally double from what we see on traditional individual blocks. 83 00:04:07,160 --> 00:04:10,600 Speaker 4: The benefit to the customers is it really accelerates time 84 00:04:10,640 --> 00:04:14,720 Speaker 4: to market. Chip development time goes down, huge value that 85 00:04:14,760 --> 00:04:16,640 Speaker 4: they see in terms of predictability of the design. 86 00:04:17,120 --> 00:04:18,000 Speaker 2: So that's what. 87 00:04:18,000 --> 00:04:20,160 Speaker 4: We've been shifting to much more in terms of our 88 00:04:20,560 --> 00:04:23,240 Speaker 4: royalty model, which is why the royalty growth has been 89 00:04:23,520 --> 00:04:24,520 Speaker 4: as good as it has been. 90 00:04:25,320 --> 00:04:28,560 Speaker 3: I'm really interested in the AI data center part because 91 00:04:28,560 --> 00:04:30,880 Speaker 3: this has been a real era of focus of growth, 92 00:04:30,920 --> 00:04:33,520 Speaker 3: and I'm interested in the momentum that you're seeing and 93 00:04:33,520 --> 00:04:35,919 Speaker 3: how resilient it is. You're talking about uncertainty when it 94 00:04:35,920 --> 00:04:38,560 Speaker 3: comes to smartphones and electronics in the future. Has there 95 00:04:38,560 --> 00:04:41,960 Speaker 3: been any signal of uncertainty on spending on AI infrastructure. 96 00:04:43,760 --> 00:04:45,800 Speaker 2: Yeah, not that we've seen, Caroline. 97 00:04:46,440 --> 00:04:49,719 Speaker 4: You've got Stargate obviously, a huge program that's being done 98 00:04:49,720 --> 00:04:52,160 Speaker 4: between soft Bank and open Ai, which is all around 99 00:04:52,520 --> 00:04:56,279 Speaker 4: capital and power for data centers. You're seeing large capex 100 00:04:56,320 --> 00:05:00,320 Speaker 4: spending by the major hyperscalers. But probably more important, certainly, 101 00:05:00,880 --> 00:05:04,159 Speaker 4: I think we're nowhere close to really good enough in 102 00:05:04,240 --> 00:05:07,320 Speaker 4: terms of the capability what AI can do. Obviously, the 103 00:05:08,040 --> 00:05:10,359 Speaker 4: advances have been amazing, and if you look at just 104 00:05:10,400 --> 00:05:12,880 Speaker 4: what OpenEye has done with chat Gypt, it's been remarkable, 105 00:05:13,800 --> 00:05:17,960 Speaker 4: but enterprise usage from a mass deployment standpoint is still 106 00:05:18,040 --> 00:05:21,040 Speaker 4: quite modest. A factoid that I like to refer to 107 00:05:21,160 --> 00:05:24,479 Speaker 4: is chat GPT used a petabyte. 108 00:05:24,000 --> 00:05:25,840 Speaker 2: Of data to create the model. 109 00:05:26,240 --> 00:05:28,600 Speaker 4: JP Morgan has one hundred and fifty petabytes of data 110 00:05:28,600 --> 00:05:31,000 Speaker 4: sitting inside their enterprise. In one way, shape or form, 111 00:05:31,520 --> 00:05:34,880 Speaker 4: harnessing that data, turning that data into real valuable information, 112 00:05:35,320 --> 00:05:38,599 Speaker 4: and then helping productivity. There's a lot of white space there, 113 00:05:38,680 --> 00:05:41,840 Speaker 4: and I think still there's a long way to see 114 00:05:41,839 --> 00:05:42,400 Speaker 4: growth here. 115 00:05:42,640 --> 00:05:45,880 Speaker 3: There's been some uncertainty, of course, around ultimately how those 116 00:05:45,920 --> 00:05:48,960 Speaker 3: that use your designs can ultimately sell their chips. And 117 00:05:49,160 --> 00:05:51,800 Speaker 3: we've now got a pullback from the AI diffusion rule 118 00:05:51,800 --> 00:05:53,320 Speaker 3: as it's called here in the United States. It would 119 00:05:53,320 --> 00:05:55,520 Speaker 3: seem that's going to be announced anytime soon by the 120 00:05:55,520 --> 00:05:57,800 Speaker 3: Trump administration. Is that going to be a boost for 121 00:05:57,800 --> 00:06:00,480 Speaker 3: your business? Do you think that leads to most You're 122 00:06:00,480 --> 00:06:03,040 Speaker 3: actually lack of it, because now we have countries having 123 00:06:03,040 --> 00:06:05,040 Speaker 3: to negotiate on a case by case basis. 124 00:06:05,600 --> 00:06:07,920 Speaker 4: Yeah, I don't know that I could predict it. I mean, 125 00:06:08,040 --> 00:06:11,120 Speaker 4: actually seen what the what the outcome looks like. The 126 00:06:11,160 --> 00:06:14,680 Speaker 4: wonderful thing about our jobs these days, CEOs, that we're 127 00:06:14,760 --> 00:06:17,799 Speaker 4: reading the news and hearing that from you at real time. 128 00:06:18,279 --> 00:06:20,479 Speaker 4: I think we'll just have to see, is the short answer. 129 00:06:21,240 --> 00:06:25,880 Speaker 4: I don't think AI demand is a bubble in any way, 130 00:06:25,920 --> 00:06:27,560 Speaker 4: shape or form. And as I said, I don't think 131 00:06:27,600 --> 00:06:31,360 Speaker 4: we've gone anywhere close to reaching its true potential. 132 00:06:32,080 --> 00:06:33,240 Speaker 2: When you think about. 133 00:06:33,320 --> 00:06:37,160 Speaker 4: End devices that will run AI models, everything will run them. 134 00:06:37,800 --> 00:06:40,320 Speaker 4: They'll run in earbuds, they'll run in cars, they'll run 135 00:06:40,320 --> 00:06:43,000 Speaker 4: on mobile phones. They're certainly going to run in the cloud, 136 00:06:43,320 --> 00:06:46,760 Speaker 4: but they won't run exclusively in the cloud. And I 137 00:06:46,800 --> 00:06:49,760 Speaker 4: think we still have a long way to go in 138 00:06:49,880 --> 00:06:55,440 Speaker 4: this area. The progress has been remarkable, shockings in some 139 00:06:55,520 --> 00:06:58,800 Speaker 4: ways just how good the models have become, but there's 140 00:06:58,800 --> 00:07:01,159 Speaker 4: still a long ways to go in terms of I 141 00:07:01,200 --> 00:07:03,679 Speaker 4: think true AGI and then ultimately ASI. 142 00:07:04,200 --> 00:07:07,039 Speaker 1: Ronnie, your top five customers are responsible for sixty percent 143 00:07:07,040 --> 00:07:09,400 Speaker 1: of revenue and are in China twenty percent of that. 144 00:07:09,920 --> 00:07:13,120 Speaker 1: I'm curious as to how you're making an effort to diversify. 145 00:07:13,200 --> 00:07:16,800 Speaker 1: That's a phenomenally concentrated client base, particularly when you consider 146 00:07:16,840 --> 00:07:20,280 Speaker 1: the China. You know, you might have some concerns around China. 147 00:07:21,720 --> 00:07:25,280 Speaker 4: Yeah, the industry that we're in has been seeing, you know, 148 00:07:25,360 --> 00:07:28,000 Speaker 4: quite a bit of consolidation. You know, for quite some time. 149 00:07:28,280 --> 00:07:33,760 Speaker 4: The amount of capital required to make chips is quite 150 00:07:33,760 --> 00:07:35,160 Speaker 4: a bit. So you look at the number of companies 151 00:07:35,200 --> 00:07:39,160 Speaker 4: who are their end products are chips. Its shrink over 152 00:07:39,160 --> 00:07:41,280 Speaker 4: the last number of years. And at the same time, 153 00:07:42,000 --> 00:07:45,560 Speaker 4: you've got large hyperscalers in the Microsoft's, the Metas, the Googles, 154 00:07:45,560 --> 00:07:48,640 Speaker 4: to Amazons that you know, there's not many people have 155 00:07:48,720 --> 00:07:52,280 Speaker 4: that capital. That being said, the number of chips, the 156 00:07:52,320 --> 00:07:54,640 Speaker 4: demand for chips the compute has actually gone way up, 157 00:07:55,040 --> 00:07:57,880 Speaker 4: So I probably don't think so much about the number 158 00:07:57,920 --> 00:08:00,400 Speaker 4: of people who buy. I would get more worried if number, 159 00:08:00,560 --> 00:08:03,520 Speaker 4: if the quantity was going down, and we're not seeing that, 160 00:08:04,120 --> 00:08:05,360 Speaker 4: and why are we not seeing that. 161 00:08:06,000 --> 00:08:08,239 Speaker 2: The insatiable demand for more and more. 162 00:08:08,080 --> 00:08:13,120 Speaker 4: Compute driven by AI, I think again, is we're in 163 00:08:13,240 --> 00:08:14,320 Speaker 4: very early stages of it. 164 00:08:14,480 --> 00:08:15,120 Speaker 2: You also have to. 165 00:08:15,040 --> 00:08:18,640 Speaker 4: Remember that running these AI workloads, you still need to 166 00:08:18,680 --> 00:08:21,160 Speaker 4: run them on top of running a Windows operating system, 167 00:08:21,240 --> 00:08:24,240 Speaker 4: on top of running an iOS operating system, on top 168 00:08:24,280 --> 00:08:28,360 Speaker 4: of running an IBI instrumentation inside a car or autonomous 169 00:08:28,640 --> 00:08:32,520 Speaker 4: So it's not that AI compute replaces traditional compute. It's 170 00:08:32,600 --> 00:08:35,640 Speaker 4: on top of which is a strong demand signal for 171 00:08:35,840 --> 00:08:38,559 Speaker 4: personmic conductors, and I has the m CEO. 172 00:08:38,840 --> 00:08:40,640 Speaker 3: It's going to enjoy having you. Thank you very much. 173 00:08:40,720 --> 00:08:41,080 Speaker 2: Indeed,