1 00:00:04,480 --> 00:00:12,440 Speaker 1: Welcome to Tech Stuff, a production from iHeartRadio. Hey there, 2 00:00:12,480 --> 00:00:15,840 Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland. 3 00:00:15,880 --> 00:00:19,159 Speaker 1: I'm an executive producer with iHeart Podcasts and how the 4 00:00:19,200 --> 00:00:23,320 Speaker 1: tech are you? So? Old time Star Trek fans may 5 00:00:23,400 --> 00:00:26,720 Speaker 1: both love and kind of cringe at the use of 6 00:00:26,760 --> 00:00:29,640 Speaker 1: some of the technobabble in scripts for that show. My 7 00:00:29,760 --> 00:00:33,280 Speaker 1: go to Star Trek tech Nonsense always includes the phrase 8 00:00:33,760 --> 00:00:37,920 Speaker 1: reverse the polarity, which typically doesn't mean very much in 9 00:00:38,000 --> 00:00:40,240 Speaker 1: most of the dialogue where it pops up, but it sounds, 10 00:00:40,240 --> 00:00:43,920 Speaker 1: you know, science adjacent. So I suppose, you know, we 11 00:00:43,960 --> 00:00:46,800 Speaker 1: should give writers some slack. They're trying to write stories 12 00:00:46,800 --> 00:00:49,160 Speaker 1: that are set in a far off future about technology 13 00:00:49,200 --> 00:00:51,680 Speaker 1: that really we can only dream about today. I still 14 00:00:51,680 --> 00:00:54,320 Speaker 1: want a replicator, though. Just look at how far the 15 00:00:54,360 --> 00:00:57,080 Speaker 1: tech world has come, however, since the original Star Trek 16 00:00:57,160 --> 00:01:01,120 Speaker 1: series first broadcast back in nineteen sixty. But you don't 17 00:01:01,120 --> 00:01:02,960 Speaker 1: have to go to the future to encounter plenty of 18 00:01:03,080 --> 00:01:07,240 Speaker 1: jargon and buzzwords. They're all over the place, particularly in 19 00:01:07,280 --> 00:01:11,360 Speaker 1: the tech sector, really throughout the business sector in general, 20 00:01:11,560 --> 00:01:14,800 Speaker 1: but tech in particular is incredibly guilty of this. It's 21 00:01:14,880 --> 00:01:17,520 Speaker 1: one of the hallmarks of tech, and you get extra 22 00:01:17,600 --> 00:01:21,200 Speaker 1: points if whatever term you're using is so vague or 23 00:01:21,280 --> 00:01:24,440 Speaker 1: easy to misuse that it may as well be meaningless. 24 00:01:24,720 --> 00:01:27,559 Speaker 1: So today we're going to talk about some tech buzzwords 25 00:01:27,600 --> 00:01:32,080 Speaker 1: that have made various lists for most hated buzzwords in Tech, 26 00:01:32,240 --> 00:01:36,440 Speaker 1: or most hated jargon in Tech, or something along those lines. Now, 27 00:01:36,600 --> 00:01:40,280 Speaker 1: I pulled these terms from a lot of different sources, 28 00:01:40,360 --> 00:01:44,759 Speaker 1: all from articles that were about hated or misused tech buzzwords. 29 00:01:45,000 --> 00:01:48,200 Speaker 1: Some of the buzzwords are used well beyond tech itself. 30 00:01:48,640 --> 00:01:51,320 Speaker 1: Some of them don't even originate from tech, but just 31 00:01:51,360 --> 00:01:56,200 Speaker 1: get reused. And I use sites like The American Genius 32 00:01:56,240 --> 00:02:00,360 Speaker 1: and Smart Company and CMC Global and DNS Research, Vation 33 00:02:00,560 --> 00:02:04,279 Speaker 1: and Forbes and trust Radius and net Suite to gather 34 00:02:04,360 --> 00:02:08,440 Speaker 1: all of these different terms. And the terms span the 35 00:02:08,520 --> 00:02:11,679 Speaker 1: last several years. Some of these buzzwords have faded a 36 00:02:11,720 --> 00:02:14,280 Speaker 1: little bit from use. We're going to talk about some that, 37 00:02:14,600 --> 00:02:18,440 Speaker 1: you know, just a couple of years ago were dominating 38 00:02:18,840 --> 00:02:23,400 Speaker 1: the conversations in tech, and now they're almost forgotten. Now 39 00:02:23,400 --> 00:02:27,640 Speaker 1: I'm going to start with one that I personally find exhausting, 40 00:02:27,760 --> 00:02:29,600 Speaker 1: and I bet a lot of y'all out there feel 41 00:02:29,760 --> 00:02:33,320 Speaker 1: much the same way, and that term is, of course 42 00:02:33,480 --> 00:02:36,400 Speaker 1: the biggest buzzword of the last couple of years in 43 00:02:36,440 --> 00:02:40,640 Speaker 1: tech Artificial intelligence, or more frequently, just plain old AI. 44 00:02:41,240 --> 00:02:44,440 Speaker 1: The explosion in AI development over the last couple of 45 00:02:44,480 --> 00:02:48,120 Speaker 1: years has really elevated the buzz terms use within the 46 00:02:48,160 --> 00:02:51,120 Speaker 1: tech space. And don't get me wrong, AI has been 47 00:02:51,160 --> 00:02:54,520 Speaker 1: a thing in tech for decades, like more than half 48 00:02:54,560 --> 00:02:58,120 Speaker 1: a century. It's a common theme in science fiction stories, 49 00:02:58,160 --> 00:03:01,280 Speaker 1: whether we're talking about comedic droi sidecakes, or you know, 50 00:03:01,360 --> 00:03:05,520 Speaker 1: some omnim present malicious intelligence determined to wipe out humans. 51 00:03:05,720 --> 00:03:08,520 Speaker 1: But in the last couple of years, AI has really 52 00:03:08,639 --> 00:03:12,120 Speaker 1: ramped up in the public consciousness, largely thanks to a 53 00:03:12,160 --> 00:03:17,600 Speaker 1: specific branch of the discipline, that of generative AI. Now 54 00:03:18,120 --> 00:03:21,040 Speaker 1: I don't think anyone out there is unfamiliar with generative 55 00:03:21,040 --> 00:03:24,000 Speaker 1: AI at this point, but just in case this term 56 00:03:24,080 --> 00:03:28,399 Speaker 1: is new to you, Generative AI creates stuff. It generates 57 00:03:28,560 --> 00:03:32,160 Speaker 1: based upon user input. So you might ask a question 58 00:03:32,360 --> 00:03:34,239 Speaker 1: and then it gives you an answer, or you might 59 00:03:34,480 --> 00:03:37,680 Speaker 1: create a suggestion that it makes some sort of content 60 00:03:37,840 --> 00:03:41,080 Speaker 1: like I once tried to use generative AI to make 61 00:03:41,440 --> 00:03:45,120 Speaker 1: I think it was a Shakespearean sonnet about artificial intelligence, 62 00:03:45,360 --> 00:03:48,000 Speaker 1: and it did a decent job at making a very 63 00:03:48,040 --> 00:03:51,600 Speaker 1: clever poem about AI, but it didn't follow the Shakespearean 64 00:03:51,680 --> 00:03:55,960 Speaker 1: sonnet rules, and I'm a stickler for form. Anyway, you 65 00:03:56,040 --> 00:03:59,600 Speaker 1: could even have generative AI that can create images based 66 00:03:59,600 --> 00:04:03,280 Speaker 1: on techs. You're all familiar with this, I'm sure, and 67 00:04:03,640 --> 00:04:05,800 Speaker 1: even today you can get to the point where you 68 00:04:05,800 --> 00:04:08,560 Speaker 1: can create video clips with some of these forms of 69 00:04:08,640 --> 00:04:12,320 Speaker 1: generative AI. And there's no doubt about it. Generative AI 70 00:04:12,640 --> 00:04:16,480 Speaker 1: can be really impressive, at least when it's working properly. 71 00:04:16,680 --> 00:04:20,200 Speaker 1: When it's not working properly, it can be creepy or unsettling. 72 00:04:20,440 --> 00:04:22,800 Speaker 1: Sometimes it could be like that if it's working properly too, 73 00:04:22,839 --> 00:04:25,680 Speaker 1: don't get me wrong, but man, even as recently as 74 00:04:25,800 --> 00:04:27,720 Speaker 1: just a couple of weeks ago, I was using an 75 00:04:27,760 --> 00:04:31,880 Speaker 1: image generator out of curiosity, just trying to create images 76 00:04:31,920 --> 00:04:35,279 Speaker 1: of characters from a friend of mine's podcast. She made 77 00:04:35,279 --> 00:04:37,160 Speaker 1: this podcast, and I was just like, I wonder if 78 00:04:37,160 --> 00:04:40,320 Speaker 1: I could create some like character concept images. And I'm 79 00:04:40,320 --> 00:04:44,440 Speaker 1: not an artist, and I just did this out of curiosity, 80 00:04:44,480 --> 00:04:46,960 Speaker 1: having no desire to actually use the images, but I 81 00:04:47,000 --> 00:04:49,360 Speaker 1: was wondering if I could make it happen, and still 82 00:04:49,640 --> 00:04:53,080 Speaker 1: fingers are hard for AI, y'all. There were so many 83 00:04:53,440 --> 00:04:57,800 Speaker 1: love crafty and monstrosities created by this image generator, and 84 00:04:57,839 --> 00:05:01,320 Speaker 1: it made me really feel calm that if I were 85 00:05:01,400 --> 00:05:06,000 Speaker 1: to actually help my friend create character images for some 86 00:05:06,040 --> 00:05:10,120 Speaker 1: of her creations, I would actually work with an artist. 87 00:05:10,160 --> 00:05:13,599 Speaker 1: I would hire a human artist to work with, because 88 00:05:13,640 --> 00:05:17,000 Speaker 1: then I know I would be one helping an actual 89 00:05:17,120 --> 00:05:19,960 Speaker 1: artist get work, which I think is really important and 90 00:05:20,040 --> 00:05:24,080 Speaker 1: to get what I wanted. But countless startups have launched 91 00:05:24,120 --> 00:05:27,200 Speaker 1: since late twenty twenty two, when open ai really got 92 00:05:27,240 --> 00:05:30,559 Speaker 1: the ball rolling by introducing chat GPT. Though to be clear, 93 00:05:30,920 --> 00:05:35,520 Speaker 1: there were already some generative AI applications available before chat GPT. 94 00:05:36,040 --> 00:05:40,000 Speaker 1: I would just say chat GPT launched everything into the stratosphere. 95 00:05:40,120 --> 00:05:44,600 Speaker 1: But here's my problem. Generative AI is just one implementation 96 00:05:44,720 --> 00:05:48,919 Speaker 1: of artificial intelligence, and it's not the only kind. AI 97 00:05:49,120 --> 00:05:52,479 Speaker 1: is actually an enormous discipline. It covers a huge amount 98 00:05:52,520 --> 00:05:56,279 Speaker 1: of ground like computer vision and image recognition that falls 99 00:05:56,320 --> 00:05:59,279 Speaker 1: under AI. Natural language processing is part of AI, and 100 00:05:59,320 --> 00:06:01,680 Speaker 1: obviously it has to be part of generative AI too. 101 00:06:01,760 --> 00:06:05,159 Speaker 1: If you're going to get anything that even resembles what 102 00:06:05,240 --> 00:06:09,040 Speaker 1: you were asking for, a lot of robotics falls under 103 00:06:09,080 --> 00:06:11,280 Speaker 1: the category of AI. Not all of it, but a 104 00:06:11,320 --> 00:06:13,599 Speaker 1: lot of it does. And on top of that, you 105 00:06:13,600 --> 00:06:15,720 Speaker 1: know the fact that we have all these different kinds 106 00:06:15,720 --> 00:06:20,200 Speaker 1: of AI and not just generative means that using the 107 00:06:20,839 --> 00:06:25,720 Speaker 1: blanket term the umbrella term for one specific implementation is 108 00:06:25,800 --> 00:06:29,560 Speaker 1: really not very accurate. But on top of that, some 109 00:06:29,600 --> 00:06:32,560 Speaker 1: companies are using AI pretty liberally to cover stuff that's 110 00:06:32,640 --> 00:06:36,840 Speaker 1: not even really artificial intelligence, like stuff like just algorithms. 111 00:06:36,880 --> 00:06:39,640 Speaker 1: And yes, algorithms are part of AI, they can be 112 00:06:39,800 --> 00:06:42,800 Speaker 1: part of AI, but that doesn't mean an algorithm by 113 00:06:42,839 --> 00:06:45,760 Speaker 1: itself should be described as AI. So if you've got 114 00:06:45,760 --> 00:06:49,800 Speaker 1: an algorithm that is looking at what I'm browsing, you know, 115 00:06:49,800 --> 00:06:52,160 Speaker 1: I'm looking at maybe vinyl record albums of the New 116 00:06:52,240 --> 00:06:55,240 Speaker 1: York Dolls, and then it do you have a recommendation? 117 00:06:55,279 --> 00:06:58,040 Speaker 1: Algorithm says, hey, maybe you should check out Velvet Underground. 118 00:06:58,320 --> 00:07:01,960 Speaker 1: That's not exactly artificial intelligence, although it is an excellent suggestion. 119 00:07:02,480 --> 00:07:06,640 Speaker 1: But because AI is so buzzy, right, it's such a 120 00:07:06,680 --> 00:07:09,680 Speaker 1: popular buzzword, there have been this ton of startups that 121 00:07:09,760 --> 00:07:13,600 Speaker 1: have begun to use AI to describe their pitch to 122 00:07:13,800 --> 00:07:17,880 Speaker 1: investors and to media. I can't tell you how many 123 00:07:18,120 --> 00:07:22,760 Speaker 1: unsolicited emails I get every single day from PR firms 124 00:07:22,840 --> 00:07:25,760 Speaker 1: representing clients who are trying to position their business as 125 00:07:25,800 --> 00:07:30,280 Speaker 1: the next big thing in AI, and sometimes, in fact, 126 00:07:30,320 --> 00:07:34,239 Speaker 1: I would argue frequently, they have little to no connection 127 00:07:34,400 --> 00:07:37,680 Speaker 1: to the actual discipline of artificial intelligence. On top of that, 128 00:07:37,960 --> 00:07:41,040 Speaker 1: I am also frustrated that so many businesses seem anxious 129 00:07:41,080 --> 00:07:45,360 Speaker 1: to jump into AI or else. I guess they're worried 130 00:07:45,400 --> 00:07:47,880 Speaker 1: they'd be left behind, but it seems to me that 131 00:07:48,080 --> 00:07:51,360 Speaker 1: many of these businesses have very little to no strategy 132 00:07:51,600 --> 00:07:54,560 Speaker 1: that's actually connected to AI. It's almost as if the 133 00:07:54,600 --> 00:07:57,200 Speaker 1: idea of AI is some sort of fix all solution 134 00:07:57,320 --> 00:08:01,000 Speaker 1: to every problem. That is going to be probably the 135 00:08:01,400 --> 00:08:06,120 Speaker 1: coda for this podcast. The motto of this is that 136 00:08:06,560 --> 00:08:09,880 Speaker 1: there are these buzzwords that people use, and it's almost 137 00:08:09,920 --> 00:08:13,480 Speaker 1: like a shortcut or a get out of jail free card, 138 00:08:13,520 --> 00:08:18,480 Speaker 1: where you've got this problem or challenge or goal in mind, 139 00:08:18,520 --> 00:08:20,480 Speaker 1: but you have no idea how to achieve that goal, 140 00:08:20,600 --> 00:08:23,280 Speaker 1: or overcome that challenge or solve that problem, So you 141 00:08:23,440 --> 00:08:28,520 Speaker 1: just use this kind of blanket term to stand in 142 00:08:28,680 --> 00:08:32,040 Speaker 1: place of an actual solution, and then you're just magically 143 00:08:32,360 --> 00:08:34,440 Speaker 1: where you need to be, and we all know that's 144 00:08:34,480 --> 00:08:36,720 Speaker 1: not really how the world works. I wish it were. 145 00:08:37,200 --> 00:08:38,560 Speaker 1: I would love to be able to use that kind 146 00:08:38,559 --> 00:08:40,560 Speaker 1: of logic to fix all sorts of things in my life, 147 00:08:40,600 --> 00:08:42,960 Speaker 1: but that's just not how it works. And you know, 148 00:08:43,280 --> 00:08:45,400 Speaker 1: you can't just open a big old box that has 149 00:08:45,440 --> 00:08:48,480 Speaker 1: the label AI on it and then business will magically 150 00:08:48,520 --> 00:08:50,880 Speaker 1: perform better. It's kind of like how I am with 151 00:08:50,960 --> 00:08:54,040 Speaker 1: electric guitars. So rather than practice on the electric guitar 152 00:08:54,120 --> 00:08:57,680 Speaker 1: I literally have standing right next to me. Sometimes I think, 153 00:08:57,720 --> 00:08:59,640 Speaker 1: you know, I should really buy a new guitar, as 154 00:08:59,640 --> 00:09:02,240 Speaker 1: if some how that new guitar is magically going to 155 00:09:02,280 --> 00:09:04,040 Speaker 1: make me a better player. And I can tell you 156 00:09:04,040 --> 00:09:07,839 Speaker 1: from experience that doesn't work either. And also my partner 157 00:09:07,880 --> 00:09:09,440 Speaker 1: would likely kick me out of the house if I 158 00:09:09,480 --> 00:09:12,240 Speaker 1: try and do that again. So I think the four 159 00:09:12,280 --> 00:09:16,080 Speaker 1: guitars I have are enough. Before we move on, we 160 00:09:16,120 --> 00:09:19,319 Speaker 1: should lump in some other AI related terms in here, 161 00:09:19,360 --> 00:09:23,640 Speaker 1: because AI, while that one alone is extremely buzzy and 162 00:09:24,160 --> 00:09:28,120 Speaker 1: people misuse it or you know, misinterpret it all the time, 163 00:09:28,200 --> 00:09:30,880 Speaker 1: there are others that fall into that same general category, 164 00:09:30,920 --> 00:09:33,800 Speaker 1: like machine learning and deep learning. They do have meaning. 165 00:09:33,880 --> 00:09:36,800 Speaker 1: These terms actually do mean something, so does AI for 166 00:09:36,880 --> 00:09:39,600 Speaker 1: that matter. They have meaning and they have relevance, but 167 00:09:39,640 --> 00:09:43,040 Speaker 1: they are frequently overused or misused by various tech companies 168 00:09:43,080 --> 00:09:45,760 Speaker 1: out there. And that's not good because you know, it 169 00:09:45,760 --> 00:09:49,920 Speaker 1: can set unrealistic or incorrect expectations, and then when those 170 00:09:49,960 --> 00:09:54,640 Speaker 1: expectations aren't met because the person had the incorrect interpretation 171 00:09:54,720 --> 00:09:58,240 Speaker 1: of what the terms actually meant, then support for research 172 00:09:58,280 --> 00:10:01,200 Speaker 1: and development in those kinds of fields can decline. And 173 00:10:01,520 --> 00:10:03,760 Speaker 1: I know that sounds kind of dramatic, but it's happened 174 00:10:03,800 --> 00:10:06,559 Speaker 1: again and again and again. It happened with virtual reality. 175 00:10:06,880 --> 00:10:10,600 Speaker 1: You know, we're seeing it possibly happen with mixed reality. 176 00:10:11,080 --> 00:10:13,880 Speaker 1: If someone's working on a research project and then they 177 00:10:13,920 --> 00:10:16,320 Speaker 1: find out that their funding has been cut because the 178 00:10:16,360 --> 00:10:19,280 Speaker 1: people who are in charge of the purse strings had 179 00:10:19,280 --> 00:10:22,800 Speaker 1: the wrong idea of what your work actually is all about. 180 00:10:23,040 --> 00:10:25,040 Speaker 1: And then once they find out what it is about, 181 00:10:25,080 --> 00:10:26,800 Speaker 1: they're like, oh, well, that's not what I wanted and 182 00:10:26,800 --> 00:10:30,000 Speaker 1: they cut off funding. That stinks, right, That really did 183 00:10:30,040 --> 00:10:32,200 Speaker 1: happen with VR in the nineties. You had people who 184 00:10:32,280 --> 00:10:36,000 Speaker 1: are working on important implementations of VR. I'm not talking 185 00:10:36,120 --> 00:10:39,280 Speaker 1: just like games, which I mean, I think games are important, 186 00:10:39,320 --> 00:10:43,319 Speaker 1: but beyond that, using VR for things like treating mental illness, 187 00:10:43,600 --> 00:10:46,360 Speaker 1: and then all the money for research kind of dried 188 00:10:46,440 --> 00:10:50,200 Speaker 1: up because people were disillusioned with what VR actually was 189 00:10:50,600 --> 00:10:54,160 Speaker 1: compared to what they thought it was. This stuff happens, Okay, 190 00:10:54,200 --> 00:10:57,240 Speaker 1: Next up, I want to talk about disrupt and disruption. 191 00:10:57,600 --> 00:11:00,079 Speaker 1: So these terms have been around for a while, and 192 00:11:00,120 --> 00:11:02,800 Speaker 1: it's a dramatic word. Typically, it just means that someone 193 00:11:02,800 --> 00:11:06,520 Speaker 1: has figured out a new way to do something. Sometimes 194 00:11:06,520 --> 00:11:09,160 Speaker 1: it's not even a new way. Sometimes it's just a 195 00:11:09,160 --> 00:11:11,400 Speaker 1: way that's a little bit different from how everyone else 196 00:11:11,520 --> 00:11:14,200 Speaker 1: is doing it currently. But it might be a very 197 00:11:14,320 --> 00:11:16,760 Speaker 1: old way that just fell out of favor and then 198 00:11:16,800 --> 00:11:19,560 Speaker 1: you kind of resurrect it. Now, the implication of disruption 199 00:11:19,760 --> 00:11:21,920 Speaker 1: is that this new way of doing things is going 200 00:11:21,960 --> 00:11:25,520 Speaker 1: to upend the industry it's in as a whole, and 201 00:11:25,559 --> 00:11:28,160 Speaker 1: that it will threaten the security of companies that refuse 202 00:11:28,240 --> 00:11:30,760 Speaker 1: to adjust to this new method and it will leave 203 00:11:30,800 --> 00:11:33,160 Speaker 1: them in the dust if they're unable to adapt. And 204 00:11:33,200 --> 00:11:35,680 Speaker 1: it's easier to understand if we just consider a couple 205 00:11:35,720 --> 00:11:40,439 Speaker 1: of examples. Amazon, for instance, disrupted retail. But how did 206 00:11:40,440 --> 00:11:43,440 Speaker 1: it do it well? It did retail online starting with 207 00:11:43,520 --> 00:11:47,000 Speaker 1: books and then eventually encompassing pretty much everything you can imagine. 208 00:11:47,080 --> 00:11:49,400 Speaker 1: And I would argue that Amazon really isn't that much 209 00:11:49,440 --> 00:11:52,960 Speaker 1: different from other huge retail companies in that many of 210 00:11:52,960 --> 00:11:55,840 Speaker 1: the strategies employed by Amazon are similar to ones that 211 00:11:55,880 --> 00:11:59,520 Speaker 1: were honed by companies like Walmart. It's just that Amazon 212 00:11:59,640 --> 00:12:02,000 Speaker 1: cut out the brick and mortar stores for the most 213 00:12:02,000 --> 00:12:06,720 Speaker 1: part and employed some other technologies to personalize the experience. Plus, 214 00:12:07,000 --> 00:12:09,760 Speaker 1: you know, buying stuff online means people don't have to 215 00:12:09,800 --> 00:12:12,920 Speaker 1: interact with other human beings, and for a not insignificant 216 00:12:12,920 --> 00:12:16,120 Speaker 1: slice of the population, that is a huge selling point. 217 00:12:16,240 --> 00:12:18,360 Speaker 1: Oh I don't need to talk to a person, I'll 218 00:12:18,400 --> 00:12:21,480 Speaker 1: just buy it online. Uber Lift and other ride haling 219 00:12:21,520 --> 00:12:25,360 Speaker 1: companies disrupted the taxi industry, which obviously has been a 220 00:12:25,360 --> 00:12:28,120 Speaker 1: real sticking point in various places around the world where 221 00:12:28,160 --> 00:12:31,160 Speaker 1: taxi companies have a great deal of influence. We've seen 222 00:12:31,400 --> 00:12:34,240 Speaker 1: examples of local governments cracking down on these kinds of 223 00:12:34,240 --> 00:12:38,160 Speaker 1: startups for sidestepping regulations that the taxi industry must obey, 224 00:12:38,440 --> 00:12:40,840 Speaker 1: and there have been attempts to refer to these as 225 00:12:41,000 --> 00:12:46,520 Speaker 1: ride shares, but because it's actually all about funneling money 226 00:12:46,600 --> 00:12:50,040 Speaker 1: through to the parent organization like Uber or lyft or whatever. 227 00:12:50,240 --> 00:12:53,600 Speaker 1: It's not really ride sharing, it's ride haling, so it 228 00:12:53,600 --> 00:12:56,360 Speaker 1: really is more like a taxi service than say, just 229 00:12:56,559 --> 00:12:59,360 Speaker 1: connecting people who happen to want to get to the 230 00:12:59,360 --> 00:13:01,360 Speaker 1: same place the same time. And there are a lot 231 00:13:01,400 --> 00:13:04,319 Speaker 1: of other examples. Of course, Airbnb is disruptive to not 232 00:13:04,360 --> 00:13:07,160 Speaker 1: only the hospitality industry but also real estate. I mean, 233 00:13:07,160 --> 00:13:09,200 Speaker 1: it's hard for folks who are just starting out to 234 00:13:09,240 --> 00:13:11,520 Speaker 1: go out and buy a house when the market caters 235 00:13:11,559 --> 00:13:14,160 Speaker 1: to rich people who want to add to their portfolio 236 00:13:14,240 --> 00:13:18,280 Speaker 1: of rental properties. But not everything that's being called disruptive 237 00:13:18,679 --> 00:13:23,000 Speaker 1: is actually upsetting apple carts. Sometimes the things that are 238 00:13:23,000 --> 00:13:25,720 Speaker 1: being called disruptive are just a new kind of business. 239 00:13:26,080 --> 00:13:29,040 Speaker 1: Sometimes it's describing a way of doing things that's different, 240 00:13:29,120 --> 00:13:32,959 Speaker 1: but it's not necessarily advantageous compared to how the industry 241 00:13:33,000 --> 00:13:36,040 Speaker 1: as a whole is doing whatever the thing is. And 242 00:13:36,080 --> 00:13:38,720 Speaker 1: a lot of leaders really hate the term disruptive because 243 00:13:38,760 --> 00:13:41,960 Speaker 1: it can distract folks into pursuing disruption at the expense 244 00:13:42,000 --> 00:13:44,760 Speaker 1: of actually making a business model that works. If you're 245 00:13:44,800 --> 00:13:49,960 Speaker 1: banking on everything causing disruption in an established market and 246 00:13:50,000 --> 00:13:52,520 Speaker 1: you're not actually spending effort making sure that your approach 247 00:13:52,679 --> 00:13:56,240 Speaker 1: even makes sense. You're just trying to watch the world burn. 248 00:13:56,679 --> 00:14:00,560 Speaker 1: Related to disrupt is the term game changer. That phrase 249 00:14:00,600 --> 00:14:03,760 Speaker 1: implies that the business model forces a change on an 250 00:14:03,960 --> 00:14:10,280 Speaker 1: entire industry, it changes the game. That very rarely happens. Instead, 251 00:14:10,320 --> 00:14:13,320 Speaker 1: we often hear game changer applied to businesses that are 252 00:14:13,559 --> 00:14:17,280 Speaker 1: just new, even ones that aren't doing anything particularly that 253 00:14:17,360 --> 00:14:21,280 Speaker 1: differently from their competitors or performing better than their competitors. 254 00:14:21,320 --> 00:14:25,600 Speaker 1: Sometimes they're performing worse. That's hardly changing the game. Okay, 255 00:14:25,640 --> 00:14:28,600 Speaker 1: we've got tons of other buzzwords to get through. Before 256 00:14:28,640 --> 00:14:30,560 Speaker 1: we do that, let's take a quick break to thank 257 00:14:30,600 --> 00:14:43,240 Speaker 1: our sponsors. We're back. Time to talk about some more 258 00:14:43,240 --> 00:14:46,360 Speaker 1: buzzwords that get a lot of hate on these lists. 259 00:14:46,520 --> 00:14:49,520 Speaker 1: This next one is a huge one. It sometimes ranks 260 00:14:49,600 --> 00:14:51,960 Speaker 1: is number one depending upon the year, and that is 261 00:14:52,360 --> 00:14:56,960 Speaker 1: digital transformation that popped up on multiple most hated buzzwords 262 00:14:57,000 --> 00:15:00,640 Speaker 1: and tech lists. John Moore of tech Target first this 263 00:15:00,960 --> 00:15:05,120 Speaker 1: definition of digital transformation. He says, it is quote the 264 00:15:05,240 --> 00:15:11,240 Speaker 1: incorporation of computer based technologies into an organization's products, processes, 265 00:15:11,320 --> 00:15:16,520 Speaker 1: and strategies. Organizations undertake digital transformation to better engage and 266 00:15:16,600 --> 00:15:20,880 Speaker 1: serve their workforce and customers and thus improve their ability 267 00:15:20,920 --> 00:15:26,120 Speaker 1: to compete end quote. So it's kind of like modernizing really, 268 00:15:26,240 --> 00:15:28,240 Speaker 1: is what I would call it. You know, you're trying 269 00:15:28,240 --> 00:15:30,920 Speaker 1: to figure out how can we take these various legacy 270 00:15:31,360 --> 00:15:35,120 Speaker 1: systems and processes and bring them into the digital age, 271 00:15:35,320 --> 00:15:40,880 Speaker 1: potentially making things easier to manage and monitor and measure 272 00:15:40,960 --> 00:15:45,080 Speaker 1: and all those sorts of things. Cindy Jondon of IFS, 273 00:15:45,120 --> 00:15:48,640 Speaker 1: which is a cloud computing company, says, quote, it's really 274 00:15:48,680 --> 00:15:53,000 Speaker 1: a seismic shift forcing organizations to better enable their teams 275 00:15:53,040 --> 00:15:56,920 Speaker 1: and improve asset usage and customer experiences end quote. To me, 276 00:15:57,040 --> 00:16:00,560 Speaker 1: that's teetering pretty darn close to being too vain to 277 00:16:00,640 --> 00:16:03,400 Speaker 1: be really useful. But at the same time, you could 278 00:16:03,600 --> 00:16:06,120 Speaker 1: argue that each organization is going to have its own 279 00:16:06,160 --> 00:16:09,840 Speaker 1: specific set of requirements and challenges, and so therefore it's 280 00:16:09,880 --> 00:16:12,880 Speaker 1: impossible to get specific, right because if you get specific, 281 00:16:13,080 --> 00:16:16,200 Speaker 1: then you're leaving out lots of other use cases, so 282 00:16:16,240 --> 00:16:19,160 Speaker 1: you have to be really general. But yeah, that particular 283 00:16:19,640 --> 00:16:23,640 Speaker 1: description to me borders on not being very useful. Now, 284 00:16:23,680 --> 00:16:27,600 Speaker 1: as pointed out on CMC Globals site, and issue with 285 00:16:27,760 --> 00:16:31,520 Speaker 1: the concept of digital transformation is that there's a tendency 286 00:16:31,560 --> 00:16:35,360 Speaker 1: to treat it again as a magical panacea similar to AI, 287 00:16:35,800 --> 00:16:39,440 Speaker 1: right that by somehow just porting processes over into a 288 00:16:39,480 --> 00:16:43,160 Speaker 1: computerized system, maybe even one that's networked, based on the cloud, 289 00:16:43,200 --> 00:16:47,400 Speaker 1: whatever it may be, you have somehow transformed the business inherently, 290 00:16:47,600 --> 00:16:50,120 Speaker 1: even though it's the exact same processes and everything, it's 291 00:16:50,160 --> 00:16:53,240 Speaker 1: just now it's done in a different way. Business strategy 292 00:16:53,280 --> 00:16:57,520 Speaker 1: is still absolutely important, and without business strategy, shifting how 293 00:16:57,560 --> 00:16:59,960 Speaker 1: you do things from one model to another doesn't actually 294 00:17:00,160 --> 00:17:03,920 Speaker 1: address fundamental issues. Again, it's like you're slapping a band 295 00:17:03,960 --> 00:17:06,720 Speaker 1: aid on something and you don't even understand it. It's 296 00:17:06,720 --> 00:17:08,879 Speaker 1: like if someone had a cold and you put a 297 00:17:08,920 --> 00:17:12,520 Speaker 1: band aid on their arm doesn't really address the problem. 298 00:17:12,760 --> 00:17:15,800 Speaker 1: There's no denying that modernizing systems so that they're more 299 00:17:15,840 --> 00:17:19,320 Speaker 1: easily accessible and adaptable is really important. But as Mark 300 00:17:19,359 --> 00:17:24,199 Speaker 1: Bilger of One Call puts it, quote digital transformations do 301 00:17:24,359 --> 00:17:28,159 Speaker 1: not magically transform the business. A fool with a tool 302 00:17:28,560 --> 00:17:31,639 Speaker 1: is still a fool, end quote. Kind of dig that. 303 00:17:31,960 --> 00:17:33,439 Speaker 1: There are a lot of companies out there that do 304 00:17:33,520 --> 00:17:36,719 Speaker 1: consulting work on digital transformation. I'm sure some of them 305 00:17:36,720 --> 00:17:39,320 Speaker 1: are quite good at it, but in my experienced consultants 306 00:17:39,320 --> 00:17:41,840 Speaker 1: are the absolute worst when it comes to leaning on 307 00:17:41,960 --> 00:17:45,679 Speaker 1: buzzwords in jargon to obfuscate what they mean. And I 308 00:17:45,680 --> 00:17:47,960 Speaker 1: feel like I can say that with some authority because 309 00:17:47,960 --> 00:17:52,679 Speaker 1: in my previous professional life, before I ever worked for iHeart, 310 00:17:52,720 --> 00:17:55,159 Speaker 1: before I work for Discovery Communications, before I work for 311 00:17:55,240 --> 00:17:58,879 Speaker 1: house stuffworks dot com, I spent more than seven years 312 00:17:58,920 --> 00:18:02,040 Speaker 1: working for management consultants. And I've read a lot of 313 00:18:02,080 --> 00:18:04,760 Speaker 1: proposals and a lot of reports, y'all, And one thing 314 00:18:04,800 --> 00:18:07,720 Speaker 1: I walked away with is that consultants just love to 315 00:18:07,840 --> 00:18:11,840 Speaker 1: use language that ultimately doesn't mean very much but sounds good. 316 00:18:12,280 --> 00:18:15,800 Speaker 1: Another big buzzword that makes these lists, and it's been 317 00:18:15,840 --> 00:18:19,320 Speaker 1: around for quite some time at this point, is the cloud. Now, 318 00:18:19,320 --> 00:18:22,320 Speaker 1: there's a meme that goes around that is one hundred 319 00:18:22,320 --> 00:18:25,560 Speaker 1: percent accurate that says there is no cloud, It's just 320 00:18:25,800 --> 00:18:29,679 Speaker 1: somebody else's computer. That's true. That's the basic truth of 321 00:18:29,680 --> 00:18:33,720 Speaker 1: what the cloud is. Cloud computing, cloud storage, cloud development, 322 00:18:33,720 --> 00:18:37,040 Speaker 1: whatever cloud service you're talking about. Ultimately, these all describe 323 00:18:37,080 --> 00:18:40,080 Speaker 1: a situation in which the thing you are using is 324 00:18:40,280 --> 00:18:44,159 Speaker 1: a computer system that's provided by a third party, and 325 00:18:44,200 --> 00:18:47,879 Speaker 1: that's it. That's the magic of the cloud. So It 326 00:18:47,920 --> 00:18:51,159 Speaker 1: may be that it's an operating environment. It may be 327 00:18:51,359 --> 00:18:54,520 Speaker 1: that it's you know again, storage. It could be any 328 00:18:54,520 --> 00:18:57,240 Speaker 1: of those things. But really it just means that these 329 00:18:57,640 --> 00:19:00,840 Speaker 1: these services are living on computers that are some else. Now, 330 00:19:00,880 --> 00:19:03,679 Speaker 1: cloud solutions free up businesses so that they don't have 331 00:19:03,720 --> 00:19:07,800 Speaker 1: to host their own services on premises or in tech speak, 332 00:19:08,080 --> 00:19:11,200 Speaker 1: on prem. I cannot tell you how much I hate 333 00:19:11,320 --> 00:19:16,000 Speaker 1: on prem not the concept but the actual use of that, 334 00:19:16,320 --> 00:19:18,920 Speaker 1: as if on prem is somehow saving you a huge 335 00:19:18,920 --> 00:19:21,560 Speaker 1: amount of time as opposed to saying on premises. In 336 00:19:21,640 --> 00:19:23,800 Speaker 1: my humble opinion, on prem is just a way to 337 00:19:23,840 --> 00:19:28,080 Speaker 1: create a code language that in small ways excludes outsiders 338 00:19:28,119 --> 00:19:30,040 Speaker 1: from your group. It's kind of akin to the Little 339 00:19:30,119 --> 00:19:34,040 Speaker 1: Rascals having the he Man Woman Haters Club, though I 340 00:19:34,080 --> 00:19:36,280 Speaker 1: really guess only a fraction of y'all probably know who 341 00:19:36,280 --> 00:19:39,560 Speaker 1: the little Rascals are. I'm old, but anyway, my commentary 342 00:19:39,560 --> 00:19:44,600 Speaker 1: aside the issue many take with cloud terminology is that 343 00:19:44,680 --> 00:19:47,439 Speaker 1: people will frequently use the phrase, similar to what we 344 00:19:47,480 --> 00:19:50,800 Speaker 1: saw with AI and digital transformation, that it's some kind 345 00:19:50,840 --> 00:19:54,119 Speaker 1: of cure all for any business challenge. There are definitely 346 00:19:54,160 --> 00:19:57,800 Speaker 1: really good reasons to use cloud services, right like you 347 00:19:57,920 --> 00:20:01,000 Speaker 1: might not be able to scale your services to your 348 00:20:01,040 --> 00:20:05,240 Speaker 1: customers if it became really popular. Right, if you host 349 00:20:05,359 --> 00:20:08,879 Speaker 1: everything yourself and everything's running on servers that are in 350 00:20:08,960 --> 00:20:13,040 Speaker 1: your own office space or garage, whatever it may be, 351 00:20:13,359 --> 00:20:16,080 Speaker 1: and you suddenly get really popular, you could end up 352 00:20:16,119 --> 00:20:19,240 Speaker 1: having your service completely overwhelmed and now you can't provide 353 00:20:19,280 --> 00:20:22,639 Speaker 1: services to anybody. And this is also kind of a 354 00:20:22,680 --> 00:20:24,560 Speaker 1: good problem to have. It means that your services are 355 00:20:24,600 --> 00:20:27,679 Speaker 1: resonating with customers, but you don't want the experience for 356 00:20:27,800 --> 00:20:30,600 Speaker 1: them to be to log in and find out they 357 00:20:30,640 --> 00:20:33,639 Speaker 1: can't access the thing that they're paying for. That's bad. 358 00:20:33,960 --> 00:20:37,119 Speaker 1: So leaning on a large, established cloud provider could be 359 00:20:37,160 --> 00:20:39,600 Speaker 1: the solution. It might be that, oh, well, we can 360 00:20:39,680 --> 00:20:44,080 Speaker 1: scale just by purchasing more compute power or more storage 361 00:20:44,119 --> 00:20:48,240 Speaker 1: from this provider. But just poorting stuff from your own 362 00:20:48,280 --> 00:20:51,440 Speaker 1: systems to the cloud doesn't automatically make them work better 363 00:20:51,760 --> 00:20:54,560 Speaker 1: or reach more customers. It's not like the company providing 364 00:20:54,560 --> 00:20:56,920 Speaker 1: the cloud services is going to be doing your marketing 365 00:20:57,000 --> 00:20:59,680 Speaker 1: for you or anything, because they've already got their customer. 366 00:21:00,080 --> 00:21:02,639 Speaker 1: Their customer is you. It's your job to go out 367 00:21:02,680 --> 00:21:05,600 Speaker 1: and get your own customers. But yeah, cloud computing is 368 00:21:05,640 --> 00:21:08,760 Speaker 1: often used as sort of this hand wavy way of saying, 369 00:21:09,000 --> 00:21:12,440 Speaker 1: don't worry about these problems, we got it covered, when 370 00:21:12,440 --> 00:21:14,919 Speaker 1: in fact, the cloud does not magically solve stuff on 371 00:21:14,960 --> 00:21:17,280 Speaker 1: its own. Again, this is a real issue with a 372 00:21:17,280 --> 00:21:19,920 Speaker 1: lot of these buzzwords. If I'm being honest, it's really 373 00:21:19,920 --> 00:21:24,280 Speaker 1: it's not the word's fault necessarily, it's that folks are lazy. 374 00:21:24,480 --> 00:21:27,480 Speaker 1: People are lazy and they don't want to have to 375 00:21:27,600 --> 00:21:31,840 Speaker 1: really tackle and define the real challenging business or tech 376 00:21:31,880 --> 00:21:35,120 Speaker 1: issues that they're facing. That's hard. This is very hard 377 00:21:35,160 --> 00:21:40,639 Speaker 1: to actually identify and then solve these tough business problems. 378 00:21:40,680 --> 00:21:42,879 Speaker 1: It's really hard work. So it's way easier to just 379 00:21:43,000 --> 00:21:45,639 Speaker 1: use a phrase or a term and to take a shortcut, 380 00:21:45,760 --> 00:21:49,000 Speaker 1: especially if you're an executive, and then you foist the 381 00:21:49,040 --> 00:21:53,040 Speaker 1: actual problem onto your underlings and it's their job to 382 00:21:53,119 --> 00:21:55,320 Speaker 1: actually figure out, Okay, well, how do we do the 383 00:21:55,359 --> 00:21:58,080 Speaker 1: thing that our boss wants us to do when all 384 00:21:58,119 --> 00:22:02,280 Speaker 1: our boss says is cloud compute or digital transformation. To me, 385 00:22:02,520 --> 00:22:05,720 Speaker 1: this is kind of like the underpants gnomes in South Park, 386 00:22:05,880 --> 00:22:08,199 Speaker 1: You know the underpants domes. They say phase one is 387 00:22:08,240 --> 00:22:11,359 Speaker 1: collect underpants, phase two is something, and phase three is 388 00:22:11,440 --> 00:22:14,159 Speaker 1: profit that's what a lot of these buzzwords are. You know, 389 00:22:14,240 --> 00:22:17,520 Speaker 1: the buzzwords are phase one, Phase two is completely undefined, 390 00:22:17,560 --> 00:22:20,480 Speaker 1: and then phase three is somehow huge success. And I'm 391 00:22:20,480 --> 00:22:23,240 Speaker 1: sad to report again it usually does not work out 392 00:22:23,280 --> 00:22:26,200 Speaker 1: that way. All right, So what's next? Well, I guess, 393 00:22:26,280 --> 00:22:27,840 Speaker 1: I mean, I didn't want to have to do this 394 00:22:28,000 --> 00:22:31,679 Speaker 1: because I really don't like covering these kinds of things, 395 00:22:31,720 --> 00:22:35,280 Speaker 1: but it's time to tackle blockchain and the related buzz 396 00:22:35,359 --> 00:22:39,640 Speaker 1: terms around that. So blockchain is a thing, right, I'm 397 00:22:39,640 --> 00:22:43,240 Speaker 1: not saying that blockchain doesn't mean anything. It absolutely does 398 00:22:43,400 --> 00:22:46,720 Speaker 1: mean something. It's mostly a thing that people associate with 399 00:22:46,760 --> 00:22:50,480 Speaker 1: cryptocurrencies because that's where it's seen the most use and 400 00:22:50,520 --> 00:22:54,880 Speaker 1: I would argue the most success. But blockchain evangelists proclaim 401 00:22:54,960 --> 00:22:57,639 Speaker 1: that blockchain is going to underpin the entirety of the 402 00:22:57,680 --> 00:23:00,240 Speaker 1: Web of the future. This will play into a another 403 00:23:00,240 --> 00:23:04,080 Speaker 1: buzz term we'll talk about shortly, web three. Now, these 404 00:23:04,119 --> 00:23:08,960 Speaker 1: evangelists aren't always super good at articulating how blockchain will 405 00:23:09,000 --> 00:23:12,320 Speaker 1: actually underpin the web of the future, just somehow that 406 00:23:12,440 --> 00:23:15,720 Speaker 1: it will, and often a lot of details get glossed 407 00:23:15,720 --> 00:23:18,560 Speaker 1: over in the process. I mean, blockchain has a lot 408 00:23:18,560 --> 00:23:21,720 Speaker 1: of challenges facing it too, Like a lot of those 409 00:23:21,720 --> 00:23:24,880 Speaker 1: systems are very slow, they're inefficient, some of them are 410 00:23:24,920 --> 00:23:29,000 Speaker 1: extremely thirsty for electricity if it's based on a proof 411 00:23:29,040 --> 00:23:32,920 Speaker 1: of work approach to blockchain. So there are a lot 412 00:23:32,960 --> 00:23:38,400 Speaker 1: of issues that evangelists usually don't directly address, and they 413 00:23:38,400 --> 00:23:41,440 Speaker 1: have pretty glib answers if you start asking follow up questions. 414 00:23:41,600 --> 00:23:45,240 Speaker 1: But what does blockchain actually mean? Well, basically, a blockchain 415 00:23:45,440 --> 00:23:49,359 Speaker 1: is a record of transactions. Typically we're talking about a 416 00:23:49,440 --> 00:23:52,920 Speaker 1: decentralized ledger, meaning this ledger does not exist in any 417 00:23:53,160 --> 00:23:58,400 Speaker 1: one given computer, it is distributed across lots of different computers, 418 00:23:58,680 --> 00:24:02,000 Speaker 1: and this ledger is a record of all these transactions. 419 00:24:02,200 --> 00:24:05,040 Speaker 1: And not only is it a record, it's viewable by 420 00:24:05,119 --> 00:24:08,560 Speaker 1: a collection of stakeholders. So in some cases those stakeholders 421 00:24:08,600 --> 00:24:11,639 Speaker 1: could be everyone who is connected to and is using 422 00:24:11,720 --> 00:24:14,960 Speaker 1: the system. So in other words, it's as public as 423 00:24:15,000 --> 00:24:17,280 Speaker 1: it gets, right, as long as you are part of 424 00:24:17,320 --> 00:24:20,560 Speaker 1: the system, you can actually view the ledger. But in 425 00:24:20,600 --> 00:24:23,280 Speaker 1: other cases, we could be talking about a closed blockchain 426 00:24:23,320 --> 00:24:26,000 Speaker 1: and which only a select number of parties have access 427 00:24:26,040 --> 00:24:28,720 Speaker 1: to that ledger, even if the blockchain itself is a 428 00:24:28,760 --> 00:24:31,760 Speaker 1: foundation for a service that lots of other people are using. 429 00:24:31,920 --> 00:24:34,520 Speaker 1: So you might have tons of people using, say a 430 00:24:34,520 --> 00:24:38,880 Speaker 1: specific cryptocurrency, but only a small collection of stakeholders are 431 00:24:38,920 --> 00:24:42,520 Speaker 1: able to actually view the ledger itself. That is problem 432 00:24:42,640 --> 00:24:46,040 Speaker 1: number one. Actually, often I hear or read about projects 433 00:24:46,080 --> 00:24:48,439 Speaker 1: that are pitched to be built on top of a blockchain, 434 00:24:48,600 --> 00:24:52,920 Speaker 1: and the implication is that this makes the system inherently transparent. 435 00:24:53,320 --> 00:24:56,840 Speaker 1: It doesn't. For example, there was Facebook, which is of 436 00:24:56,880 --> 00:25:00,280 Speaker 1: course now called Meta, and Facebook's attempt to ch a 437 00:25:00,320 --> 00:25:04,560 Speaker 1: cryptocurrency initially called Libra, later it was called DM. Actually 438 00:25:04,560 --> 00:25:07,760 Speaker 1: technically Libra itself was I think the second name for it, 439 00:25:07,800 --> 00:25:11,080 Speaker 1: but Libra and then DIM. The blockchain serving as the 440 00:25:11,080 --> 00:25:14,560 Speaker 1: foundation for this particular cryptocurrency was going to be the 441 00:25:14,600 --> 00:25:18,320 Speaker 1: domain of a consortium of companies that initially was called 442 00:25:18,359 --> 00:25:22,720 Speaker 1: the Libra Association, later became the DM Association. So instead 443 00:25:22,720 --> 00:25:25,320 Speaker 1: of a community of users all having access to this 444 00:25:25,440 --> 00:25:29,040 Speaker 1: distributed ledger of transactions, it would be this consortium. But 445 00:25:29,480 --> 00:25:32,120 Speaker 1: that ultimately did not work out. The whole project got 446 00:25:32,160 --> 00:25:35,679 Speaker 1: bogged down, a ton of companies that initially had signed 447 00:25:35,720 --> 00:25:38,760 Speaker 1: on to be part of the consortium bailed on it. Ultimately, 448 00:25:38,800 --> 00:25:41,639 Speaker 1: the consortium sold off what few assets it still had 449 00:25:41,800 --> 00:25:44,760 Speaker 1: to a bank called Silvergate Capital for a couple hundred 450 00:25:44,760 --> 00:25:47,639 Speaker 1: million dollars. At least that was the belief. The money 451 00:25:48,119 --> 00:25:51,760 Speaker 1: amount was never made public, but then Silvergate subsequently shut 452 00:25:51,840 --> 00:25:54,480 Speaker 1: down the following year. Because this stuff is hard, y'all. 453 00:25:54,680 --> 00:25:57,919 Speaker 1: I mean, if Facebook can't do it, it's really hard. 454 00:25:58,600 --> 00:26:01,720 Speaker 1: We'll come back to that when we talk about the metaverse. Anyway, 455 00:26:01,920 --> 00:26:04,920 Speaker 1: the selling point for blockchain technology is that the record 456 00:26:04,960 --> 00:26:08,119 Speaker 1: of transactions is both transparent and it is reliable because 457 00:26:08,200 --> 00:26:11,919 Speaker 1: each block of transactions is cryptographically linked to all the 458 00:26:11,960 --> 00:26:16,240 Speaker 1: previous transactions in that ledger, and we'll be linked to 459 00:26:16,320 --> 00:26:21,040 Speaker 1: all subsequent transactions in that ledger. And this means that 460 00:26:21,160 --> 00:26:24,480 Speaker 1: no one can tamper with the records of previous transactions. 461 00:26:24,600 --> 00:26:27,080 Speaker 1: If you went back and tried to change the record 462 00:26:27,400 --> 00:26:29,879 Speaker 1: further back on the list, like let's say it's three 463 00:26:29,960 --> 00:26:33,080 Speaker 1: blocks back, well, that would actually make changes to the 464 00:26:33,119 --> 00:26:36,159 Speaker 1: next two blocks. It would be impossible to hide. So 465 00:26:37,040 --> 00:26:40,199 Speaker 1: there's no bacxies. Every transaction is permanent. You know, you 466 00:26:40,200 --> 00:26:43,400 Speaker 1: could do a new transaction with the exact same assets, 467 00:26:43,480 --> 00:26:45,560 Speaker 1: right Like if you had purchased something and then you 468 00:26:45,600 --> 00:26:47,600 Speaker 1: wanted to turn around and sell it you could do that, 469 00:26:47,880 --> 00:26:51,159 Speaker 1: but you couldn't purchase something and then go back and 470 00:26:51,200 --> 00:26:53,960 Speaker 1: erase the record of you purchasing it so that you 471 00:26:54,080 --> 00:26:57,840 Speaker 1: magically get your cryptocurrency back. You can't reverse an earlier 472 00:26:57,840 --> 00:27:01,080 Speaker 1: transaction that way. So this leads some to say, aha, 473 00:27:01,200 --> 00:27:04,280 Speaker 1: we can use blockchain to serve as the bedrock for 474 00:27:04,440 --> 00:27:07,440 Speaker 1: all online transactions. I mean, you could do it to 475 00:27:07,520 --> 00:27:09,879 Speaker 1: keep record of like buying a house. You know, you 476 00:27:10,119 --> 00:27:13,239 Speaker 1: enter that transaction into a blockchain that shows proof of 477 00:27:13,280 --> 00:27:16,160 Speaker 1: this transition of ownership of the property. No one else 478 00:27:16,240 --> 00:27:18,879 Speaker 1: can claim to own your property. You've got the record 479 00:27:18,960 --> 00:27:22,560 Speaker 1: right there, and it is unalterable and irreversible. So the 480 00:27:22,560 --> 00:27:25,200 Speaker 1: blockchain will show that the transaction happened and will serve 481 00:27:25,200 --> 00:27:28,600 Speaker 1: as proof that ownership has changed hands. Moreover, it can 482 00:27:28,720 --> 00:27:31,399 Speaker 1: serve as a record for digital transactions, which are a 483 00:27:31,400 --> 00:27:34,000 Speaker 1: lot more whibly wobbly than stuff that you can buy 484 00:27:34,080 --> 00:27:37,160 Speaker 1: and sell an actual meat space. So, for example, let's 485 00:27:37,160 --> 00:27:39,920 Speaker 1: say I wanted to buy a clip of music. Maybe 486 00:27:39,960 --> 00:27:42,280 Speaker 1: I even want a smart contract that gives me the 487 00:27:42,359 --> 00:27:45,720 Speaker 1: license to use that music clip in some other work, 488 00:27:45,840 --> 00:27:48,240 Speaker 1: such as an episode of a podcast. Well, you could 489 00:27:48,280 --> 00:27:51,399 Speaker 1: set that up on a blockchain ecosystem to show proof 490 00:27:51,440 --> 00:27:54,280 Speaker 1: of this transaction, and that could stand as the record 491 00:27:54,280 --> 00:27:57,280 Speaker 1: indicating that I, as a customer, have legally purchased the 492 00:27:57,320 --> 00:28:00,280 Speaker 1: license to use a clip of someone else's music in 493 00:28:00,320 --> 00:28:04,960 Speaker 1: my work. Now that's just one hypothetical example. This does 494 00:28:05,000 --> 00:28:08,040 Speaker 1: tie into n fts or non fungible tokens. But there 495 00:28:08,119 --> 00:28:11,400 Speaker 1: was obviously a huge problem with NFTs as they rolled out, Namely, 496 00:28:11,640 --> 00:28:15,840 Speaker 1: they became a target for insane and unsustainable speculation. So 497 00:28:15,880 --> 00:28:18,720 Speaker 1: folks were buying up NFTs with the expectation that these 498 00:28:18,720 --> 00:28:22,320 Speaker 1: digital assets were going to escalate in value, and a 499 00:28:22,359 --> 00:28:24,639 Speaker 1: lot of companies got in on the NFT craze. They 500 00:28:24,640 --> 00:28:27,520 Speaker 1: saw it as a way to essentially print money, or 501 00:28:27,560 --> 00:28:30,600 Speaker 1: they were afraid of being left behind, and ultimately the 502 00:28:30,680 --> 00:28:34,560 Speaker 1: NFT bubble popped and laid waste to the entire landscape, 503 00:28:34,560 --> 00:28:36,959 Speaker 1: and it also did an enormous amount of pr damage 504 00:28:36,960 --> 00:28:39,680 Speaker 1: to the NFT concept as a whole. So even folks 505 00:28:39,720 --> 00:28:43,120 Speaker 1: who were coming up with undeniably interesting ideas for NFTs 506 00:28:43,240 --> 00:28:46,959 Speaker 1: found themselves scrambling for interest and support because the speculative 507 00:28:47,000 --> 00:28:51,400 Speaker 1: market had burned so many people. Okay, we're coming up 508 00:28:51,440 --> 00:28:55,640 Speaker 1: on the last third of our podcast and speaking of thirds, 509 00:28:55,640 --> 00:28:58,760 Speaker 1: we'll be talking about Web three next, but first let's 510 00:28:58,760 --> 00:29:11,360 Speaker 1: take another quick break to thank our sponsors. All right, 511 00:29:11,440 --> 00:29:15,280 Speaker 1: we're back and we're going to talk about web three now. 512 00:29:15,280 --> 00:29:17,160 Speaker 1: A lot of the buzzwords we've talked about so far 513 00:29:17,560 --> 00:29:21,920 Speaker 1: have an actual meaning, right, They do have meaning to them, 514 00:29:22,160 --> 00:29:25,880 Speaker 1: but often there's this issue of people misinterpreting or misusing 515 00:29:25,920 --> 00:29:31,520 Speaker 1: the terminology, misconstruing something, and then the meaning of those 516 00:29:31,560 --> 00:29:34,240 Speaker 1: other terms gets a little fuzzy. Web three is not 517 00:29:34,440 --> 00:29:37,200 Speaker 1: like that, though, because it doesn't really have a definition. 518 00:29:37,560 --> 00:29:40,600 Speaker 1: It's kind of like the term metaverse, which we will 519 00:29:40,640 --> 00:29:42,920 Speaker 1: talk about in a second. In fact, I would argue 520 00:29:43,000 --> 00:29:46,000 Speaker 1: web three and metaverse are very similar in that regard. 521 00:29:46,280 --> 00:29:49,000 Speaker 1: They are both words used by people to make some 522 00:29:49,160 --> 00:29:53,400 Speaker 1: pretty vague statements about a kind of hazy future of 523 00:29:53,480 --> 00:29:57,680 Speaker 1: online interaction and commerce and society. But once you start 524 00:29:57,680 --> 00:30:00,200 Speaker 1: to dive down into it, you start to discover that 525 00:30:00,320 --> 00:30:02,640 Speaker 1: there actually are a lot of different takes on what 526 00:30:02,800 --> 00:30:06,080 Speaker 1: these things are ultimately going to be, and so it 527 00:30:06,120 --> 00:30:09,040 Speaker 1: doesn't seem like anyone's really on the same page, Like 528 00:30:09,080 --> 00:30:11,560 Speaker 1: there are a lot of similarities, but there are a 529 00:30:11,560 --> 00:30:15,280 Speaker 1: lot of differences too, and this ultimately means there's not 530 00:30:15,360 --> 00:30:18,200 Speaker 1: a really meaningful way to talk about these kinds of things. 531 00:30:18,600 --> 00:30:21,320 Speaker 1: But you still have companies jumping on board in an 532 00:30:21,360 --> 00:30:24,600 Speaker 1: attempt to establish a presence in an undefined field or 533 00:30:24,680 --> 00:30:29,560 Speaker 1: else lose some sort of unknowable advantage. So generally speaking, 534 00:30:29,920 --> 00:30:33,520 Speaker 1: most versions of Web three share certain qualities. One of 535 00:30:33,560 --> 00:30:37,200 Speaker 1: the big ones is decentralization. So a big criticism of 536 00:30:37,240 --> 00:30:41,480 Speaker 1: the current web is that power and influence gravitates toward 537 00:30:41,560 --> 00:30:45,440 Speaker 1: a few massive players in the space. We're talking big 538 00:30:45,520 --> 00:30:49,080 Speaker 1: companies like Amazon and Google, for example, and there's no 539 00:30:49,200 --> 00:30:53,080 Speaker 1: denying it, Like, there are certain companies that have a 540 00:30:53,160 --> 00:30:57,440 Speaker 1: stranglehold on the massive amounts of data that pass over 541 00:30:57,520 --> 00:31:00,160 Speaker 1: the Web, And so the thought is, wouldn't it be 542 00:31:00,160 --> 00:31:04,680 Speaker 1: better if we democratize that power somewhat? We took it 543 00:31:04,760 --> 00:31:06,680 Speaker 1: so that the next version of the Web is not 544 00:31:07,280 --> 00:31:10,560 Speaker 1: entrusted into the hands of these corporate mega giants, but 545 00:31:10,640 --> 00:31:14,560 Speaker 1: rather to the users. You know, that's what evangelists like 546 00:31:14,600 --> 00:31:16,640 Speaker 1: to say, put the power in the hands of the users, 547 00:31:16,680 --> 00:31:20,360 Speaker 1: which is kind of like tron. Critics of Web three 548 00:31:20,480 --> 00:31:23,280 Speaker 1: say that most of the Web three implementation ideas would 549 00:31:23,280 --> 00:31:26,360 Speaker 1: really just create different power brokers for the Web. It 550 00:31:26,400 --> 00:31:28,400 Speaker 1: wouldn't be the big companies that we talk about, the 551 00:31:28,400 --> 00:31:31,240 Speaker 1: big tech companies, but it would go into the hands 552 00:31:31,280 --> 00:31:35,160 Speaker 1: of a wealthy subculture that would be able to afford 553 00:31:35,600 --> 00:31:38,280 Speaker 1: to act as the cornerstones of this new web. So 554 00:31:38,360 --> 00:31:41,120 Speaker 1: really it doesn't democratize who owns the web. It just 555 00:31:41,200 --> 00:31:44,760 Speaker 1: designates different stakeholders, the folks in charge of overseeing the 556 00:31:44,840 --> 00:31:47,520 Speaker 1: various systems that Web three is actually built upon, which 557 00:31:47,760 --> 00:31:51,760 Speaker 1: usually involves some kind of blockchain technology and token economy. 558 00:31:52,000 --> 00:31:54,440 Speaker 1: Now I don't mean a token economy. I mean an 559 00:31:54,440 --> 00:31:57,840 Speaker 1: economy based upon the minting, buying, selling, and trading of 560 00:31:57,880 --> 00:32:00,800 Speaker 1: digital tokens. And we heard a lot of buzz about 561 00:32:00,880 --> 00:32:03,840 Speaker 1: Web three just a couple of years ago. And to 562 00:32:03,880 --> 00:32:06,960 Speaker 1: be clear, there are still companies that are working toward 563 00:32:07,040 --> 00:32:11,840 Speaker 1: making something along the lines of a Web three implementation happen. 564 00:32:11,960 --> 00:32:15,040 Speaker 1: But the excitement around this has fizzled out quite a bit. 565 00:32:15,640 --> 00:32:18,760 Speaker 1: And I honestly I think that artificial intelligence has managed 566 00:32:18,800 --> 00:32:23,120 Speaker 1: to drink an awful lot of tech milkshakes. So you 567 00:32:23,120 --> 00:32:25,280 Speaker 1: can also look at the metaverse as an example of this, 568 00:32:25,400 --> 00:32:30,160 Speaker 1: where some of that excitement has been ported over for AI. 569 00:32:30,600 --> 00:32:33,360 Speaker 1: In fact, according to Gopal Solanki, who wrote a piece 570 00:32:33,400 --> 00:32:37,360 Speaker 1: on Medium that's titled is Web three dead already? He 571 00:32:37,400 --> 00:32:40,160 Speaker 1: said investment in Web three companies has fallen by more 572 00:32:40,200 --> 00:32:43,000 Speaker 1: than seventy five percent in twenty twenty three compared to 573 00:32:43,040 --> 00:32:45,640 Speaker 1: the levels it had in twenty twenty one. He went 574 00:32:45,680 --> 00:32:48,960 Speaker 1: on to say, we cannot say that Web three is dead, 575 00:32:49,120 --> 00:32:52,640 Speaker 1: but it has surely failed to deliver the promises it made. 576 00:32:52,720 --> 00:32:56,280 Speaker 1: Each innovative idea presented in the form of renovated web 577 00:32:56,440 --> 00:33:00,800 Speaker 1: version has turned into complete dust on unless it has 578 00:33:00,840 --> 00:33:04,080 Speaker 1: something to do with the native cryptocurrency token. All the 579 00:33:04,120 --> 00:33:07,160 Speaker 1: developments and projects introduced in the Web three hype are 580 00:33:07,280 --> 00:33:10,200 Speaker 1: majorly underperforming. That seems to sum it up to me. 581 00:33:10,520 --> 00:33:13,200 Speaker 1: I can't disagree with that, and not to say that 582 00:33:13,600 --> 00:33:16,880 Speaker 1: something called Web three won't come down the line, but 583 00:33:17,320 --> 00:33:21,920 Speaker 1: in the meantime, that term is largely without meaning, and 584 00:33:21,960 --> 00:33:26,040 Speaker 1: it's mostly used by people who are scrambling for funding 585 00:33:26,280 --> 00:33:30,680 Speaker 1: for something that's unproven and potentially no better than what 586 00:33:30,800 --> 00:33:33,920 Speaker 1: we already have. In fact, potentially it could be worse. 587 00:33:34,360 --> 00:33:39,040 Speaker 1: Things like transmission speeds and stuff could be drastically affected 588 00:33:39,160 --> 00:33:43,600 Speaker 1: because again, blockchain transactions are not the most efficient. So 589 00:33:43,840 --> 00:33:47,360 Speaker 1: if you build everything based on blockchain transactions like online 590 00:33:47,400 --> 00:33:50,440 Speaker 1: commerce is completely based on blockchain. It could mean that 591 00:33:50,520 --> 00:33:54,040 Speaker 1: it's just overwhelmed that it's far too slow to deal 592 00:33:54,280 --> 00:33:58,000 Speaker 1: with that level of responsibility. All right, Well, then let's 593 00:33:58,040 --> 00:34:01,400 Speaker 1: tackle metaverse and mixed reality, more stuff that went through 594 00:34:01,440 --> 00:34:05,320 Speaker 1: the hype cycle and recently has struggled to remain relevant. 595 00:34:05,640 --> 00:34:09,120 Speaker 1: Starting off with the metaverse, we're talking about a concept that, again, 596 00:34:09,239 --> 00:34:12,440 Speaker 1: like Web three, does not have a firm definition. There 597 00:34:12,480 --> 00:34:17,359 Speaker 1: are a distinct lack of details. Generally speaking, most definitions, 598 00:34:17,360 --> 00:34:20,840 Speaker 1: if you can call them, that, imply a persistent virtual 599 00:34:20,880 --> 00:34:24,600 Speaker 1: world in which you can explore and socialize and shop 600 00:34:24,760 --> 00:34:29,080 Speaker 1: and create and consume, kind of like a computer generated 601 00:34:29,160 --> 00:34:33,279 Speaker 1: alternate reality to the reality we experience if we step 602 00:34:33,320 --> 00:34:37,240 Speaker 1: outside our houses. Some versions of the metaverse tap into 603 00:34:37,239 --> 00:34:39,960 Speaker 1: similar stuff that we hear about in Web three, like 604 00:34:40,040 --> 00:34:44,000 Speaker 1: cryptocurrencies and blockchain. Other versions of the metaverse focus more 605 00:34:44,080 --> 00:34:47,120 Speaker 1: on the virtual reality aspect and things like creating your 606 00:34:47,120 --> 00:34:52,080 Speaker 1: own avatar and being able to maneuver around these virtual environments. 607 00:34:52,440 --> 00:34:56,880 Speaker 1: Some versions of the metaverse describe a huge, interconnected series 608 00:34:57,000 --> 00:35:00,640 Speaker 1: of virtual worlds kind of hosted by different intit so 609 00:35:00,920 --> 00:35:04,719 Speaker 1: there might be one that's owned and operated by Meta 610 00:35:04,760 --> 00:35:07,280 Speaker 1: and another one owned and operated by Amazon, and maybe 611 00:35:07,280 --> 00:35:10,439 Speaker 1: they're interlinked together so you can pass through from one 612 00:35:10,520 --> 00:35:12,920 Speaker 1: to the other, kind of like how the web itself 613 00:35:13,000 --> 00:35:15,720 Speaker 1: is a big interconnected series of web pages, but instead 614 00:35:15,719 --> 00:35:19,160 Speaker 1: you're talking about a virtual world with like three dimensional 615 00:35:19,239 --> 00:35:22,080 Speaker 1: virtual space, but like web three. A lot of the 616 00:35:22,200 --> 00:35:25,160 Speaker 1: enthusiasm and excitement around the metaverse has kind of gone 617 00:35:25,200 --> 00:35:28,080 Speaker 1: cup put in recent years. There was a flurry of 618 00:35:28,120 --> 00:35:31,160 Speaker 1: excitement about the metaverse idea for a while, and you 619 00:35:31,239 --> 00:35:34,040 Speaker 1: had people and companies that were rushing to establish a 620 00:35:34,120 --> 00:35:38,759 Speaker 1: presence on various platforms, claiming that these platforms would become 621 00:35:38,880 --> 00:35:42,920 Speaker 1: pillars of the upcoming metaverse. But you don't hear about 622 00:35:42,960 --> 00:35:46,000 Speaker 1: that as frequently these days. It kind of blows my 623 00:35:46,080 --> 00:35:49,960 Speaker 1: mind that virtual real estate sold for real money, sometimes 624 00:35:50,239 --> 00:35:54,279 Speaker 1: a significant amount of real money, even before any such 625 00:35:54,320 --> 00:35:57,319 Speaker 1: platform had established itself, as you know, a real thing 626 00:35:57,360 --> 00:36:00,160 Speaker 1: that people wanted to go and spend time at. It's 627 00:36:00,239 --> 00:36:03,600 Speaker 1: kind of like this wild land rush, except land in 628 00:36:03,640 --> 00:36:06,520 Speaker 1: the real world is a finite resource, and the only 629 00:36:06,560 --> 00:36:10,319 Speaker 1: thing stopping yet another company from launching a virtual real 630 00:36:10,480 --> 00:36:14,560 Speaker 1: estate company is computational hardware. Scarcity is not really a 631 00:36:14,640 --> 00:36:17,480 Speaker 1: thing in the digital space, which again brings us back 632 00:36:17,480 --> 00:36:21,759 Speaker 1: to the challenges of digital assets and transactions anyway. Obviously, 633 00:36:21,800 --> 00:36:24,680 Speaker 1: there are still companies that are working on creating a metaverse, 634 00:36:24,719 --> 00:36:26,799 Speaker 1: but the question I have is how many folks are 635 00:36:26,840 --> 00:36:30,520 Speaker 1: actually itching for a metaverse. I wondered that from the 636 00:36:30,600 --> 00:36:33,720 Speaker 1: very beginning. I definitely wonder it. Now. Meta has spent 637 00:36:34,080 --> 00:36:37,759 Speaker 1: billions with a b of dollars on such efforts. It 638 00:36:37,800 --> 00:36:41,120 Speaker 1: continues to do this, much to the chagrin of investors, 639 00:36:41,320 --> 00:36:43,600 Speaker 1: and I am still not convinced that those efforts will 640 00:36:43,640 --> 00:36:46,880 Speaker 1: have a good return on investment. Maybe we'll get some 641 00:36:46,960 --> 00:36:49,319 Speaker 1: virtual environments out of it, and some of them might 642 00:36:49,360 --> 00:36:52,200 Speaker 1: even be really good and compelling experiences, but I don't 643 00:36:52,200 --> 00:36:54,200 Speaker 1: know that that's going to be enough to get the 644 00:36:54,239 --> 00:36:58,200 Speaker 1: results needed to make those billions of dollars a sound investment. 645 00:36:58,400 --> 00:37:00,880 Speaker 1: I don't know if it's going to make that, you know, 646 00:37:00,920 --> 00:37:04,839 Speaker 1: the metaverse the future of online interaction. But then again, 647 00:37:04,920 --> 00:37:08,520 Speaker 1: I'm not a genius anyway. There are tons of barriers 648 00:37:08,520 --> 00:37:10,719 Speaker 1: that the metaverse will have to overcome in order to 649 00:37:10,760 --> 00:37:13,439 Speaker 1: become a real thing. And real thing you can put 650 00:37:13,440 --> 00:37:16,560 Speaker 1: in air quotes. I guess, assuming that you know it 651 00:37:16,600 --> 00:37:19,680 Speaker 1: does involve virtual reality. One of the hurdles for the 652 00:37:19,680 --> 00:37:23,759 Speaker 1: metaverse is the cost to the consumer, because VR headsets 653 00:37:23,760 --> 00:37:26,920 Speaker 1: aren't cheap. Now, there are some headsets that are significantly 654 00:37:26,960 --> 00:37:30,520 Speaker 1: less expensive than earlier models, so they aren't necessarily as 655 00:37:30,600 --> 00:37:33,160 Speaker 1: expensive as they used to be, but they're still not cheap. 656 00:37:33,239 --> 00:37:36,840 Speaker 1: And computers are really versatile technologies, right, You can do 657 00:37:36,920 --> 00:37:39,719 Speaker 1: a lot of stuff on a computer. Now, you could 658 00:37:39,840 --> 00:37:42,560 Speaker 1: arguably do most of that same stuff, if not all 659 00:37:42,600 --> 00:37:45,719 Speaker 1: of it, while wearing VR gear as well, But that 660 00:37:45,760 --> 00:37:48,560 Speaker 1: requires a lot of work to design a really good 661 00:37:48,640 --> 00:37:51,360 Speaker 1: user interface so that the person who's wearing the VR 662 00:37:51,480 --> 00:37:53,560 Speaker 1: gear can do whatever it is they want to do 663 00:37:53,840 --> 00:37:56,840 Speaker 1: in a way that makes sense and feels natural. But 664 00:37:56,960 --> 00:37:58,840 Speaker 1: if you can already do pretty much all of that 665 00:37:58,920 --> 00:38:01,359 Speaker 1: stuff on a computer, you know, with the exception of 666 00:38:01,400 --> 00:38:05,000 Speaker 1: being in an immersive virtual environment, I'm not sure the 667 00:38:05,040 --> 00:38:08,360 Speaker 1: sales pitch is good enough to get people to buy in. Also, 668 00:38:08,440 --> 00:38:11,640 Speaker 1: this whole concept of an online world that is persistent 669 00:38:11,680 --> 00:38:15,120 Speaker 1: and virtual and even three dimensional isn't new. Folks have 670 00:38:15,120 --> 00:38:17,719 Speaker 1: been talking about that for years. Heck, you watch old 671 00:38:17,760 --> 00:38:21,560 Speaker 1: Hollywood films that represent the web, and it almost always 672 00:38:21,719 --> 00:38:24,400 Speaker 1: has someone seeing at a computer, and it looks like 673 00:38:24,440 --> 00:38:28,040 Speaker 1: they're playing some sort of weird first person shooter navigating 674 00:38:28,080 --> 00:38:30,880 Speaker 1: through stuff, because that looks way more exciting than just 675 00:38:30,920 --> 00:38:33,960 Speaker 1: staring at a page full of text and hyperlinks. Right, 676 00:38:34,160 --> 00:38:36,680 Speaker 1: But you know, navigating through a virtual space in order 677 00:38:36,719 --> 00:38:39,000 Speaker 1: to get to a destination has never made much sense 678 00:38:39,040 --> 00:38:42,600 Speaker 1: to me. Like, instead of having websites, having you know, 679 00:38:42,680 --> 00:38:46,080 Speaker 1: maybe like a virtual mall of stores and you have 680 00:38:46,120 --> 00:38:48,719 Speaker 1: to wander around in order to go to places, that 681 00:38:48,800 --> 00:38:51,520 Speaker 1: just doesn't make sense. Clicking on a link is super 682 00:38:51,640 --> 00:38:54,200 Speaker 1: fast and efficient, and sure you could build that kind 683 00:38:54,239 --> 00:38:56,440 Speaker 1: of capability into the metaverse, you know, maybe you make 684 00:38:56,480 --> 00:38:58,920 Speaker 1: it a voice command. But is the experience of just 685 00:38:59,000 --> 00:39:02,880 Speaker 1: teleporting from one virtual spot to another, perhaps, you know, 686 00:39:02,960 --> 00:39:04,799 Speaker 1: just to do some shopping, or maybe even just check 687 00:39:04,840 --> 00:39:07,399 Speaker 1: the news. Does that really sound like an experience most 688 00:39:07,400 --> 00:39:09,520 Speaker 1: people want to have, because I think it would be 689 00:39:09,560 --> 00:39:12,960 Speaker 1: pretty disorienting and distracting and inefficient. You could do it 690 00:39:13,160 --> 00:39:16,160 Speaker 1: so much faster just using a computer or a smartphone. 691 00:39:16,400 --> 00:39:18,480 Speaker 1: But really, whether you think like I do and you 692 00:39:18,520 --> 00:39:21,960 Speaker 1: find the whole metaverse concept puzzling, or if you think 693 00:39:22,000 --> 00:39:24,920 Speaker 1: it's a great idea, there's no getting around that. Tons 694 00:39:24,920 --> 00:39:28,080 Speaker 1: of folks and companies. We're using metaverse as shorthand for 695 00:39:28,840 --> 00:39:32,320 Speaker 1: this is the future. Nearly every press release or announcement 696 00:39:32,360 --> 00:39:35,040 Speaker 1: I saw relating to the metaverse said very little apart 697 00:39:35,040 --> 00:39:38,839 Speaker 1: from we're forward thinking and we're super cool, without you know, 698 00:39:39,120 --> 00:39:41,800 Speaker 1: doing anything to back up those claims. Just as cloud 699 00:39:41,800 --> 00:39:44,920 Speaker 1: computing and digital transformation can be used as buzzy shortcuts 700 00:39:44,960 --> 00:39:47,960 Speaker 1: to avoid addressing real challenges, I feel like the metaverse 701 00:39:47,960 --> 00:39:51,280 Speaker 1: and web three come across as more or less meaningless 702 00:39:51,360 --> 00:39:55,239 Speaker 1: terms used to proclaim relevance. You know, they might not 703 00:39:55,840 --> 00:39:58,879 Speaker 1: be anything today, but maybe tomorrow. Right, you'll see and 704 00:39:58,920 --> 00:40:01,359 Speaker 1: you'll see it from us, because we're hip and we're 705 00:40:01,400 --> 00:40:05,040 Speaker 1: with it. Okay, I'm really old, So maybe I'm just 706 00:40:05,120 --> 00:40:07,799 Speaker 1: way too cynical. Maybe it's brought on by the fact 707 00:40:07,840 --> 00:40:10,440 Speaker 1: that a lot of early attempts at showcasing ideas that 708 00:40:10,440 --> 00:40:13,400 Speaker 1: are at least intended to be incorporated into the metaverse 709 00:40:13,440 --> 00:40:17,320 Speaker 1: have been a bit disappointing. This brings me to mixed 710 00:40:17,520 --> 00:40:21,719 Speaker 1: reality now, y'all. I love me some mixed reality. I'm 711 00:40:21,760 --> 00:40:24,840 Speaker 1: not as big on VR these days. I acknowledge that 712 00:40:24,920 --> 00:40:28,000 Speaker 1: VR is the far more successful end of the mixed 713 00:40:28,040 --> 00:40:31,759 Speaker 1: reality spectrum. VR at least has established use cases in 714 00:40:31,800 --> 00:40:36,040 Speaker 1: the form of gaming. My problem is physiological because as 715 00:40:36,080 --> 00:40:38,840 Speaker 1: I get older, I get more prone to motion sickness, 716 00:40:38,880 --> 00:40:42,520 Speaker 1: which stinks. It's not the technology's fault necessarily, unless latency 717 00:40:42,560 --> 00:40:45,080 Speaker 1: is really bad, in which case it is the technology's fault. 718 00:40:45,239 --> 00:40:46,879 Speaker 1: But you know, I used to be the guy who 719 00:40:46,880 --> 00:40:49,680 Speaker 1: would ride a roller coaster two dozen times in a 720 00:40:49,800 --> 00:40:52,280 Speaker 1: day and think nothing of it. Now, if I ride 721 00:40:52,320 --> 00:40:54,520 Speaker 1: two different roller coasters in a row, I have to 722 00:40:54,560 --> 00:40:58,120 Speaker 1: lie down for forty minutes, So that's on me. But 723 00:40:58,400 --> 00:41:01,120 Speaker 1: VR has a place at the table, right It's an 724 00:41:01,239 --> 00:41:04,239 Speaker 1: established technology, and there are some great VR games and 725 00:41:04,280 --> 00:41:08,360 Speaker 1: experiences out there. It's still not necessarily a large enough 726 00:41:08,400 --> 00:41:11,800 Speaker 1: library of experiences to get a critical mass of users 727 00:41:11,800 --> 00:41:14,680 Speaker 1: on board, but the audience for VR tends to be 728 00:41:14,719 --> 00:41:18,720 Speaker 1: fairly enthusiastic or at least curious to try VR stuff. 729 00:41:18,800 --> 00:41:21,280 Speaker 1: I do know a few people who have VR setups 730 00:41:21,320 --> 00:41:23,440 Speaker 1: that have gone untouched for you know, long enough for 731 00:41:23,480 --> 00:41:25,800 Speaker 1: them to gather dust, So I don't know how common 732 00:41:25,840 --> 00:41:27,560 Speaker 1: that is. I'm sure there are people who use it 733 00:41:27,680 --> 00:41:30,279 Speaker 1: every day, you know. I've got a friend who uses 734 00:41:30,360 --> 00:41:33,759 Speaker 1: VR to do exercise with beat saber and that's you know, 735 00:41:33,840 --> 00:41:36,040 Speaker 1: she's not alone. Lots of people do that. It's on 736 00:41:36,120 --> 00:41:39,760 Speaker 1: the augmented reality side where I am actually the most interested. 737 00:41:40,120 --> 00:41:43,520 Speaker 1: But I simultaneously have to admit that not nearly enough 738 00:41:43,520 --> 00:41:45,960 Speaker 1: has been done in the AR space to make it 739 00:41:46,080 --> 00:41:49,840 Speaker 1: really useful outside of some very specific implementations. And I 740 00:41:49,880 --> 00:41:53,240 Speaker 1: think it's easy to imagine how AR could be useful, 741 00:41:53,560 --> 00:41:56,759 Speaker 1: Like if you can overlay digital information on your view 742 00:41:56,840 --> 00:41:59,520 Speaker 1: of the real world around you. There are countless ways 743 00:41:59,560 --> 00:42:03,080 Speaker 1: to make that really useful, everything from just entertaining to 744 00:42:03,360 --> 00:42:06,920 Speaker 1: genuinely answering questions or letting you do things more efficiently. 745 00:42:07,200 --> 00:42:10,239 Speaker 1: But while the technology has potential, we haven't really seen 746 00:42:10,280 --> 00:42:13,640 Speaker 1: that potential realized, and it's been a challenge so difficult 747 00:42:13,680 --> 00:42:16,800 Speaker 1: that even Apple appears to be struggling with it. Apple 748 00:42:16,920 --> 00:42:20,000 Speaker 1: launched the Vision Pro earlier this year. The year in 749 00:42:20,120 --> 00:42:22,760 Speaker 1: question is twenty twenty four for many of y'all listening 750 00:42:22,760 --> 00:42:25,759 Speaker 1: from the future. An initially word was that despite the 751 00:42:26,320 --> 00:42:29,920 Speaker 1: incredibly hefty price tag of three thousand, five hundred dollars 752 00:42:29,960 --> 00:42:33,680 Speaker 1: for the base model of this headset, the company was 753 00:42:33,719 --> 00:42:37,040 Speaker 1: actually going to sell out of its initial production run. However, 754 00:42:37,080 --> 00:42:39,880 Speaker 1: it's just a few months later and the story has changed. 755 00:42:40,000 --> 00:42:43,759 Speaker 1: An Apple analyst named Ming chi Quo posted that the 756 00:42:43,800 --> 00:42:46,640 Speaker 1: company was cutting orders by nearly half for the rest 757 00:42:46,680 --> 00:42:50,680 Speaker 1: of twenty twenty four, downgrading the expected unit sales that 758 00:42:50,760 --> 00:42:53,359 Speaker 1: initially were projected to be seven hundred to eight hundred 759 00:42:53,400 --> 00:42:56,800 Speaker 1: thousand units down to four hundred thousand to four hundred 760 00:42:56,800 --> 00:42:59,480 Speaker 1: and fifty thousand, which is a big old' oof because 761 00:42:59,480 --> 00:43:03,160 Speaker 1: demand dropped very quickly. Wes Davis of The Verge posted 762 00:43:03,200 --> 00:43:06,120 Speaker 1: an article recently that said he was finding listings on 763 00:43:06,160 --> 00:43:08,800 Speaker 1: eBay in which the headsets were selling for far below 764 00:43:08,880 --> 00:43:11,640 Speaker 1: market price, and Davis says it stings to know that 765 00:43:11,719 --> 00:43:14,000 Speaker 1: he could have waited and purchased a Vision Pro for 766 00:43:14,200 --> 00:43:16,480 Speaker 1: much less than what he actually paid for it when 767 00:43:16,520 --> 00:43:19,040 Speaker 1: it first became available. But really, I would argue that's 768 00:43:19,080 --> 00:43:21,480 Speaker 1: just the tip of the iceberg for consumer pain when 769 00:43:21,520 --> 00:43:24,319 Speaker 1: it comes to mixed reality, because I think the real 770 00:43:24,400 --> 00:43:28,240 Speaker 1: problem is that, facing a lack of a really big 771 00:43:28,360 --> 00:43:31,239 Speaker 1: user base, developers don't have a lot of reason to 772 00:43:31,320 --> 00:43:35,240 Speaker 1: make applications for AR hardware, because why would you spend 773 00:43:35,239 --> 00:43:38,360 Speaker 1: your time and your energy and your skills making something 774 00:43:38,640 --> 00:43:41,400 Speaker 1: that hardly anyone is going to get to use? But 775 00:43:41,480 --> 00:43:45,120 Speaker 1: if developers don't embrace the hardware, then consumers don't really 776 00:43:45,120 --> 00:43:48,040 Speaker 1: have an incentive to shell out the considerable amount of 777 00:43:48,080 --> 00:43:50,920 Speaker 1: money it costs to buy one of these headsets. It's 778 00:43:50,920 --> 00:43:53,759 Speaker 1: a catch twenty two issue, right because I don't want 779 00:43:53,760 --> 00:43:56,560 Speaker 1: a vision pro because I feel there aren't enough applications 780 00:43:56,560 --> 00:43:59,279 Speaker 1: for it. But no one's going to build applications for 781 00:43:59,360 --> 00:44:02,440 Speaker 1: the vision proh because people like me don't want to 782 00:44:02,520 --> 00:44:05,879 Speaker 1: purchase one. And then it's very possible that Apple will 783 00:44:05,960 --> 00:44:08,719 Speaker 1: either have to scale the tech way back so it 784 00:44:08,760 --> 00:44:12,719 Speaker 1: can introduce a significantly less expensive headset, which presumably would 785 00:44:12,719 --> 00:44:15,880 Speaker 1: have far fewer features and make it less attractive, or 786 00:44:16,480 --> 00:44:19,879 Speaker 1: just back away from the effort entirely and say this 787 00:44:19,960 --> 00:44:24,000 Speaker 1: one is a loss. My whole point is that if Apple, 788 00:44:24,360 --> 00:44:29,040 Speaker 1: with its famous reality distortion field, can't get mixed reality 789 00:44:29,040 --> 00:44:31,040 Speaker 1: to work in the market, it might just be too 790 00:44:31,120 --> 00:44:34,520 Speaker 1: early for that technology to take hold. Now, maybe someday 791 00:44:34,560 --> 00:44:37,200 Speaker 1: it'll be a big success, but it's going through its 792 00:44:37,200 --> 00:44:39,759 Speaker 1: own rough time, kind of similar to how VR really 793 00:44:39,800 --> 00:44:44,520 Speaker 1: struggled after a similar issue in the nineteen nineties after 794 00:44:44,560 --> 00:44:48,160 Speaker 1: that hype cycle kind of deflated. And this brings me 795 00:44:48,200 --> 00:44:50,799 Speaker 1: to a conclusion as well as a general warning that 796 00:44:50,920 --> 00:44:53,440 Speaker 1: I think it's really good to remember. If someone is 797 00:44:53,440 --> 00:44:57,319 Speaker 1: pushing very hard to sell you an idea, whether that 798 00:44:57,440 --> 00:45:01,640 Speaker 1: idea is AI, it's web three, a blockchain, or the 799 00:45:01,680 --> 00:45:05,600 Speaker 1: metaverse or mixed reality or anything like that, it often 800 00:45:05,840 --> 00:45:10,160 Speaker 1: indicates that the person talking to you is heavily invested 801 00:45:10,200 --> 00:45:13,640 Speaker 1: in that particular technology, and in order for their investment 802 00:45:13,680 --> 00:45:15,719 Speaker 1: to pay off, they need to get other folks to 803 00:45:15,760 --> 00:45:18,080 Speaker 1: buy into it. Now, I don't mean to say that 804 00:45:18,160 --> 00:45:21,239 Speaker 1: all of these ideas are ultimately nothing more than a 805 00:45:21,239 --> 00:45:24,560 Speaker 1: pyramid scheme, but they sure do operate that way in 806 00:45:24,600 --> 00:45:27,040 Speaker 1: the early days, and you don't get paid out unless 807 00:45:27,080 --> 00:45:31,080 Speaker 1: folks lower down the chain buy in. So buyer beware 808 00:45:31,160 --> 00:45:34,200 Speaker 1: is what I'm saying. Use critical thinking, make sure you 809 00:45:34,280 --> 00:45:37,360 Speaker 1: ask questions and make sure that the answers are satisfying 810 00:45:37,360 --> 00:45:39,520 Speaker 1: and that they mean something, and it's not just filled 811 00:45:39,520 --> 00:45:42,479 Speaker 1: with buzzwords and jargon. And for the leaders out there, 812 00:45:43,239 --> 00:45:46,320 Speaker 1: really think about different ways you can communicate your ideas 813 00:45:46,320 --> 00:45:51,279 Speaker 1: that aren't necessarily reliant on buzzwords, that actually do define 814 00:45:51,560 --> 00:45:56,680 Speaker 1: challenges and problems and solutions, because otherwise it starts to 815 00:45:56,840 --> 00:46:02,319 Speaker 1: sound like you're using language to cover the possibility that 816 00:46:02,360 --> 00:46:04,120 Speaker 1: you don't know what you're doing, and that's not a 817 00:46:04,120 --> 00:46:07,120 Speaker 1: good look at all. Doesn't serve anyone well in the 818 00:46:07,160 --> 00:46:09,839 Speaker 1: long run. All Right, that's it. Like I said, there 819 00:46:09,840 --> 00:46:13,520 Speaker 1: are tons of other buzzwords that we could include here, 820 00:46:13,760 --> 00:46:15,880 Speaker 1: and maybe I'll do another episode in the future with 821 00:46:15,960 --> 00:46:18,920 Speaker 1: more of these, but I thought this was a good 822 00:46:19,440 --> 00:46:23,399 Speaker 1: roundup for an episode like this. I hope you are 823 00:46:23,440 --> 00:46:27,080 Speaker 1: all well, and I'll talk to you again really soon. 824 00:46:32,960 --> 00:46:37,640 Speaker 1: Tech Stuff is an iHeartRadio production. For more podcasts from iHeartRadio, 825 00:46:37,960 --> 00:46:41,680 Speaker 1: visit the iHeartRadio app, Apple Podcasts, or wherever you listen 826 00:46:41,680 --> 00:46:46,360 Speaker 1: to your favorite shows.