1 00:00:03,680 --> 00:00:07,920 Ejaaz: There are two companies currently worth trillions of dollars that I think are 2 00:00:07,920 --> 00:00:10,700 Ejaaz: the most undervalued companies in the world right now. 3 00:00:10,880 --> 00:00:15,980 Ejaaz: Google and Apple are a tale of two tech giants that have taken a very different approach to AI. 4 00:00:16,280 --> 00:00:20,020 Ejaaz: Google, on one hand, has poured billions of dollars to create some of the world's 5 00:00:20,020 --> 00:00:25,040 Ejaaz: leading AI models, going from a corporate has-been to one of the titans of AI. 6 00:00:25,280 --> 00:00:30,220 Ejaaz: They have their own custom GPUs rivaling NVIDIA. They have one of the largest 7 00:00:30,220 --> 00:00:34,700 Ejaaz: user bases in the world with Gmail, Android, YouTube. I could go on. 8 00:00:35,040 --> 00:00:38,560 Ejaaz: Apple, on the other hand, has taken the opposite approach. They haven't invested 9 00:00:38,560 --> 00:00:42,480 Ejaaz: in AI at all. They've been late to update their AI assistant Siri. 10 00:00:42,660 --> 00:00:46,920 Ejaaz: They haven't spent any money to hire AI geniuses like Zuckerberg at Meta. 11 00:00:47,260 --> 00:00:52,100 Ejaaz: But despite this, I think these two companies are poised to be the biggest companies in the world. 12 00:00:52,360 --> 00:00:56,240 Ejaaz: So in this episode, we're going to give you the bull case for Google and Apple 13 00:00:56,240 --> 00:01:00,260 Ejaaz: revealing not just why you should buy their stocks, but also why these two companies 14 00:01:00,260 --> 00:01:03,220 Ejaaz: in particular are very unlikely allies. 15 00:01:03,580 --> 00:01:07,440 Josh: Yeah, I think this episode is going to surprise a lot of people because there's 16 00:01:07,440 --> 00:01:11,580 Josh: this gross disconnect between public market sentiment and public sentiment where 17 00:01:11,580 --> 00:01:14,560 Josh: stocks are trading very high and people don't quite agree with that. 18 00:01:14,560 --> 00:01:18,020 Josh: So I think in this episode, we have a lot of what most would have perceived 19 00:01:18,020 --> 00:01:21,900 Josh: to be contrarian takes about where these companies have come from and where 20 00:01:21,900 --> 00:01:24,980 Josh: they are headed to and how we are actually much more optimistic than I think 21 00:01:24,980 --> 00:01:26,540 Josh: a lot of people think on these companies. 22 00:01:26,680 --> 00:01:29,500 Josh: So Ejaz, maybe you could help us start with the bull case for Google, 23 00:01:29,720 --> 00:01:31,880 Josh: which is one of the first companies we're going to be talking about here. 24 00:01:32,180 --> 00:01:38,600 Ejaaz: What if I told you that Google currently worth $3.4 trillion is an absolute bargain buy right now? 25 00:01:38,740 --> 00:01:39,780 Josh: That's a crazy take. 26 00:01:39,780 --> 00:01:44,480 Ejaaz: You call me crazy. But here's why I think Google is actually worth $10 trillion 27 00:01:44,480 --> 00:01:50,020 Ejaaz: as an AI giant currently masquerading as a simple, humble search engine. 28 00:01:50,240 --> 00:01:51,520 Ejaaz: I've got four reasons for you. 29 00:01:51,780 --> 00:01:54,860 Ejaaz: Number one, Google has the best AI models. 30 00:01:54,960 --> 00:01:58,180 Ejaaz: You have Google Gemini, which is currently crushing across all benchmarks and 31 00:01:58,180 --> 00:02:00,800 Ejaaz: beating ChatGPT on so many different fronts. 32 00:02:00,960 --> 00:02:04,600 Ejaaz: You have VO3, which is their text-to-video model, which is creating cinematic 33 00:02:04,600 --> 00:02:06,800 Ejaaz: masterpieces in a matter of seconds. 34 00:02:06,980 --> 00:02:11,140 Ejaaz: You have Nano Banana, their image generation model, which not just creates really 35 00:02:11,140 --> 00:02:13,300 Ejaaz: good images, but also allows you to edit them. 36 00:02:13,460 --> 00:02:17,160 Ejaaz: And finally, who can forget about Google's Alpha Gemini series, 37 00:02:17,520 --> 00:02:21,720 Ejaaz: their science AI models, which have won not one, but two Nobel Prizes. 38 00:02:21,860 --> 00:02:25,660 Ejaaz: Number two, they're the only real competitor that NVIDIA has. 39 00:02:25,780 --> 00:02:30,520 Ejaaz: They've created TPUs, which is their version of GPUs built to make their own 40 00:02:30,520 --> 00:02:34,940 Ejaaz: custom AI models specifically for Google's software stack and hardware stack. 41 00:02:35,290 --> 00:02:40,470 Ejaaz: They also have some of the craziest distribution of users. They have the number 42 00:02:40,470 --> 00:02:41,730 Ejaaz: one mailing app in Gmail. 43 00:02:42,010 --> 00:02:46,550 Ejaaz: They have the number one entertainment app with YouTube. They dominate search 44 00:02:46,550 --> 00:02:47,750 Ejaaz: engines and advertising. 45 00:02:48,010 --> 00:02:51,410 Ejaaz: And they also have the number one mobile operating system with Android. 46 00:02:51,690 --> 00:02:55,690 Ejaaz: And number four, a little lesser known fact, is they're some of the biggest 47 00:02:55,690 --> 00:02:57,170 Ejaaz: and best investors in the world. 48 00:02:57,290 --> 00:03:02,710 Ejaaz: They currently own 14% of competitor Anthropic and 6% of SpaceX. 49 00:03:03,230 --> 00:03:08,390 Ejaaz: So no matter how way you want to look at it, it's hard to argue why Google isn't 50 00:03:08,390 --> 00:03:10,310 Ejaaz: going to become the most valuable company in the world. 51 00:03:10,770 --> 00:03:13,670 Ejaaz: They have all these strengths, they have the best models, they have the best 52 00:03:13,670 --> 00:03:17,170 Ejaaz: data to train these models, and they have all the compute to build this in-house. 53 00:03:17,610 --> 00:03:20,530 Ejaaz: So I'm struggling to find an argument to see why Google isn't going to be the 54 00:03:20,530 --> 00:03:22,550 Ejaaz: most valuable company within a decade. 55 00:03:22,730 --> 00:03:26,010 Josh: I like looking at history. Google is very much a large player in this Game of 56 00:03:26,010 --> 00:03:27,970 Josh: Thrones that we talk about in the search for AGI. 57 00:03:28,430 --> 00:03:31,950 Josh: And it's helpful to have a little bit of context and pretext to how we got here 58 00:03:31,950 --> 00:03:34,750 Josh: today, where you're saying $10 trillion is a reasonable market cap. 59 00:03:34,870 --> 00:03:39,170 Josh: It's a little outrageous. But there's this funny story associated with the history of Google. 60 00:03:39,510 --> 00:03:44,170 Josh: And it kind of starts in 2019, I believe the year is, where they released a 61 00:03:44,170 --> 00:03:47,010 Josh: paper that was basically the inception of the Transformer. 62 00:03:47,090 --> 00:03:50,030 Josh: And for those who aren't familiar, the Transformer is the piece of technology, 63 00:03:50,170 --> 00:03:53,630 Josh: this little piece of code that has generated and created every single large 64 00:03:53,630 --> 00:03:55,070 Josh: language model that exists today. 65 00:03:55,270 --> 00:03:59,550 Josh: So by all means, Google kind of invented the technology that is running everybody's AI today. 66 00:04:00,070 --> 00:04:02,530 Josh: Naturally, as a result, you would expect them to be the front runner. 67 00:04:02,670 --> 00:04:06,250 Josh: But what they did is they kind of sat on this technology for a very long time. 68 00:04:06,450 --> 00:04:12,270 Josh: So in 2022, when ChatGPT came out, Google actually didn't really have a publicly facing AI product. 69 00:04:12,430 --> 00:04:14,750 Josh: They just had the technology because they were very much a research lab. 70 00:04:15,090 --> 00:04:19,150 Josh: So while OpenAI acquired a million users in the first week, Google is just kind 71 00:04:19,150 --> 00:04:23,770 Josh: of sitting there on, at this time, three to four year old technology that they 72 00:04:23,770 --> 00:04:25,630 Josh: just haven't actually implemented in the product. 73 00:04:25,750 --> 00:04:29,890 Josh: So what they did is they rushed to implement this product. and they created a lot of 74 00:04:30,290 --> 00:04:34,850 Josh: AI systems that started with Bard and then recently is what we know today as 75 00:04:34,850 --> 00:04:37,290 Josh: Gemini that just weren't really quite good. 76 00:04:37,470 --> 00:04:41,930 Josh: And you get the idea that the reason they weren't quite good is because the culture was pretty bad. 77 00:04:42,450 --> 00:04:47,270 Josh: In Google, there was a lot of problems with the workforce and of course a lot 78 00:04:47,270 --> 00:04:50,970 Josh: of disconnect where if you asked Bard at the time to generate the founding fathers, 79 00:04:51,230 --> 00:04:55,650 Josh: it would generate a series of minority women, which was just objectively incorrect and wrong. 80 00:04:55,770 --> 00:05:01,090 Josh: And a lot of people took that as, okay, Google actually doesn't have a chance at succeeding in AI. 81 00:05:01,330 --> 00:05:06,550 Josh: And the reality is that wasn't true because that changed when Sergey Brin comes into the picture. 82 00:05:06,690 --> 00:05:10,530 Josh: So we have a post here, Sergey Brin spotted IRL again, and apparently he's working 83 00:05:10,530 --> 00:05:12,210 Josh: on Gemini at Google. And this is true. 84 00:05:12,370 --> 00:05:14,470 Josh: Sergey Brin, for those who don't know, co-founder of Google. 85 00:05:14,590 --> 00:05:18,110 Josh: He was the guy who started from the beginning and he recognized a wave that 86 00:05:18,110 --> 00:05:18,990 Josh: was too important to miss. 87 00:05:19,090 --> 00:05:23,710 Josh: He came back to Google and he started implementing what they did at early stage Google today. 88 00:05:23,890 --> 00:05:28,050 Josh: And now we have Gemini, which is the most powerful AI model in the world, 89 00:05:28,050 --> 00:05:30,790 Josh: they're at least very much at the frontier with everybody else and they're implementing 90 00:05:30,790 --> 00:05:35,270 Josh: a lot of new services they incepted this amazing technology lost the lead and 91 00:05:35,270 --> 00:05:38,150 Josh: now are each as you're telling me they're probably going to get back into the 92 00:05:38,150 --> 00:05:40,630 Josh: lead because that would be the implication with 10 trillion dollar market cap 93 00:05:40,630 --> 00:05:46,330 Ejaaz: Yep and i think there are four key reasons why uh they hold such a a powerful 94 00:05:46,330 --> 00:05:49,330 Ejaaz: moat and why they're super undervalued i want to start off with, 95 00:05:49,800 --> 00:05:55,440 Ejaaz: Talking about their model, and it's not just like an LLM, it is everything else, right? 96 00:05:55,580 --> 00:05:59,540 Ejaaz: They've tackled and are leading every other medium in terms of AI-generated 97 00:05:59,540 --> 00:06:03,120 Ejaaz: content on the video side with VO, on the image side with Nano Banana, 98 00:06:03,300 --> 00:06:07,080 Ejaaz: and on the scientific discovery side with the Alpha Gemini series. 99 00:06:07,520 --> 00:06:10,660 Ejaaz: Just taking a look at this benchmark setup that I have here, 100 00:06:10,760 --> 00:06:13,700 Ejaaz: this is something that we've started to see with every Gemini model release, 101 00:06:13,800 --> 00:06:17,120 Ejaaz: which is they're frequently and consistently at the top, Josh. 102 00:06:17,280 --> 00:06:20,380 Ejaaz: They're the number one LLM, they're the number one coding assistant, 103 00:06:20,540 --> 00:06:22,920 Ejaaz: and they're the number one agent provider as well. 104 00:06:23,020 --> 00:06:27,560 Ejaaz: And I think that this isn't by coincidence. They've worked very hard to kind 105 00:06:27,560 --> 00:06:32,700 Ejaaz: of like restructure Google from this corporate kind of bloat, 106 00:06:32,840 --> 00:06:35,860 Ejaaz: which they typically had up until AI became a running thing, 107 00:06:36,260 --> 00:06:39,480 Ejaaz: into this like frontier AI tech lab that is constantly innovating, 108 00:06:39,640 --> 00:06:43,520 Ejaaz: changing, and adapting their strategies, given whatever the environment they're faced with. 109 00:06:43,700 --> 00:06:48,140 Ejaaz: So they consistently have the best AI models, but it's also worth explaining 110 00:06:48,140 --> 00:06:51,920 Ejaaz: how they've translated this into user dominance. 111 00:06:52,180 --> 00:06:56,380 Ejaaz: So typically how OpenAI and ChatGPT has done this is they've created a model 112 00:06:56,380 --> 00:06:59,440 Ejaaz: and then they've pioneered basically the chat interface, right? 113 00:06:59,800 --> 00:07:04,260 Ejaaz: They then did the same for text to video into Sora. So they've done a really 114 00:07:04,260 --> 00:07:06,820 Ejaaz: good job of surfacing this to new users. 115 00:07:07,100 --> 00:07:11,280 Ejaaz: Now, Google already has these users and they've done a great job of doing the same thing. 116 00:07:11,440 --> 00:07:14,900 Ejaaz: They've integrated AI into their search. So whenever you search anything on 117 00:07:14,900 --> 00:07:18,140 Ejaaz: Google now, you have something called an AI overview, Josh. 118 00:07:18,340 --> 00:07:22,400 Ejaaz: And something that I learned just this morning, which they released from their 119 00:07:22,400 --> 00:07:27,940 Ejaaz: quarterly report last week, is the monetization rate of this AI search, 120 00:07:27,980 --> 00:07:29,480 Ejaaz: which comes up at the top of their. 121 00:07:30,040 --> 00:07:36,440 Ejaaz: Infamous Google search page is monetizing at the same rate as their search links 122 00:07:36,440 --> 00:07:39,560 Ejaaz: themselves, which is just a crazy undertaking, right? 123 00:07:39,660 --> 00:07:43,400 Ejaaz: Because you would think that Google is killing their own monopoly in search 124 00:07:43,400 --> 00:07:46,560 Ejaaz: by doing something like this, but it turns out that it's actually aiding and 125 00:07:46,560 --> 00:07:49,680 Ejaaz: probably going to offer them more profits going forwards. 126 00:07:50,020 --> 00:07:53,200 Ejaaz: The other thing is they have this whole AI productivity suite, 127 00:07:53,420 --> 00:07:55,500 Ejaaz: which they surface all these different models and features. 128 00:07:55,780 --> 00:07:59,420 Ejaaz: So I guess the point that I'm trying to make is Google isn't just a model creator, 129 00:08:00,100 --> 00:08:03,080 Ejaaz: are a product creator they understand their audience both 130 00:08:03,080 --> 00:08:05,800 Ejaaz: from the enterprise side and the consumer side and i 131 00:08:05,800 --> 00:08:08,840 Ejaaz: think it's highly undervalued and very misunderstood 132 00:08:08,840 --> 00:08:14,240 Ejaaz: that at how good google is at doing that job but what's probably surprising 133 00:08:14,240 --> 00:08:19,900 Ejaaz: to most is one of their products comes in the form of hardware uh their equivalent 134 00:08:19,900 --> 00:08:26,960 Ejaaz: of the gpu called the tpu which has added unlikely the most value to Google's market cap? 135 00:08:27,120 --> 00:08:30,960 Josh: Yeah, TPUs are amazing. And I'm going to do my best to try to explain TPU versus 136 00:08:30,960 --> 00:08:34,940 Josh: GPUs because on the surface, it seems a little confusing, but I think we can simplify it quite a bit. 137 00:08:35,680 --> 00:08:40,100 Josh: Ijus, I want you to imagine a GPU being a chef, a chef who is a master chef, 138 00:08:40,220 --> 00:08:42,760 Josh: who can cook anything and can make anything that you imagine. 139 00:08:42,940 --> 00:08:45,860 Josh: But the reality is that you and myself and the rest of the world, 140 00:08:46,000 --> 00:08:47,120 Josh: we only really want sandwiches. 141 00:08:47,380 --> 00:08:50,800 Josh: So while a chef can make a sandwich, it will take a little bit longer to make a sandwich. 142 00:08:51,200 --> 00:08:54,400 Josh: That is what a GPU does. It can cook you anything you like, But the reality 143 00:08:54,400 --> 00:08:55,940 Josh: is most of the world wants sandwiches. 144 00:08:56,180 --> 00:08:59,360 Josh: A TPU, you can imagine, instead of being a general purpose chef, 145 00:08:59,500 --> 00:09:01,400 Josh: is a production line for sandwiches. 146 00:09:01,640 --> 00:09:05,860 Josh: It is a singular line that has all of the ingredients on top of it to hyper-efficiently 147 00:09:05,860 --> 00:09:07,340 Josh: make sandwiches for the whole world. 148 00:09:07,440 --> 00:09:10,340 Josh: And because the world doesn't want salmon, they don't want steak, 149 00:09:10,440 --> 00:09:14,340 Josh: they just want sandwiches, this production line is much more efficient at making sandwiches. 150 00:09:14,620 --> 00:09:17,500 Josh: So while the GPU can do everything, and a lot of people want a GPU, 151 00:09:17,900 --> 00:09:21,060 Josh: people who are training hardcore AI, they just want a TPU. 152 00:09:21,060 --> 00:09:25,500 Josh: It's called a tensor processing unit, and it is this hyper-focused piece of 153 00:09:25,500 --> 00:09:30,200 Josh: hardware built to perform this thing called matrix math, which a lot of AI hardware is built upon. 154 00:09:30,400 --> 00:09:34,600 Josh: So what is so effective about these TPUs? Well, there's two ways of measuring 155 00:09:34,600 --> 00:09:36,260 Josh: GPU, CPU, compute in general. 156 00:09:36,420 --> 00:09:38,880 Josh: It's performance per watt, and it is cost per token. 157 00:09:39,140 --> 00:09:43,940 Josh: So performance per watt is two times that of the NVIDIA A100s, 158 00:09:44,020 --> 00:09:45,680 Josh: which is one of their leading flagships of chips. 159 00:09:46,040 --> 00:09:51,580 Josh: That means that for every watt of energy you apply, you get double the amount of performance back. 160 00:09:51,990 --> 00:09:55,870 Josh: The other one is cost per token. So for every dollar you spend, 161 00:09:56,090 --> 00:09:57,870 Josh: this is how many tokens you can yield. 162 00:09:58,050 --> 00:10:01,850 Josh: And it's about one and a half to two times better performance per token than 163 00:10:01,850 --> 00:10:04,590 Josh: NVIDIA GPUs. So these TPUs are remarkable. 164 00:10:04,850 --> 00:10:08,050 Josh: They work really, really well. And the question I asked myself when I was going 165 00:10:08,050 --> 00:10:11,130 Josh: through this is, well, why does the whole world not use TPUs? 166 00:10:11,390 --> 00:10:15,390 Josh: Well, the first answer is they actually don't sell them. Google just owns the 167 00:10:15,390 --> 00:10:16,810 Josh: TPU. It is a Google invention. 168 00:10:17,030 --> 00:10:20,150 Josh: They own them, they use them for their own stack, and they vertically integrate 169 00:10:20,150 --> 00:10:21,890 Josh: it through the software. so it's hyper-performance. 170 00:10:22,070 --> 00:10:24,470 Josh: And it's kind of like what we see with Apple chips with the M-Series. 171 00:10:24,550 --> 00:10:27,270 Josh: I always reference the M-Series because it's amazing, is that they've built 172 00:10:27,270 --> 00:10:29,710 Josh: this chip hyper-optimized for their exact production workflow. 173 00:10:29,910 --> 00:10:33,270 Josh: And as a result, the cost efficiencies, performance efficiencies, 174 00:10:33,450 --> 00:10:35,130 Josh: every proficiency is through the roof. 175 00:10:35,330 --> 00:10:38,690 Josh: So that's kind of how I would describe the TPU to a layman. That's kind of how 176 00:10:38,690 --> 00:10:41,610 Josh: I learned it myself. And hopefully that description makes sense. 177 00:10:41,770 --> 00:10:45,790 Ejaaz: That makes a lot of sense. Although I have one slight pushback for you, Josh, 178 00:10:45,930 --> 00:10:48,810 Ejaaz: which is as of last week, they have 179 00:10:48,810 --> 00:10:52,150 Ejaaz: started to sell their tpus to a 180 00:10:52,150 --> 00:10:55,670 Ejaaz: little known ai company uh known as anthropic um 181 00:10:55,670 --> 00:10:58,910 Ejaaz: supposedly the deal is marked at 50 billion dollars 182 00:10:58,910 --> 00:11:02,170 Ejaaz: which doubles their compute offering uh 183 00:11:02,170 --> 00:11:06,870 Ejaaz: from revenue earnings on the year uh so if this deal actually goes through this 184 00:11:06,870 --> 00:11:13,690 Ejaaz: will be the first major gpu sale that has sat outside of nvidia's remit so i 185 00:11:13,690 --> 00:11:19,290 Ejaaz: already know jensen's fuming uh at the head but we will see whether Google takes this seriously. 186 00:11:19,450 --> 00:11:22,150 Ejaaz: I mean, to your point, I don't know if Google has the... 187 00:11:23,310 --> 00:11:27,650 Ejaaz: Manufacturing capability or even the ambition to scale TPUs in the way that 188 00:11:27,650 --> 00:11:29,390 Ejaaz: NVIDIA is done with GPUs. 189 00:11:29,710 --> 00:11:33,370 Ejaaz: I see kind of two major constraints. Number one, Google's just focused on so 190 00:11:33,370 --> 00:11:37,130 Ejaaz: many other things and NVIDIA is like hyper-focused on doing this one thing really well. 191 00:11:37,490 --> 00:11:41,610 Ejaaz: And number two, TPUs, as you said, are highly specific and custom. 192 00:11:41,790 --> 00:11:46,970 Ejaaz: So I'm guessing that the TPUs that they're selling to Anthropic in this deal are very specific. 193 00:11:47,190 --> 00:11:50,910 Ejaaz: Maybe that's a niche that they can kind of take forward, but I don't think it 194 00:11:50,910 --> 00:11:52,490 Ejaaz: could grow as large as NVIDIA. 195 00:11:52,790 --> 00:11:55,490 Ejaaz: Do you think I'm wrong or do you think they're knocking trillions of dollars 196 00:11:55,490 --> 00:11:57,350 Ejaaz: of market cap off of NVIDIA soon? 197 00:11:57,470 --> 00:12:01,830 Josh: Yeah, well, there's two cases. There's one in which you believe TPUs are the next form of GPU. 198 00:12:01,990 --> 00:12:04,170 Josh: It's like a natural extension where everyone's going to want to buy these. 199 00:12:04,290 --> 00:12:06,950 Josh: In that case, if they could do these production at scale, well, 200 00:12:07,090 --> 00:12:10,330 Josh: they will, yeah, they can knock off a trillion or two off of NVIDIA's market cap, sure. 201 00:12:10,890 --> 00:12:15,330 Josh: The reality is, is that I don't believe they are direct Apple to Apple's comparison. 202 00:12:15,350 --> 00:12:18,450 Josh: There's a lot of different types of training that NVIDIA GPUs are good for. the per 203 00:12:18,450 --> 00:12:21,930 Josh: per watt of gpus from nvidia are still higher nvidia 204 00:12:21,930 --> 00:12:25,650 Josh: is still innovating faster they have access to the most cutting edge lithography which 205 00:12:25,650 --> 00:12:28,590 Josh: happens only in a few places in taiwan they really 206 00:12:28,590 --> 00:12:31,370 Josh: have this monopoly on the supply chain that google just can't really compete 207 00:12:31,370 --> 00:12:36,190 Josh: with but google can supplement a lot more compute so to the point of jevin's 208 00:12:36,190 --> 00:12:41,070 Josh: paradox where compute will just expand to the emptiness that there is around 209 00:12:41,070 --> 00:12:45,770 Josh: it um there's no supply demand shortage for these processing units, 210 00:12:45,770 --> 00:12:47,330 Josh: whether they be tensor or graphical. 211 00:12:47,570 --> 00:12:51,450 Josh: And if Google can start selling them, that just opens up another pillar for Google. 212 00:12:51,590 --> 00:12:55,970 Josh: I'm not sure it necessarily hurts NVIDIA, but it allows Google to just make 213 00:12:55,970 --> 00:12:57,530 Josh: more money and print more cash. 214 00:12:57,590 --> 00:13:01,870 Josh: And I think that's a big win for a company that really hasn't made money off 215 00:13:01,870 --> 00:13:05,250 Josh: of the infrastructure play yet, but now has a very clear opportunity to do so. 216 00:13:05,860 --> 00:13:09,840 Ejaaz: Yeah, I mean, I'm just looking at this tweet here. Morgan Stanley kind of like 217 00:13:09,840 --> 00:13:14,800 Ejaaz: up their price and prediction for Google stock in 2026. 218 00:13:15,240 --> 00:13:21,580 Ejaaz: But one thing that really caught my eye is the $158 billion backlog that they 219 00:13:21,580 --> 00:13:24,380 Ejaaz: currently have for their cloud offering. 220 00:13:24,720 --> 00:13:28,040 Ejaaz: And it got me thinking that like, Google has always been a powerhouse when it 221 00:13:28,040 --> 00:13:32,160 Ejaaz: has come to like infrastructure provision and they've done so really well with 222 00:13:32,160 --> 00:13:33,720 Ejaaz: GCP, their cloud product. 223 00:13:34,240 --> 00:13:36,940 Ejaaz: You could also argue the same of Microsoft, Azure. 224 00:13:37,600 --> 00:13:41,420 Ejaaz: Both of these companies have signed major deals, Microsoft and Google, 225 00:13:41,600 --> 00:13:45,080 Ejaaz: in the last two weeks for AI-specific stuff, not just training, 226 00:13:45,200 --> 00:13:46,320 Ejaaz: but also inference costs. 227 00:13:46,520 --> 00:13:50,080 Ejaaz: So I see this like growing trend, Josh, of like infrastructure, 228 00:13:50,420 --> 00:13:54,760 Ejaaz: whether it's chips or just kind of like cloud services, getting really in demand 229 00:13:54,760 --> 00:13:56,920 Ejaaz: as we kind of like scale these AI models up. 230 00:13:57,020 --> 00:14:01,420 Ejaaz: So I don't know, I'm super excited to see where this goes. The final thing is 231 00:14:01,420 --> 00:14:04,000 Ejaaz: Google is just everywhere. 232 00:14:04,440 --> 00:14:07,980 Ejaaz: They are the doorstep to the internet and actually the entire house. 233 00:14:08,420 --> 00:14:11,940 Ejaaz: You know, they run Gemini, they're models, they have the TPU chips, 234 00:14:12,080 --> 00:14:16,060 Ejaaz: which we just mentioned, but they also handle 90% of search. 235 00:14:16,260 --> 00:14:18,460 Ejaaz: They run YouTube, the number one entertainment in the world. 236 00:14:18,600 --> 00:14:22,060 Ejaaz: They have Google Maps, they have Android, they power all Android devices. 237 00:14:22,400 --> 00:14:27,760 Ejaaz: It is just a very gluttonous monopoly that Google has that extends way beyond 238 00:14:27,760 --> 00:14:31,860 Ejaaz: just a simple search engine. And the point I wanna make around here is that 239 00:14:31,860 --> 00:14:35,940 Ejaaz: is a crazy positive feedback loop to when you're creating AI models. 240 00:14:36,120 --> 00:14:40,240 Ejaaz: They have all the data, they have all the compute in-house, so they don't have 241 00:14:40,240 --> 00:14:44,240 Ejaaz: to rely on that tiny island in Taiwan and on Nvidia's dominance here. 242 00:14:44,460 --> 00:14:48,340 Ejaaz: And then they have all the apps to surface that through a very monetizable audience. 243 00:14:48,420 --> 00:14:50,140 Ejaaz: We're talking about billions of users here. 244 00:14:50,280 --> 00:14:53,960 Ejaaz: So whereas OpenAI has to kind of build their audience from scratch and they've 245 00:14:53,960 --> 00:14:56,940 Ejaaz: done so very impressively to 800 million weekly active users, 246 00:14:57,330 --> 00:15:00,750 Ejaaz: Google kind of already had that waiting and ready to go. And they've proven 247 00:15:00,750 --> 00:15:04,330 Ejaaz: that, right? In their quarterly earnings, they have 650 million weekly active users. 248 00:15:04,490 --> 00:15:08,210 Ejaaz: I'm guessing the next quarter, that's going to, you know, increase by at least a third. 249 00:15:08,390 --> 00:15:12,310 Ejaaz: So the point is, Google's dominance extends way beyond a search engine. 250 00:15:12,390 --> 00:15:15,570 Ejaaz: I don't think people are very aware of that. And I think that is one of the 251 00:15:15,570 --> 00:15:17,730 Ejaaz: biggest bull cases for their stock going forwards. 252 00:15:18,310 --> 00:15:23,750 Ejaaz: A counter argument that I've heard to this, Josh, is that they just simply won't execute as well. 253 00:15:24,030 --> 00:15:27,110 Ejaaz: I would agree with you, except that the data tells us otherwise. 254 00:15:27,110 --> 00:15:30,890 Ejaaz: If you look at this chart over here, the retention rate, the three-month retention 255 00:15:30,890 --> 00:15:35,450 Ejaaz: rate, specifically for Google Gemini AI models, has been up and to the right. 256 00:15:35,690 --> 00:15:40,110 Ejaaz: It is pretty insane. We're talking about 90% the three-month retention rate 257 00:15:40,110 --> 00:15:45,970 Ejaaz: and six-month retention rate of 85%. That is staggering for any kind of consumer internet product. 258 00:15:45,970 --> 00:15:48,850 Josh: So you just you've laid out a pretty bullish case 259 00:15:48,850 --> 00:15:51,930 Josh: for google and i'm not sure that mismatches the public perception as 260 00:15:51,930 --> 00:15:54,770 Josh: of late i think that's changed a lot people really hated google but 261 00:15:54,770 --> 00:15:57,630 Josh: they're starting to come around see the light it's trading just beneath all-time highs 262 00:15:57,630 --> 00:16:01,910 Josh: and it very vividly reminds me of another company of about the same size a little 263 00:16:01,910 --> 00:16:06,750 Josh: bit bigger that has it's sitting at all-time highs but there is a very like 264 00:16:06,750 --> 00:16:10,450 Josh: gross disconnect between public sentiment and the company and that's apple um 265 00:16:10,450 --> 00:16:13,390 Josh: there's this post on the screen here that says what the hell is apple doing. 266 00:16:13,550 --> 00:16:15,470 Josh: They failed to make a car. They have no AI investments. 267 00:16:15,750 --> 00:16:19,950 Josh: Siri still sucks. Just releasing the same phone over and over again. How can you miss AI? 268 00:16:20,250 --> 00:16:24,470 Josh: How is that even possible? And Sean, to your point, I agree. 269 00:16:24,710 --> 00:16:27,390 Josh: They've actually, they've swung and missed on just about everything they've 270 00:16:27,390 --> 00:16:32,190 Josh: tried recently. And it's been a big disappointment, but the stock is trading at all time highs. 271 00:16:32,350 --> 00:16:36,750 Josh: So where is this disconnect coming from? How can one group of the internet be 272 00:16:36,750 --> 00:16:38,850 Josh: so polarized against the other group? 273 00:16:39,070 --> 00:16:42,490 Josh: And where all the money is going is clearly into Apple because Apple is trading 274 00:16:42,490 --> 00:16:45,830 Josh: like 4 point something trillion dollar market caps. It's a gigantic company. 275 00:16:46,630 --> 00:16:52,370 Josh: There's a few ways to think about this. And one that I really like is around local inference. 276 00:16:52,650 --> 00:16:56,290 Josh: So the way AI works, and granted, this is kind of funny because 277 00:16:56,760 --> 00:17:00,940 Josh: I think Apple accidentally stumbled upon this conclusion, but I'm going to purvey 278 00:17:00,940 --> 00:17:02,800 Josh: it as if this was all by design. 279 00:17:03,080 --> 00:17:06,960 Josh: There's two kind of ways that companies handle compute. There's cloud-based 280 00:17:06,960 --> 00:17:09,400 Josh: compute, and then there's edge inference that happens. 281 00:17:09,580 --> 00:17:13,160 Josh: So one happens in a data center in a remote place. That's what we see all the 282 00:17:13,160 --> 00:17:16,140 Josh: pictures of, these gigantic factories that have a bunch of GPUs. 283 00:17:16,360 --> 00:17:19,220 Josh: And the other happens locally on your device, whether it be your smartphone 284 00:17:19,220 --> 00:17:22,400 Josh: or your laptop or your desktop, whatever device it may be, 285 00:17:22,800 --> 00:17:25,740 Josh: compute happens locally on that device compute on a local device 286 00:17:25,740 --> 00:17:29,600 Josh: is free compute in a cloud costs money so what 287 00:17:29,600 --> 00:17:32,660 Josh: is apple doing well apple just released a new mac 288 00:17:32,660 --> 00:17:37,420 Josh: mini um which we have a post about here the m3 mac ultra studio or i guess that's 289 00:17:37,420 --> 00:17:40,960 Josh: what it's called is the only device which you can run open source state-of-the-art 290 00:17:40,960 --> 00:17:44,960 Josh: models outside of a data center and that seems strange because there's a lot 291 00:17:44,960 --> 00:17:48,200 Josh: of really powerful gpus there's a lot of really powerful computers but the only 292 00:17:48,200 --> 00:17:51,240 Josh: ones that actually allow you to run these are these Macs. 293 00:17:51,340 --> 00:17:56,500 Josh: Why is that? Well, it's because Apple owns the chips, and they've optimized these chips for AI. 294 00:17:56,740 --> 00:17:59,860 Josh: So even though there is an absence of AI currently running on Apple devices, 295 00:18:00,100 --> 00:18:04,060 Josh: they are fully compute capable of running these very impressive models from 296 00:18:04,060 --> 00:18:06,260 Josh: anything on a Mac Studio down to your iPhone, 297 00:18:06,280 --> 00:18:12,100 Josh: which leads us to the bull case of Apple being they are not subject to a lot 298 00:18:12,100 --> 00:18:15,820 Josh: of the swings that we see in public markets, because they're not investing all of the CapEx. 299 00:18:15,820 --> 00:18:20,000 Josh: Now, EJS, if you'll remember, there was a deal struck between Google and Apple in the past. 300 00:18:20,080 --> 00:18:23,040 Josh: This is not the first time they've worked together. And that was for Google search. 301 00:18:23,700 --> 00:18:25,760 Josh: Back in the day, I think we have a post somewhere about this. 302 00:18:26,000 --> 00:18:29,200 Josh: Yeah, here's a post from EJS. You dug this up from 2018, I think. 303 00:18:30,240 --> 00:18:33,900 Josh: How much is your data worth? So much that Google just paid Apple $9 billion 304 00:18:33,900 --> 00:18:37,700 Josh: to be the default search engine in the iPhone. $9 billion to get people... 305 00:18:38,350 --> 00:18:42,750 Josh: To use a free search. Well, that number has actually jumped to 20 billion as 306 00:18:42,750 --> 00:18:44,910 Josh: of as late as 2022 was the most confirmed number. 307 00:18:45,170 --> 00:18:48,290 Josh: And it's just an outrageous amount of money to spend. But I don't think this 308 00:18:48,290 --> 00:18:49,690 Josh: is the last time they're going to work with each other. 309 00:18:49,830 --> 00:18:53,570 Josh: So Ejas, this week we got some news that there is a new deal on the table. 310 00:18:53,570 --> 00:18:55,270 Josh: And this isn't a search related deal. 311 00:18:55,370 --> 00:18:57,850 Josh: This is instead an AI related deal. 312 00:18:58,130 --> 00:19:03,170 Ejaaz: Yeah, this is like Google and Apple deal 2.0. And it's so much bigger. 313 00:19:03,430 --> 00:19:09,110 Ejaaz: And it's back better than ever, right? So this week, we had news break that 314 00:19:09,110 --> 00:19:14,950 Ejaaz: Apple has asked Google to create their own Gemini model just for Apple users 315 00:19:14,950 --> 00:19:16,950 Ejaaz: that will run on their private cloud. 316 00:19:17,310 --> 00:19:19,550 Ejaaz: Josh, can you break this down for me? What's going on here? 317 00:19:19,950 --> 00:19:24,150 Josh: This is amazingly important. So everybody and their mother is spending trillions 318 00:19:24,150 --> 00:19:26,710 Josh: of dollars of capital building AI data centers. 319 00:19:27,310 --> 00:19:30,990 Josh: OpenAI is spending trillions, Google, Microsoft, name anybody they're spending 320 00:19:30,990 --> 00:19:33,950 Josh: trillions of dollars. There's a question that we frequently ask ourselves on 321 00:19:33,950 --> 00:19:37,850 Josh: the show and public markets are asking, is there a bubble? When is this bubble going to burst? 322 00:19:38,150 --> 00:19:42,110 Josh: How much CapEx is appropriate before you just can't justify the returns on your investment? 323 00:19:43,230 --> 00:19:48,290 Josh: Apple, in a way, in a funny messed up roundabout way, is completely immune to 324 00:19:48,290 --> 00:19:52,030 Josh: these swings, to this capital expenditure, and to this bubble exposure because 325 00:19:52,030 --> 00:19:55,490 Josh: they have not invested much money into building out the resources needed to 326 00:19:55,490 --> 00:19:56,830 Josh: train their own supermodels. 327 00:19:57,230 --> 00:20:01,230 Josh: What they're doing now is a very clear and obvious answer. is they're actually 328 00:20:01,230 --> 00:20:04,450 Josh: offloading that responsibility, offloading the financial risk to Google. 329 00:20:04,590 --> 00:20:08,170 Josh: And they're going to pay them X amount of dollars in order for Google Gemini 330 00:20:08,170 --> 00:20:10,830 Josh: to create a custom model for the Apple ecosystem. 331 00:20:10,890 --> 00:20:14,210 Josh: And I think this is a really powerful thing because we mentioned a little bit 332 00:20:14,210 --> 00:20:16,430 Josh: earlier, there's cloud and then there's local compute. 333 00:20:16,610 --> 00:20:20,710 Josh: And the local compute is actually sufficient enough to create a custom model. 334 00:20:21,380 --> 00:20:24,820 Josh: Don't suffice for a lot of requests that people have. I think a lot of prompts, 335 00:20:24,960 --> 00:20:27,300 Josh: and we talked about this a lot where with cutting edge models, 336 00:20:27,460 --> 00:20:30,220 Josh: I'm not even sure how to really test them because just my requests, 337 00:20:30,360 --> 00:20:32,700 Josh: my needs from an AI model aren't cutting edge. 338 00:20:32,840 --> 00:20:36,620 Josh: They don't need massive amounts of compute or tokens or resources to solve my problems. 339 00:20:36,780 --> 00:20:39,620 Josh: A lot of the times I'm just like, I need help navigating my day. 340 00:20:39,740 --> 00:20:42,900 Josh: I have a lot going on. I need to know like what, what times am I able to do things? 341 00:20:43,120 --> 00:20:46,500 Josh: And the thing with Apple is it actually has all this intelligence. 342 00:20:46,680 --> 00:20:50,460 Josh: And this was the promise with apple intelligence we just never got um but by 343 00:20:50,460 --> 00:20:54,540 Josh: all floating into gemini we start to see these unlocks where apple's the only 344 00:20:54,540 --> 00:20:58,140 Josh: one that has more context than open ai and it does we think about memory a lot 345 00:20:58,140 --> 00:21:02,620 Josh: and context and how powerful it is for a system and what device what system 346 00:21:02,620 --> 00:21:06,400 Josh: have you been using longer than chat gpt that has more info about you what's your smartphone 347 00:21:06,880 --> 00:21:10,340 Josh: and a lot of people will be reluctant to give up that data but in the case that 348 00:21:10,340 --> 00:21:14,040 Josh: it is private and it runs locally and it's able to take all the context from 349 00:21:14,040 --> 00:21:16,820 Josh: your device that creates this really powerful edge compute. 350 00:21:16,980 --> 00:21:20,560 Josh: And that's kind of part one of the bull case for Apple. So I'll stop there to 351 00:21:20,560 --> 00:21:24,140 Josh: see if you disagree, agree. This is like, we're getting into the weeds here a little bit. 352 00:21:24,660 --> 00:21:29,340 Ejaaz: I mean, as you know, I've been one of the biggest bears against Apple for almost a year now. 353 00:21:29,680 --> 00:21:30,560 Josh: And rightfully so. 354 00:21:31,040 --> 00:21:36,440 Ejaaz: Yeah, yeah. I think they've done a terrible job. But as you pointed out, this works both ways. 355 00:21:36,640 --> 00:21:41,000 Ejaaz: They've effectively shielded themselves from the crazy fluctuations that you 356 00:21:41,000 --> 00:21:44,860 Ejaaz: can see in AI, specifically in CapEx, right? So they're not investing trillions of dollars. 357 00:21:45,120 --> 00:21:49,040 Ejaaz: But also when that rollercoaster ride starts going down, they're shielded, 358 00:21:49,180 --> 00:21:51,300 Ejaaz: they're affected from it and they can pick and choose the winners. 359 00:21:51,400 --> 00:21:54,980 Ejaaz: There's also the argument that like all this AI CapEx investment is kind of 360 00:21:54,980 --> 00:21:59,240 Ejaaz: a race to the bottom because whoever gets to AGI first is gonna absolutely disrupt 361 00:21:59,240 --> 00:22:00,980 Ejaaz: and destroy any other competitor. 362 00:22:01,480 --> 00:22:04,780 Ejaaz: An argument that you could potentially give. The other side of it is, 363 00:22:05,200 --> 00:22:09,240 Ejaaz: Josh, I really like your point around the personalization and localization and 364 00:22:09,240 --> 00:22:12,900 Ejaaz: the importance of privacy of having your model on your own device. 365 00:22:13,080 --> 00:22:19,180 Ejaaz: Who cares if there's a general query that can be answered by some research professor versus an AI model? 366 00:22:19,340 --> 00:22:22,920 Ejaaz: I want it to be able to read my text and understand the next thing I'm going to text. 367 00:22:23,080 --> 00:22:26,440 Ejaaz: I want it to be able to download the apps ahead of me even knowing about the 368 00:22:26,440 --> 00:22:30,480 Ejaaz: apps and do the things for me. That's only going to work on personalized devices. 369 00:22:30,840 --> 00:22:33,120 Ejaaz: And as you said, Apple has the distribution. 370 00:22:33,400 --> 00:22:36,660 Josh: Yeah, the use cases for local inference are kind of remarkable when you think 371 00:22:36,660 --> 00:22:38,740 Josh: about having access to all of your texts or emails. 372 00:22:39,220 --> 00:22:41,620 Josh: There's a second thing to this also, which is cost. 373 00:22:42,420 --> 00:22:45,340 Josh: If you remember in a previous episode, we covered Grok Nano, 374 00:22:45,800 --> 00:22:50,060 Josh: which was this very lightweight, very easy to use, very low cost model, 375 00:22:50,200 --> 00:22:54,320 Josh: and how within days of it being released, it went to the very top of all the 376 00:22:54,320 --> 00:22:55,180 Josh: charts in terms of usage. 377 00:22:55,680 --> 00:22:59,740 Josh: Every developer in the world wanted to use it because it was fast and it was cheap. 378 00:22:59,900 --> 00:23:04,200 Josh: And one of the trends that we see as AI develops over time is this race to the bottom. 379 00:23:04,360 --> 00:23:07,640 Josh: The cost per token, the race to zero is fairly aggressive. 380 00:23:07,640 --> 00:23:11,700 Josh: And what Apple's done is they've kind of cheated and they've gone from the starting 381 00:23:11,700 --> 00:23:15,640 Josh: line directly to the finish line without doing the work in between because inference 382 00:23:15,640 --> 00:23:20,640 Josh: on a local device that has an M-series chip or an A-series chip that Apple has is completely free. 383 00:23:20,640 --> 00:23:24,020 Josh: It costs $0 to run a query on these local devices. 384 00:23:24,220 --> 00:23:26,640 Josh: And there's billions of them that are capable of doing this. 385 00:23:26,760 --> 00:23:29,860 Josh: So if you're a developer who wants to build a great experience for a customer, 386 00:23:30,100 --> 00:23:33,860 Josh: there is absolutely no reason why you shouldn't be building for Apple devices 387 00:23:33,860 --> 00:23:36,140 Josh: because the inference costs are free. 388 00:23:36,300 --> 00:23:38,920 Josh: And a lot of these developers who are building applications for the world of 389 00:23:38,920 --> 00:23:41,700 Josh: AI, they're bringing these servers. They're constantly looking for the next 390 00:23:41,700 --> 00:23:43,880 Josh: cheapest one because they want to keep the cost down. 391 00:23:44,100 --> 00:23:47,000 Josh: But if you just throw an app in the App Store that runs on these local models 392 00:23:47,000 --> 00:23:49,660 Josh: that Apple will hopefully produce in partnership with Google, 393 00:23:50,080 --> 00:23:54,660 Josh: You suddenly tap into this gigantic context window, this gigantic bay of memory, 394 00:23:54,720 --> 00:23:57,700 Josh: and it costs you absolutely zero dollars to do. 395 00:23:57,880 --> 00:24:01,560 Josh: And I think market forces will kind of come into play at some point here where 396 00:24:01,560 --> 00:24:05,660 Josh: just the natural tendency to trend towards lower prices will allow a lot more 397 00:24:05,660 --> 00:24:08,180 Josh: developer adoption and to create the experiences on top. 398 00:24:08,320 --> 00:24:12,340 Josh: So while Apple completely and utterly failed at AI version one with Siri, 399 00:24:12,500 --> 00:24:16,840 Josh: it is an abomination. It is the worst AI product of any major company by far. 400 00:24:16,980 --> 00:24:20,320 Josh: And I don't want to get that twisted. they may have accidentally 401 00:24:20,320 --> 00:24:25,480 Josh: just by the fact of vertically integrating these chips stumbled into the best 402 00:24:25,480 --> 00:24:29,540 Josh: case scenario where everybody's spending a bunch of money everyone is trying 403 00:24:29,540 --> 00:24:34,240 Josh: to build the ai first get the user second apple has all the users and they have 404 00:24:34,240 --> 00:24:39,180 Josh: all the data they just need the ai to plug into it and google could be that person to do so yeah 405 00:24:39,180 --> 00:24:42,840 Ejaaz: It's super smart i think the market is finally recognizing that if i were to 406 00:24:42,840 --> 00:24:47,900 Ejaaz: boil all of this down to its core i would say that Apple is actually doing what 407 00:24:47,900 --> 00:24:50,260 Ejaaz: they've always done the best, 408 00:24:50,400 --> 00:24:54,400 Ejaaz: which is create the best consumer experience and products. 409 00:24:54,640 --> 00:24:57,840 Ejaaz: And so rather than jump into the infrastructure wars and the infrastructure 410 00:24:57,840 --> 00:25:01,100 Ejaaz: race in AI with GPUs, they let everyone else do it. 411 00:25:01,320 --> 00:25:05,000 Ejaaz: They cherry pick the best, and then they integrate it in the best, 412 00:25:05,240 --> 00:25:08,560 Ejaaz: most artful way for their own products and services. 413 00:25:08,740 --> 00:25:13,280 Ejaaz: And that's why they have the addicted audience that they have, right? 414 00:25:13,360 --> 00:25:17,560 Ejaaz: I buy iPhones practically every single well, you're having MacBooks at this point. 415 00:25:17,680 --> 00:25:20,920 Ejaaz: I'm addicted to the Apple brand. And there's a reason behind that because it 416 00:25:20,920 --> 00:25:23,100 Ejaaz: has the best all-in consumer experience. 417 00:25:23,340 --> 00:25:26,520 Ejaaz: And that's what Apple knows that they have. And they can afford to basically 418 00:25:26,520 --> 00:25:29,880 Ejaaz: sign these deals and partnerships with the Googles of the world. 419 00:25:30,480 --> 00:25:34,440 Ejaaz: Another thing that I find interesting about this, Josh, is in this case, 420 00:25:34,600 --> 00:25:37,740 Ejaaz: they're paying Google to create their own AI model for them, 421 00:25:37,840 --> 00:25:41,020 Ejaaz: which seems like an L on the balance sheet for Apple. 422 00:25:41,200 --> 00:25:46,080 Ejaaz: But if you play this out, Gemini and Google are definitely going to build their 423 00:25:46,080 --> 00:25:51,380 Ejaaz: own agent, right, which is going to use a bunch of apps and they need to get 424 00:25:51,380 --> 00:25:54,780 Ejaaz: access to billions of consumers. Who has that? 425 00:25:55,340 --> 00:25:59,180 Ejaaz: Apple. I know Google already has it across an array of their different products 426 00:25:59,180 --> 00:26:01,340 Ejaaz: and apps that we explained earlier on. 427 00:26:01,580 --> 00:26:06,080 Ejaaz: But Apple has that addictive user experience that only operates at the hardware 428 00:26:06,080 --> 00:26:07,600 Ejaaz: level through the cellular device. 429 00:26:07,740 --> 00:26:12,580 Ejaaz: And if they maintain that lead, that could be a case for Google actually paying 430 00:26:12,580 --> 00:26:15,580 Ejaaz: Apple a hell of a lot more money to get access to this. 431 00:26:15,900 --> 00:26:18,120 Ejaaz: Is that fair? Is that crazy? Or have I got this wrong? 432 00:26:18,520 --> 00:26:21,620 Josh: Yeah, at the edge, it makes sense that the search thing happens 433 00:26:21,620 --> 00:26:24,740 Josh: again where okay apple owns the user experience 434 00:26:24,740 --> 00:26:27,500 Josh: google owns the software stack google winds up paying 435 00:26:27,500 --> 00:26:30,220 Josh: apple for the exposure um like i said before 436 00:26:30,220 --> 00:26:34,040 Josh: a lot of these companies they they have the intelligence they don't have the 437 00:26:34,040 --> 00:26:36,880 Josh: products they don't have the interface they don't have the trust or the users 438 00:26:36,880 --> 00:26:42,320 Josh: apple has that and by licensing technology from gemini they exclude themselves 439 00:26:42,320 --> 00:26:45,380 Josh: from all the capex fluctuations and the crazy amount of spending without a promised 440 00:26:45,380 --> 00:26:48,740 Josh: return in exchange for creating a a 441 00:26:49,300 --> 00:26:52,280 Josh: AI experience that is frankly the only one that I really want. 442 00:26:52,460 --> 00:26:56,620 Josh: The one that has all of my context. It can read all of my texts, all of my emails. 443 00:26:56,940 --> 00:26:59,900 Josh: It could be the personal assistant that no one else can be yet. 444 00:26:59,980 --> 00:27:01,360 Josh: And that's remarkably powerful. 445 00:27:01,560 --> 00:27:05,460 Josh: And if I want to outsource my thinking to an impressive AI, I could do that. 446 00:27:05,720 --> 00:27:08,700 Josh: And sure, Apple could probably ping some sort of API through Google or whoever 447 00:27:08,700 --> 00:27:09,820 Josh: they're partnered with, like OpenAI. 448 00:27:10,100 --> 00:27:14,860 Josh: But for most of my tasks, most of my AI needs, I just want a really helpful assistant. 449 00:27:15,060 --> 00:27:18,280 Josh: And no one can provide that better than an AI on my iPhone. 450 00:27:18,480 --> 00:27:22,960 Josh: And I think that's kind of the bull case in summary is as AI is able to remove 451 00:27:22,960 --> 00:27:26,960 Josh: themselves from CapEx, as they're able to implement local inference on all these 452 00:27:26,960 --> 00:27:30,460 Josh: devices for zero dollars, there's a lot of network effects that will probably 453 00:27:30,460 --> 00:27:31,320 Josh: come swinging their way. 454 00:27:31,420 --> 00:27:35,220 Josh: And maybe it was accidental, maybe it was by design, but the long tail effects 455 00:27:35,220 --> 00:27:37,620 Josh: of Apple's position right now seem fairly optimistic. 456 00:27:37,780 --> 00:27:40,880 Josh: And I think that's probably why it's priced sitting right at an all-time high 457 00:27:40,880 --> 00:27:42,600 Josh: right now, because we're not the only ones that think that. 458 00:27:42,820 --> 00:27:43,920 Josh: And that just about wraps it up. 459 00:27:44,020 --> 00:27:47,580 Josh: Why we think Google and Apple are both undervalued while at all-time high. 460 00:27:47,720 --> 00:27:51,200 Josh: And while perception might not always match public market sentiment and i think 461 00:27:51,200 --> 00:27:53,880 Josh: it's just it's important to continue to evaluate these companies like we said 462 00:27:53,880 --> 00:27:57,620 Josh: on yesterday's episode um these things matter a lot and how ai is implemented 463 00:27:57,620 --> 00:27:59,020 Josh: really matters a lot and it's changing 464 00:27:59,690 --> 00:28:02,790 Josh: Architecture of the world around us. So it's this exciting conversation we're 465 00:28:02,790 --> 00:28:03,830 Josh: going to continue having as we go. 466 00:28:04,050 --> 00:28:06,870 Josh: I just, as always, thank you so much for watching the episode. 467 00:28:07,010 --> 00:28:08,110 Josh: We really appreciate all the support. 468 00:28:08,450 --> 00:28:12,810 Josh: Things have been going well. In fact, so well that 85% of the people who watch 469 00:28:12,810 --> 00:28:16,570 Josh: this episode on YouTube are not subscribed, which is a problem. 470 00:28:16,750 --> 00:28:19,370 Josh: So if you are watching this and you are not subscribed, please go ahead, 471 00:28:19,810 --> 00:28:23,050 Josh: click that subscribe button and also listen to us wherever you find your podcast. 472 00:28:23,190 --> 00:28:27,230 Josh: One place we're struggling to grow is on the RSS feed on Spotify because it's 473 00:28:27,240 --> 00:28:30,840 Josh: kind of tough to get people to go there so if you listen and you want to support 474 00:28:30,840 --> 00:28:34,440 Josh: the show please go there subscribe on spotify subscribe on your rss feed wherever 475 00:28:34,440 --> 00:28:36,660 Josh: your player may be apple podcast even if 476 00:28:36,660 --> 00:28:40,620 Ejaaz: You don't want to listen if you're taking a shower just put it on play put it 477 00:28:40,620 --> 00:28:43,120 Ejaaz: in the other room it helps us out a lot. 478 00:28:43,120 --> 00:28:46,700 Josh: That's what my dad does it's great so yeah we just appreciate the support of 479 00:28:46,700 --> 00:28:49,300 Josh: whatever you can give all the comments it's been amazing we're coming off our 480 00:28:49,300 --> 00:28:52,840 Josh: best month ever and we continue to keep our foot on the gas thanks to all the 481 00:28:52,840 --> 00:28:56,680 Josh: support so thank you for watching as always we will see you in the next episode and peace