1 00:00:00,080 --> 00:00:01,760 Speaker 1: Seven Heller duper Cel. 2 00:00:02,040 --> 00:00:04,560 Speaker 2: So the chip mak in Vidia has announced the age 3 00:00:04,559 --> 00:00:07,240 Speaker 2: of AI is in full steam. The companies announced its 4 00:00:07,280 --> 00:00:10,480 Speaker 2: third quarter earnings today, beating expectations for sales and earnings, 5 00:00:10,720 --> 00:00:13,200 Speaker 2: and Sam Dickey from Fisher Funds is with us on that. Hey, Sam, 6 00:00:13,560 --> 00:00:15,600 Speaker 2: good right, So tell me about the result. 7 00:00:17,320 --> 00:00:19,760 Speaker 1: Another astonishing result on the face of it. So they 8 00:00:19,760 --> 00:00:23,320 Speaker 1: almost doubled revenue to thirty five billion in profits more 9 00:00:23,360 --> 00:00:25,680 Speaker 1: than doubled, and importantly, as you said, it was more 10 00:00:25,680 --> 00:00:29,320 Speaker 1: than five percent better than already lofty expectations that analysts 11 00:00:29,360 --> 00:00:32,360 Speaker 1: had and their key data center business, where by they're 12 00:00:32,360 --> 00:00:36,600 Speaker 1: selling their accelerated computer chips into data centers like Google Cloud, 13 00:00:36,640 --> 00:00:39,519 Speaker 1: for example. That grew one hundred and twenty two percent. 14 00:00:39,680 --> 00:00:40,919 Speaker 1: So all well on. 15 00:00:40,840 --> 00:00:43,199 Speaker 2: The face of it, And the stock price did what. 16 00:00:44,720 --> 00:00:47,000 Speaker 1: Not fabulously It closed about two and a half percent 17 00:00:47,040 --> 00:00:49,159 Speaker 1: after hours despite the strong results. So it is a 18 00:00:49,200 --> 00:00:53,640 Speaker 1: reminder that the bar for this company is punishingly high. 19 00:00:54,080 --> 00:00:55,560 Speaker 1: In other words, there's a lot of good news in 20 00:00:55,600 --> 00:00:56,280 Speaker 1: the share price. 21 00:00:56,600 --> 00:00:59,040 Speaker 2: Okay, Now, obviously everybody's looking at this not just about 22 00:00:59,040 --> 00:01:01,880 Speaker 2: the perform pullmans of one company, but what this means 23 00:01:01,880 --> 00:01:03,640 Speaker 2: for the tech sector. And what it means for AI. 24 00:01:04,000 --> 00:01:05,480 Speaker 2: So what are you taking from it? 25 00:01:06,840 --> 00:01:08,840 Speaker 1: Yeah, there's no doub there's a huge amount of money 26 00:01:08,840 --> 00:01:13,160 Speaker 1: pouring into AI, and in fact a huge amount more 27 00:01:13,200 --> 00:01:15,080 Speaker 1: than was expected just a few weeks ago. But what 28 00:01:15,200 --> 00:01:18,040 Speaker 1: is super interesting is you've got to remember the vast 29 00:01:18,080 --> 00:01:20,080 Speaker 1: majority of these in vidio chips have been sold to 30 00:01:20,080 --> 00:01:22,960 Speaker 1: companies like Microsoft and Google and Amazon, who are re 31 00:01:22,959 --> 00:01:26,000 Speaker 1: renting out those chips to thousands of smaller companies who 32 00:01:26,040 --> 00:01:28,319 Speaker 1: are racing to find the next big AI use case 33 00:01:28,360 --> 00:01:30,640 Speaker 1: and the one that we will all pay for, as 34 00:01:30,680 --> 00:01:32,759 Speaker 1: we've talked about before. So to that end, in video, 35 00:01:32,800 --> 00:01:37,560 Speaker 1: seeing most excited about AI agents. So AI agents to 36 00:01:37,600 --> 00:01:40,200 Speaker 1: replace call centers and course center people, AI agents to 37 00:01:40,360 --> 00:01:44,000 Speaker 1: automate everyday work streams and videos, talking about billions of 38 00:01:44,000 --> 00:01:47,000 Speaker 1: agents over the next few years. And the other thing 39 00:01:47,040 --> 00:01:51,240 Speaker 1: that's taking off again right now is industrial robotics. And 40 00:01:51,360 --> 00:01:53,040 Speaker 1: it was always a growth theory, but the potential for 41 00:01:53,080 --> 00:01:56,560 Speaker 1: the robots and factories and surgical robots to learn and 42 00:01:56,600 --> 00:02:00,919 Speaker 1: get better and more precise is increasingly as preaching exponentially, 43 00:02:00,960 --> 00:02:04,600 Speaker 1: And if you take Intuitive Surgical for example, they've got 44 00:02:04,640 --> 00:02:08,480 Speaker 1: near one hundred percent markets here in soft to robotic surgery. 45 00:02:09,040 --> 00:02:11,560 Speaker 1: Their new robotic system is learning so fast that in 46 00:02:11,560 --> 00:02:13,799 Speaker 1: time it's going to be able to perform simple operations 47 00:02:13,840 --> 00:02:16,959 Speaker 1: like stitching up the wound after a gall bladder operational boat. 48 00:02:17,080 --> 00:02:19,280 Speaker 2: So now, I mean the thing is, it's been it's 49 00:02:19,320 --> 00:02:22,919 Speaker 2: been somewhat disappointing, you know, the our adoption, consumer's adoption 50 00:02:22,960 --> 00:02:24,360 Speaker 2: of AI. So do you think it's going to pick 51 00:02:24,440 --> 00:02:24,880 Speaker 2: up from here? 52 00:02:26,160 --> 00:02:28,440 Speaker 1: Yeah, when the consumer adoption has been poor and we 53 00:02:28,480 --> 00:02:31,080 Speaker 1: talked about this last time, So was it going to 54 00:02:31,200 --> 00:02:35,160 Speaker 1: be the an upgrade cycle on iPhones because of the 55 00:02:35,200 --> 00:02:37,680 Speaker 1: new Apple intelligence? And it doesn't look like people are 56 00:02:37,720 --> 00:02:39,400 Speaker 1: prepared to pay an extra two or three hundred bucks 57 00:02:39,400 --> 00:02:42,040 Speaker 1: of phone just for a smartest sery. And then of 58 00:02:42,040 --> 00:02:45,440 Speaker 1: course the large language models themselves and there are people 59 00:02:45,480 --> 00:02:47,920 Speaker 1: that pay, you know, twenty bucks a month for Perplexity 60 00:02:48,080 --> 00:02:51,360 Speaker 1: or chat Giti or whatever. But I don't think that's 61 00:02:51,440 --> 00:02:54,160 Speaker 1: going to kind of fill that yawning gap between the 62 00:02:54,200 --> 00:02:57,520 Speaker 1: amount of these accelerated compute chips that are being sold 63 00:02:57,520 --> 00:03:01,000 Speaker 1: by in video. So it looks like corporate So the 64 00:03:01,560 --> 00:03:04,600 Speaker 1: new big buyers of AI. And this is this is 65 00:03:04,639 --> 00:03:07,960 Speaker 1: this AI agent story I'm talking about. So if you 66 00:03:08,040 --> 00:03:11,400 Speaker 1: can sadly replace lots of people with an AI agent 67 00:03:11,440 --> 00:03:14,200 Speaker 1: and a core center that's as good, if not better, 68 00:03:14,240 --> 00:03:16,560 Speaker 1: then that makes sense for a corporate. 69 00:03:16,480 --> 00:03:18,040 Speaker 2: Okay, so what do you tell me what you're making 70 00:03:18,080 --> 00:03:20,919 Speaker 2: of this? For investors, Sam, it. 71 00:03:20,880 --> 00:03:24,880 Speaker 1: Seems like the AI bonanza continues unchecked, and there are 72 00:03:25,200 --> 00:03:27,400 Speaker 1: a few things to keep an eye on those. So 73 00:03:27,400 --> 00:03:30,000 Speaker 1: the revenue guidance for next quarter, and that was one 74 00:03:30,000 --> 00:03:31,600 Speaker 1: of the reasons why the stock was a bit weak, 75 00:03:32,360 --> 00:03:34,400 Speaker 1: was only kind of in line with expectations, so not 76 00:03:34,440 --> 00:03:36,960 Speaker 1: a barber as we've become accustomed to. And the other 77 00:03:37,000 --> 00:03:40,560 Speaker 1: thing that Nvidia talked about was the profit margin guidance. 78 00:03:40,600 --> 00:03:43,520 Speaker 1: So the margin they're making on this incredibly big revenue 79 00:03:43,600 --> 00:03:47,320 Speaker 1: number is just a bit soggy. So they're ramping a 80 00:03:46,120 --> 00:03:49,680 Speaker 1: new generation of chip called the Black World chip, which 81 00:03:49,680 --> 00:03:52,920 Speaker 1: has got exceptional performance, but it's just not quite as 82 00:03:52,960 --> 00:03:56,000 Speaker 1: profitable in the early days as the previous chips. So 83 00:03:56,000 --> 00:03:57,600 Speaker 1: a couple of things going on there. And then of 84 00:03:57,640 --> 00:03:59,920 Speaker 1: course these AI use cases. Let's keep our bd I 85 00:04:00,200 --> 00:04:03,800 Speaker 1: peeled on the next killer AI use case to fill 86 00:04:03,840 --> 00:04:07,520 Speaker 1: that yawning gap between you know, three point seven trillion 87 00:04:07,520 --> 00:04:12,360 Speaker 1: dollar valuation of Nvidia and the much less lower number 88 00:04:12,560 --> 00:04:15,160 Speaker 1: of the amount of dollars were prepared to pay for AI. 89 00:04:15,360 --> 00:04:17,480 Speaker 2: Your very very good point there, Sam Hey, thank you 90 00:04:17,560 --> 00:04:20,040 Speaker 2: appreciated that, Sam Dickey for your funds. 91 00:04:20,680 --> 00:04:23,839 Speaker 1: For more from Hither Duplessy Allen Drive, listen live to 92 00:04:23,960 --> 00:04:26,960 Speaker 1: news talks. It'd be from four pm weekdays, or follow 93 00:04:27,000 --> 00:04:28,719 Speaker 1: the podcast on iHeartRadio.