1 00:00:05,670 --> 00:00:06,310 What? 2 00:00:08,530 --> 00:00:10,070 Oh, come on. 3 00:00:11,310 --> 00:00:12,190 That's okay. 4 00:00:12,670 --> 00:00:20,630 Okay, what I'd like to do is I'd like to get the slackers up here, up into this portion of the chairs. 5 00:00:20,930 --> 00:00:22,770 I have got some t-shirts that I'm going to give away. 6 00:00:22,770 --> 00:00:25,590 We're going to do a Q&A session and hopefully we're going to have a little bit of fun with this. 7 00:00:25,590 --> 00:00:26,610 Everybody looks bored. 8 00:00:26,610 --> 00:00:28,570 It's not going to be as bad as you think. 9 00:00:36,320 --> 00:00:40,920 Here is the mandatory personal anecdote. 10 00:00:40,960 --> 00:00:42,800 Okay, I'm in New Jersey right now. 11 00:00:43,360 --> 00:00:43,960 Yeah. 12 00:00:46,700 --> 00:00:48,460 So I'm on the plane, right? 13 00:00:48,740 --> 00:00:50,580 And we're getting ready to take off. 14 00:00:50,640 --> 00:00:54,200 And I've got two guys behind me. 15 00:00:54,200 --> 00:00:55,820 And I've got the cute girl next to him. 16 00:00:55,820 --> 00:00:57,860 And there's a guy over here that looks kind of goofy. 17 00:00:58,000 --> 00:00:59,860 And there's another girl next to him, right? 18 00:01:00,680 --> 00:01:04,180 So we're waiting to take off and I'm thinking these two don't know each other. 19 00:01:04,180 --> 00:01:05,700 These two don't know each other. 20 00:01:05,700 --> 00:01:06,800 We're headed to Vegas. 21 00:01:06,800 --> 00:01:09,000 There's all kinds of possibilities here, right? 22 00:01:09,880 --> 00:01:17,980 Then the dumb guy gets up, taps the girl on the shoulder and he says, Hey, would you mind moving over so that I can sit with my friend? 23 00:01:18,920 --> 00:01:22,560 That's when I knew that I had computer geeks behind me. 24 00:01:25,400 --> 00:01:26,360 True story. 25 00:01:26,360 --> 00:01:30,120 And somewhere I was hoping that there would be a guy here whose face would turn really red. 26 00:01:31,960 --> 00:01:34,560 Anyway, so they're behind me and they start talking geek speak. 27 00:01:34,560 --> 00:01:41,180 They start talking about XML and security and all this stuff, which past a certain point you get kind of tired of it. 28 00:01:42,520 --> 00:01:43,780 Then I got a surprise. 29 00:01:43,780 --> 00:01:44,840 These guys are all in their 20s. 30 00:01:44,840 --> 00:01:45,780 They're clean cut. 31 00:01:45,780 --> 00:01:49,720 They seem really driven by what they're doing, which is typical for DEF CON, I think. 32 00:01:51,500 --> 00:01:57,360 And then they're going through resumes and the one guy looks at a resume and he says, This guy's got a lot of technical knowledge. 33 00:01:57,540 --> 00:02:04,060 And the other guy looks and he says, Yeah, I interviewed him, but he doesn't have any business knowledge and he doesn't know what is of value and what is not. 34 00:02:04,060 --> 00:02:05,580 And that surprised me. 35 00:02:06,280 --> 00:02:07,400 That's what I look for now. 36 00:02:07,400 --> 00:02:08,800 I look for what things have value. 37 00:02:08,800 --> 00:02:18,280 I think we're in the midst of a change in the industry where we focus on what is of value rather than the mechanics of building things. 38 00:02:18,640 --> 00:02:20,260 So that's what our focus is going to be. 39 00:02:20,260 --> 00:02:26,300 It's going to be on keeping people employed through the industry because I personally don't believe that the shakeout is over yet. 40 00:02:28,620 --> 00:02:32,320 This is my other personal anecdote, which I decided was too egotistical. 41 00:02:32,940 --> 00:02:34,620 Why should you listen to me? 42 00:02:34,660 --> 00:02:37,180 I don't have a black t-shirt on, so maybe you shouldn't. 43 00:02:39,360 --> 00:02:43,300 What we're going to do, we're going to go through and we're going to hit three basic areas. 44 00:02:43,300 --> 00:02:48,780 We're going to lay out a couple simple business concepts, which are very common in MBA programs. 45 00:02:49,040 --> 00:02:51,780 They're common in large companies. 46 00:02:52,480 --> 00:02:54,740 We're going to lay those theories out. 47 00:02:54,740 --> 00:03:01,640 We're going to drive them down into a technical implementation that gives us concrete results that we can make decisions from. 48 00:03:01,920 --> 00:03:11,480 And then towards the end of the presentation, what I'm going to do is I'm going to throw out some strategic concepts to you, which are going to be a little bit radical, I think. 49 00:03:11,480 --> 00:03:12,120 We'll test it. 50 00:03:12,120 --> 00:03:12,460 We'll see. 51 00:03:12,460 --> 00:03:13,120 This is DEF CON. 52 00:03:13,120 --> 00:03:14,000 Maybe it won't be radical. 53 00:03:14,000 --> 00:03:15,160 Maybe nobody will care. 54 00:03:15,160 --> 00:03:24,020 But there's some ideas that I think that people can play around with and they might be able to turn them into additional concrete implementations in companies, things like that. 55 00:03:25,480 --> 00:03:26,280 Okay. 56 00:03:26,340 --> 00:03:27,720 Everybody watches the news, right? 57 00:03:27,720 --> 00:03:32,040 I took this a month ago and this is already out of date because there's already like a dozen more I could add on here. 58 00:03:32,200 --> 00:03:33,360 Layouts are still going on. 59 00:03:33,360 --> 00:03:35,340 People are still being laid off left and right. 60 00:03:35,880 --> 00:03:37,900 The crash is not over yet. 61 00:03:38,540 --> 00:03:47,960 Historically, industrial revolutions like this have seen a shakeout of approximately 30% of the peak population of the leading technologies. 62 00:03:47,960 --> 00:03:51,000 What we've seen in IT right now is about a 15% shakeout. 63 00:03:51,000 --> 00:03:56,740 So personally, I think that you're looking at another wave that will be equivalent to the last four years. 64 00:03:56,740 --> 00:04:00,740 How many people here have been laid off or out of work in the last five years? 65 00:04:02,140 --> 00:04:02,760 Yeah. 66 00:04:02,760 --> 00:04:03,420 And you know what? 67 00:04:03,420 --> 00:04:07,260 For every hand that's here, there's a guy that isn't here because he's not in the industry anymore. 68 00:04:07,260 --> 00:04:08,360 He got washed out. 69 00:04:08,360 --> 00:04:20,920 My goal here is to give people a little bit of knowledge so that they can make decisions that will keep them employed or it will let them make a decision to leave the industry now before they waste a lot of time on it. 70 00:04:21,940 --> 00:04:25,480 So either way, if that's the outcome here, I'm happy with either outcome. 71 00:04:27,900 --> 00:04:30,720 The time and effort that you put out to learn things is finite. 72 00:04:30,760 --> 00:04:34,180 If you learn something that has no value, you're fucked. 73 00:04:34,280 --> 00:04:34,760 Right? 74 00:04:34,760 --> 00:04:35,600 Your time is gone. 75 00:04:35,600 --> 00:04:36,700 You can't get it back. 76 00:04:36,720 --> 00:04:38,380 People are not going to pay you for it. 77 00:04:39,940 --> 00:04:50,600 Now, the skew here in DEF CON is a little bit different because you guys are in the security industry and I think you've got a substantially better chance of staying employed over the next four or five years than business. 78 00:04:50,600 --> 00:04:53,860 If you're in business software, I think you're going to be in trouble. 79 00:04:55,720 --> 00:04:57,940 IT market changes constantly, everybody knows that. 80 00:04:58,160 --> 00:05:02,680 What we're going to look at is we're going to try and focus on what kind of skills that we should be learning to stay employed. 81 00:05:05,380 --> 00:05:07,260 How many people know what a meme is? 82 00:05:09,080 --> 00:05:09,520 That's good. 83 00:05:09,520 --> 00:05:11,720 The first question I got asked when I walked in was, what is a meme? 84 00:05:11,720 --> 00:05:13,720 And I thought, oh my god, I should have put that up. 85 00:05:14,180 --> 00:05:19,580 A meme is an idea it's a mind virus that passes through a population. 86 00:05:19,960 --> 00:05:31,520 And typically, if you want to be completely theoretical about it, it starts with a single person, that person talks to two more, those two people talk to four people, four people talk to eight, so it's typically an exponential function. 87 00:05:32,880 --> 00:05:45,300 And it looks like an exponential function, a hyperbolic curve, until it reaches about the 50% mark of reaching the entire population and then, because you're getting people that already know it, you're talking to people, oh yeah, I already know that, I already know that, 88 00:05:45,300 --> 00:05:49,720 it starts tapering down and you get a drop-off as you reach market saturation. 89 00:05:50,580 --> 00:05:52,660 And that's typically known as an S-curve. 90 00:05:52,660 --> 00:05:54,760 How many people know the concept of an S-curve? 91 00:05:56,120 --> 00:05:57,100 Okay, that's good. 92 00:05:58,120 --> 00:05:59,460 Here's a picture of it. 93 00:05:59,580 --> 00:06:06,400 I start with a single point, it goes through a rapid run-up, it reaches the 50% point, and then I reach market saturation. 94 00:06:08,600 --> 00:06:13,420 This is a fundamental concept that you can apply in a lot of different situations, a surprising number. 95 00:06:13,820 --> 00:06:16,040 And it's simple, it's a simple concept. 96 00:06:17,940 --> 00:06:19,620 Ultimately, this is our goal. 97 00:06:20,120 --> 00:06:26,620 We want to eliminate getting into new technologies when they're first introduced because there's a very high failure rate. 98 00:06:26,640 --> 00:06:27,860 I don't want to be here. 99 00:06:27,860 --> 00:06:29,660 I don't want to be in the high-risk area. 100 00:06:30,060 --> 00:06:35,260 I don't want to be in the low-reward area because that's a technology on its way out and I can't make any money in it. 101 00:06:35,680 --> 00:06:44,960 What I want to do is I want to identify an area as it's ramping up, but I want to get it before it's at the 50% mark so I can make the most money off of it. 102 00:06:44,960 --> 00:07:00,360 Right here, I can make a decision that, yeah, this is probably going to stick around, this is probably going to be a viable technology, and I can ride the highest part of the wave off, which is the optimum profit point because other people are not paying attention and you're already in the market to learn these things. 103 00:07:00,360 --> 00:07:02,860 You're already in the market to sell your services in this. 104 00:07:03,000 --> 00:07:04,260 This is a simple concept. 105 00:07:04,360 --> 00:07:05,660 Does everybody grasp this? 106 00:07:05,660 --> 00:07:09,140 Can I get a show of hands where everybody thinks that this is... do you think it's important? 107 00:07:16,400 --> 00:07:21,220 The reason I care about an S-curve is it has predictive power into the future. 108 00:07:22,300 --> 00:07:24,300 How many people here know calculus? 109 00:07:25,440 --> 00:07:26,360 Oh, there you go. 110 00:07:26,360 --> 00:07:27,580 So you know this already. 111 00:07:28,740 --> 00:07:36,120 As this is ramping up, my rate of change is constantly increasing and I can measure that by doing empirical analysis on certain things. 112 00:07:36,120 --> 00:07:38,460 And I can see that the saturation is... 113 00:07:38,460 --> 00:07:42,140 or the propagation of the mean is rising. 114 00:07:42,180 --> 00:07:52,060 Once it reaches the 50% mark, where roughly I have 50% of the people know the mean's already propagated, it changes, I reach the inflection point and the rate of change begins decreasing. 115 00:07:52,060 --> 00:07:58,060 So if I can measure the rate of change and see that it's increasing, I know that I'm still on the pre-50% mark. 116 00:07:58,120 --> 00:08:00,820 Afterwards, I know that I'm after the 50% mark. 117 00:08:00,820 --> 00:08:02,520 So this is really what we look for. 118 00:08:02,520 --> 00:08:04,160 We look for a rate of change. 119 00:08:06,240 --> 00:08:07,560 Okay, peak oil. 120 00:08:07,560 --> 00:08:08,900 How many know about peak oil? 121 00:08:10,040 --> 00:08:12,940 Oh my god, now I'm stunned. 122 00:08:15,460 --> 00:08:22,640 Just as a quick overview, peak oil is the idea that oil resources are finite in the world. 123 00:08:22,720 --> 00:08:32,740 And there was a guy named Hubert which, in the 50s, he did basically an S-curve analysis at the rate at which they were finding oil drilling holes, you know, that they were making discoveries. 124 00:08:32,800 --> 00:08:39,620 And he graphed it down on a chart and he was able to see that in the United States that peak oil production would occur around 1970. 125 00:08:39,620 --> 00:08:41,300 And he was right within about a year. 126 00:08:41,300 --> 00:08:43,520 And he predicted it 15 to 20 years before it happened. 127 00:08:43,520 --> 00:08:47,260 This is all numbers off the top of my head, so I didn't actually expect to talk about this. 128 00:08:49,920 --> 00:08:55,440 What is probably very likely going to happen over the next few years is you're going to see peak oil occur worldwide. 129 00:08:55,740 --> 00:08:56,800 There's a lot of talk about it. 130 00:08:56,800 --> 00:09:00,540 If you do a search on the internet, Google peak oil, you'll get all kinds of information. 131 00:09:02,460 --> 00:09:04,760 Environmentalists have been talking about it for a long time. 132 00:09:05,160 --> 00:09:12,280 I'm not an environmentalist, but I understand the concept of how Hubert did the analysis, and I personally believe that this is very likely to happen. 133 00:09:12,280 --> 00:09:14,980 I think you're going to see peak oil happen within the next five years. 134 00:09:15,080 --> 00:09:17,260 And that's why you see oil prices being driven up. 135 00:09:17,260 --> 00:09:20,000 It's because there's a lot of guys like me sitting at companies like J.P. 136 00:09:20,000 --> 00:09:24,560 Morgan, and they're doing the same analysis, and they're saying, peak oil is probably going to happen. 137 00:09:24,560 --> 00:09:28,040 We need to get our money into oil now and make money on that. 138 00:09:28,880 --> 00:09:30,940 Oil prices at $60, right? 139 00:09:30,940 --> 00:09:32,360 Everybody thinks it's speculation? 140 00:09:32,360 --> 00:09:33,480 I don't think so. 141 00:09:35,160 --> 00:09:36,420 This is why you care. 142 00:09:36,420 --> 00:09:37,460 You can make money. 143 00:09:37,660 --> 00:09:42,180 Or you can avoid losing money, which depends on if you're risk averse or not. 144 00:09:44,360 --> 00:09:46,360 This is another example of an S-curve. 145 00:09:46,360 --> 00:09:47,800 How many people know Harry Dent? 146 00:09:48,520 --> 00:09:49,900 Yeah, that's not surprising. 147 00:09:49,900 --> 00:10:01,820 Harry Dent wrote a book in 1989 which was called The Great Boom Ahead, where he predicted that there would be a rapid IT boom, which would essentially look like an S-curve, and that's exactly what we saw from 1990 to 2000. 148 00:10:01,820 --> 00:10:08,980 We saw the entire information technology sector boom hugely beyond what anybody imagined, except Harry Dent did predict it. 149 00:10:08,980 --> 00:10:10,620 I don't buy a lot of his other theories. 150 00:10:10,620 --> 00:10:12,140 I do believe he was right. 151 00:10:12,140 --> 00:10:14,640 I mean, you can't deny that he was right about what he claimed. 152 00:10:14,720 --> 00:10:26,320 He made a second prediction in his book, which is that there will be a subsequent wave of S-curve technologies, which will build upon the infrastructure that was created in the first S-curve. 153 00:10:26,320 --> 00:10:28,120 That's where we're at right now. 154 00:10:29,100 --> 00:10:30,600 There's an infrastructure in place. 155 00:10:30,600 --> 00:10:31,520 There's networks everywhere. 156 00:10:31,520 --> 00:10:36,560 There's wireless networks, there's standards, there's TCP, IP, all the acronyms, all those things. 157 00:10:36,560 --> 00:10:37,920 It's too hard for me to remember. 158 00:10:38,380 --> 00:10:46,120 But ultimately, if you want to be looking where you should be, you don't want to be here anymore. 159 00:10:46,440 --> 00:10:50,000 This is foundational stuff that's in place, that's standard. 160 00:10:50,000 --> 00:10:51,600 It's not interesting to work on. 161 00:10:51,600 --> 00:10:56,080 It's maintenance work, and it doesn't pay a lot of money, and that's why you see a lot of things being outsourced now. 162 00:10:56,080 --> 00:11:01,800 It's stuff that's duplicatable, that we can send somewhere where there's a different kind of culture that adapts to those kind of things. 163 00:11:01,900 --> 00:11:09,660 What you want to be looking for is technologies that build on the existing infrastructure that was created in the last ten years. 164 00:11:11,560 --> 00:11:17,060 And I goofed up because I was going to give away a t-shirt if somebody told me what peak oil was and I blew it. 165 00:11:20,120 --> 00:11:21,860 Okay, MemMiner. 166 00:11:21,960 --> 00:11:33,400 This is a little tool that I made, which I've been doing this for about thirteen years, and basically it assumes that a frequency count, a word count on the internet is roughly equivalent to an S-curve growth of that technology. 167 00:11:33,460 --> 00:11:34,880 That's a big assumption, I know. 168 00:11:34,880 --> 00:11:37,100 And how many math people do we have in here? 169 00:11:37,700 --> 00:11:38,640 Oh, thank God. 170 00:11:39,360 --> 00:11:41,440 I don't have to worry about all the criticism. 171 00:11:42,160 --> 00:11:43,680 You get a ton of criticism. 172 00:11:43,680 --> 00:11:45,060 From my standpoint, I'm very pragmatic. 173 00:11:45,060 --> 00:11:48,060 I don't want to sit down and do a lot of analysis about probability and this and that. 174 00:11:48,060 --> 00:11:55,720 I just want a tool, a rough cut tool that will give me a way to make a decision quickly and easily without having to do a lot of analysis and a lot of guessing and things like that. 175 00:11:55,720 --> 00:11:56,860 And that's what this does. 176 00:11:57,800 --> 00:12:17,760 In my mind, I think of it as a data miner that anyone can implement and use in a small business and compete pretty well against large companies that have substantially more resources and better ideology, better methodology of how they do predictions. 177 00:12:21,520 --> 00:12:22,980 It's a simple little program. 178 00:12:26,420 --> 00:12:27,620 I'll go through and do it. 179 00:12:28,080 --> 00:12:30,280 I don't consider... does anybody want to see a demo of it? 180 00:12:30,280 --> 00:12:32,000 Do you need to see a Java code of it? 181 00:12:34,500 --> 00:12:36,100 How about if I do it at the end? 182 00:12:36,100 --> 00:12:37,920 I don't want to break out of this thing right now. 183 00:12:38,260 --> 00:12:40,120 But to me, it's really simple. 184 00:12:40,120 --> 00:12:40,480 It really is. 185 00:12:40,480 --> 00:12:42,140 It took me about 4 or 5 days to write it. 186 00:12:42,140 --> 00:12:44,620 Anybody could write it with basic programming knowledge. 187 00:12:44,940 --> 00:12:50,140 The key to it is the business concepts behind it and the application of those things. 188 00:12:52,320 --> 00:12:56,280 Okay, here's an example of one of the first graphs that I ran after I built the tool. 189 00:12:56,520 --> 00:12:58,540 This is the first T-Cert question. 190 00:12:58,900 --> 00:13:01,080 Can anybody tell me what this pattern is? 191 00:13:01,080 --> 00:13:02,620 What's driving this pattern? 192 00:13:06,820 --> 00:13:07,680 That's true. 193 00:13:07,680 --> 00:13:12,940 Okay, this is a graph made off of the keyword of work, but can you tell me why it's so rhythmic? 194 00:13:14,560 --> 00:13:15,360 Exactly. 195 00:13:15,780 --> 00:13:18,420 People don't talk about work on Saturday and Sunday. 196 00:13:18,760 --> 00:13:19,800 That's exactly right. 197 00:13:19,800 --> 00:13:21,060 So, T-Cert. 198 00:13:21,140 --> 00:13:22,520 I don't want to take those home. 199 00:13:24,900 --> 00:13:25,840 Saturday, Sunday. 200 00:13:25,840 --> 00:13:27,180 Monday, Tuesday, Wednesday, Thursday, Friday. 201 00:13:27,180 --> 00:13:29,820 And look, Wednesday really is the hump day. 202 00:13:33,760 --> 00:13:38,700 This is a small example that there really is data that you can extract out of the Internet. 203 00:13:38,700 --> 00:13:47,280 I use Deja News right now because Deja News, I've used it for several years because it gives me a time history and I don't have to previously know about a concept. 204 00:13:48,000 --> 00:13:50,520 You know, Deja News is being recorded all the time. 205 00:13:50,520 --> 00:13:52,020 So, let's say RSS comes along. 206 00:13:52,020 --> 00:13:53,260 And I'm not paying attention. 207 00:13:53,360 --> 00:13:55,940 And a year later I decide, oh, I should have been paying attention. 208 00:13:55,940 --> 00:13:57,540 I want to see what RSS is doing. 209 00:13:57,600 --> 00:13:59,960 Deja News has a history that I can go back and I can backfill it. 210 00:13:59,960 --> 00:14:01,040 You can see this graph. 211 00:14:01,280 --> 00:14:03,080 The date here is April 2002. 212 00:14:03,080 --> 00:14:04,740 I ran this graph two years ago. 213 00:14:05,960 --> 00:14:09,620 Okay, I was able to backfill it and figure out what was going on. 214 00:14:09,760 --> 00:14:22,600 The search engines, I have done pieces to do the same kind of analysis against the search engines, against Google, against Yahoo, a couple of the others, but they're very highly skewed to the present. 215 00:14:22,620 --> 00:14:33,160 You can recreate, you can make a crude approximation of the same data that you can get out of Deja News, but it's much less granular and it's just, you've got to do manipulations, it's really goofy. 216 00:14:33,160 --> 00:14:36,180 The search engines are very highly skewed to the present. 217 00:14:36,340 --> 00:14:41,840 You can't backfill data without doing a lot of analysis for more than 90 days or maybe a year . 218 00:14:42,840 --> 00:14:44,760 That's another key, using Deja News. 219 00:14:44,760 --> 00:14:50,800 Using some kind of pre-recorded data that had no knowledge of the fact that a trend was going on. 220 00:14:51,840 --> 00:14:53,980 Here's Easter Bunny, same thing. 221 00:14:54,380 --> 00:14:58,080 You can see every year, along comes Easter, people talk about Easter Bunny. 222 00:14:58,820 --> 00:15:01,980 The data is there waiting to be pulled out, you just have to know how to do it. 223 00:15:03,360 --> 00:15:04,320 Here's Comdex. 224 00:15:04,320 --> 00:15:07,240 Now, Comdex got cancelled in 2004, right? 225 00:15:07,340 --> 00:15:09,120 Actually, this isn't my new graph. 226 00:15:10,180 --> 00:15:11,860 Comdex got cancelled right here. 227 00:15:11,860 --> 00:15:17,680 If I had had this graph last year, like I did, is there any doubt in my mind that Comdex is going to get cancelled? 228 00:15:18,260 --> 00:15:19,620 There's not a lot of doubt. 229 00:15:19,620 --> 00:15:21,060 It was a predictable event. 230 00:15:21,080 --> 00:15:24,600 The fact that it got cancelled in 2005, same thing, a predictable event. 231 00:15:24,600 --> 00:15:28,440 You could have made money on it if you'd gone to the bookies and said, I think Comdex is going to be cancelled. 232 00:15:29,640 --> 00:15:32,600 Very clear trend, starting right here. 233 00:15:33,180 --> 00:15:35,020 Each successive high is lower. 234 00:15:35,020 --> 00:15:37,500 Does anybody do technical analysis of stocks? 235 00:15:38,360 --> 00:15:40,660 This is a very similar analogy. 236 00:15:40,700 --> 00:15:45,220 Each successive high never reaches the previous high, so we're clearly in a downtrend. 237 00:15:48,540 --> 00:15:49,920 Now, here's a graph. 238 00:15:49,920 --> 00:15:51,280 I went back later. 239 00:15:51,280 --> 00:15:52,040 You know, I'm not... 240 00:15:52,040 --> 00:15:56,640 I don't care about money a lot, but I wish I had. 241 00:15:57,060 --> 00:16:02,580 I went back and I retrofitted stuff on here, and I did keyword searches against stock prices of the bubble. 242 00:16:02,780 --> 00:16:05,760 The green is the stock price of Siebel. 243 00:16:05,780 --> 00:16:12,080 The blue is the frequency word count out of Deje News at the same time period, and what I did was I matched the amplitudes. 244 00:16:12,820 --> 00:16:15,600 You can see there's a... for Siebel, there's a very tight correlation. 245 00:16:15,600 --> 00:16:16,620 I mean, this is like a 90... 246 00:16:16,620 --> 00:16:19,740 you know, for the statistical people, this is close to a 90% correlation. 247 00:16:20,240 --> 00:16:29,240 Now, in this particular example, the word count does lag the actuality, so maybe it doesn't help you so much, but that's not always the case. 248 00:16:29,900 --> 00:16:31,220 Let's take a look at Palladium. 249 00:16:31,220 --> 00:16:34,760 Now, this is the one I really wish I had done in 2000. 250 00:16:35,300 --> 00:16:44,040 You can see clearly that there are rumors about Palladium's price spiking almost two years before it actually happens. 251 00:16:45,280 --> 00:16:46,480 Okay, right here. 252 00:16:46,480 --> 00:16:51,520 Although, if you really want to get technical and drive it back, you can say that maybe this was the peak, but that's still a year. 253 00:16:51,520 --> 00:16:58,360 A year before Platinum peaked, it was... you could have figured out that there was a good chance that Platinum was going to spike. 254 00:16:58,500 --> 00:17:06,120 And also, if you take a look, that when Platinum collapses, the keyword told you that it was going to collapse before it happened almost a year ahead of time. 255 00:17:07,020 --> 00:17:07,860 That's money. 256 00:17:07,860 --> 00:17:09,060 There's money right there. 257 00:17:09,060 --> 00:17:12,120 There are large companies that are doing all this analysis right now. 258 00:17:12,120 --> 00:17:16,940 The fact that they're doing this analysis... okay, you know, there's guys like me floating all around. 259 00:17:17,320 --> 00:17:24,740 I'm not really a large corporation guy, but there are guys in those corporations right now that are doing this and they understand all these concepts. 260 00:17:25,000 --> 00:17:31,440 And they've been piling onto the internet over the last five years and what they've done is they've cut the margin of where you can make the money. 261 00:17:31,560 --> 00:17:34,680 The latency is shrinking over the last four or five years. 262 00:17:34,680 --> 00:17:36,360 This is a very high latency a year. 263 00:17:36,420 --> 00:17:38,040 That's amazing to me. 264 00:17:38,040 --> 00:17:44,820 If you look at some of the later graphs that happened two or three years later, the latency has shrunk to like three months, four months, things like that. 265 00:17:44,820 --> 00:17:46,400 Sometimes it's down to like a month. 266 00:17:49,600 --> 00:17:50,680 Here's another example. 267 00:17:50,680 --> 00:17:51,680 Applied materials. 268 00:17:51,920 --> 00:17:53,060 There was a latency. 269 00:17:53,060 --> 00:17:58,840 Applied materials was clearly in an uptrend years before the price spike. 270 00:17:58,840 --> 00:18:05,460 And the keyword count told you that it was collapsing before the stock collapsed by about a quarter. 271 00:18:06,020 --> 00:18:09,480 And if you look right here, you can see that now the latency has disappeared out of it. 272 00:18:09,480 --> 00:18:13,980 There's a latency here in 2000 and as we go along, right about here, now there's no latency anymore. 273 00:18:31,150 --> 00:18:32,650 That's an excellent question. 274 00:18:32,650 --> 00:18:36,790 I've got a couple of other graphs that will show that it's very hard to determine and that's where there really is. 275 00:18:37,010 --> 00:18:39,330 There is no money to be made in mechanical 276 00:18:43,070 --> 00:18:43,830 skills. 277 00:18:43,830 --> 00:18:46,870 You can't make money in those things, especially in a global market. 278 00:18:46,890 --> 00:18:50,890 You have to move into something that requires some kind of artistic ability. 279 00:18:51,330 --> 00:18:58,390 And this particular mechanism right here does require a fair amount of interpretation and analysis that sometimes you're wrong. 280 00:18:58,390 --> 00:19:00,290 I mean, it's just the way it goes. 281 00:19:00,710 --> 00:19:08,110 In the case of Palladium, there were rumors flowing out of Russia that they were having problems and that they weren't going to make deliveries. 282 00:19:08,170 --> 00:19:12,070 So in that case, it was the lack of metal that drove the price spike. 283 00:19:12,530 --> 00:19:13,970 But you're absolutely right. 284 00:19:13,970 --> 00:19:26,330 There are cases where the rumor precedes and sometimes, you know, I'm not so sure that there isn't guys at some of the companies that are actually spiking the internet now in order to create an artificial demand in order to offload their stock or whatever it is. 285 00:19:26,330 --> 00:19:28,030 So that's something you've got to be careful of. 286 00:19:31,780 --> 00:19:33,000 I didn't run Enron. 287 00:19:33,000 --> 00:19:34,800 I didn't have any interest in Enron. 288 00:19:34,880 --> 00:19:36,480 I just looked at the dot com boom. 289 00:19:36,600 --> 00:19:40,380 But you're more than happy if you want the source code, you're more than happy to run Enron. 290 00:19:44,400 --> 00:19:45,280 Okay, JBuilder. 291 00:19:45,280 --> 00:19:47,220 How many programmers do we have in here? 292 00:19:48,420 --> 00:19:50,860 How many JBuilder programmers? 293 00:19:51,360 --> 00:19:52,160 Ah, interesting. 294 00:19:52,820 --> 00:19:55,020 You guys are all assembly, low level, right? 295 00:19:55,580 --> 00:19:58,000 What kind of languages do we have in here? 296 00:19:59,880 --> 00:20:01,820 Well, JBuilder, that's okay. 297 00:20:07,960 --> 00:20:13,060 This is a graph of JBuilder and it basically, you can see an S curve right here. 298 00:20:13,180 --> 00:20:14,760 The inflection point is roughly right here. 299 00:20:14,760 --> 00:20:18,740 And typically what you see, at the inflection point, your rate of change is infinite. 300 00:20:18,740 --> 00:20:25,020 As you're switching over from a rising to a falling rate of change, there's a spike there of infinite demand, theoretically. 301 00:20:25,160 --> 00:20:27,440 And you can see it reflected in this graph very clearly. 302 00:20:27,440 --> 00:20:33,140 There's a huge spike right at the time that JBuilder is undergoing its inflection point. 303 00:20:33,300 --> 00:20:37,500 And by about this time right here, you should have been out of JBuilder and you should have been doing something else. 304 00:20:37,500 --> 00:20:40,940 Although it's only been in the past year that it finally came to fruition. 305 00:20:41,080 --> 00:20:47,580 So there was a lag time of about two years before JBuilder finally died off and Borland had to admit it. 306 00:20:53,380 --> 00:20:59,020 No, you have to have a keyword that has uniqueness. 307 00:21:04,700 --> 00:21:06,420 Well, you have to do qualifiers. 308 00:21:07,020 --> 00:21:10,660 And I've got a couple other graphs in there further on where you'll see that, like ColdFusion. 309 00:21:10,660 --> 00:21:11,760 ColdFusion is a perfect one. 310 00:21:11,760 --> 00:21:17,260 I ran a graph on ColdFusion because I saw an article on it and there is some evidence to support that ColdFusion is real. 311 00:21:17,260 --> 00:21:20,740 So I ran a graph and I got this really strange graph that didn't make any sense to me. 312 00:21:20,880 --> 00:21:26,820 And about three days later, after I published it, I found out, oh right, it's ColdFusion the programming language. 313 00:21:27,480 --> 00:21:29,240 So it kind of made me look like a fool. 314 00:21:30,080 --> 00:21:34,040 So what I did for that graph was I added a new qualifier, ColdFusion Physics. 315 00:21:34,800 --> 00:21:36,980 And that gave me a much better picture of what was really going on. 316 00:21:36,980 --> 00:21:41,040 So yeah, you've got to be careful about keyword picks, which I have a little bit later on. 317 00:21:41,760 --> 00:21:42,220 Delphi. 318 00:21:42,220 --> 00:21:45,460 Now this is a real life example of something that I did in my own life. 319 00:21:45,520 --> 00:21:48,220 I got into Delphi around 95. 320 00:21:48,420 --> 00:21:49,800 I did programming on it. 321 00:21:49,800 --> 00:21:51,020 I wrote the wave up. 322 00:21:51,200 --> 00:21:56,420 And about 98 it was clear to me that this peak was over and I needed to do something different. 323 00:21:56,420 --> 00:21:58,300 So right in here I started learning Java. 324 00:21:58,320 --> 00:22:00,580 I went to Sun's conference. 325 00:22:00,580 --> 00:22:03,960 I started learning a whole different ideology and methodology of the way I did programs. 326 00:22:03,960 --> 00:22:06,580 And I switched over here and I missed the crash. 327 00:22:06,740 --> 00:22:07,900 There's a lot of Delphi programmers. 328 00:22:07,900 --> 00:22:09,160 Delphi is an extremely good language. 329 00:22:09,160 --> 00:22:09,800 I like it a lot. 330 00:22:09,800 --> 00:22:11,240 It's the best thing I ever used. 331 00:22:11,240 --> 00:22:12,920 I can't make money in it anymore. 332 00:22:13,180 --> 00:22:16,520 And there's a lot of ex-Delphi programmers that found that out the hard way. 333 00:22:19,480 --> 00:22:25,760 This, for some reason, I put this up and this is like the single most red graph on my site. 334 00:22:27,080 --> 00:22:29,860 The guys are just fanatical about scripting languages. 335 00:22:29,860 --> 00:22:31,180 It's very strange. 336 00:22:32,540 --> 00:22:35,460 Here you see Perl. 337 00:22:35,540 --> 00:22:36,920 Very clear rise. 338 00:22:36,920 --> 00:22:38,160 Very clear fall. 339 00:22:38,400 --> 00:22:40,300 Should have got out of it right around here. 340 00:22:40,500 --> 00:22:41,140 Maybe. 341 00:22:41,140 --> 00:22:42,360 Maybe should have. 342 00:22:43,060 --> 00:22:43,940 PHP. 343 00:22:44,220 --> 00:22:45,080 Same thing. 344 00:22:45,080 --> 00:22:45,540 Rises. 345 00:22:45,540 --> 00:22:46,760 Inflection points are roughly out here. 346 00:22:46,760 --> 00:22:48,020 It's not a true S-curve. 347 00:22:48,020 --> 00:22:48,800 It's not identical. 348 00:22:48,800 --> 00:22:51,320 But in real life that never happens because you get all kinds of variations. 349 00:22:51,320 --> 00:22:53,760 You just have to kind of guesstimate between peak and fall. 350 00:22:53,760 --> 00:22:56,800 And then Python and Ruby. 351 00:22:56,860 --> 00:23:04,100 Python, this doesn't show enough detail, but Python to me is the choice out of these four. 352 00:23:04,100 --> 00:23:07,680 If you were going to have to do a project right now I would choose Python. 353 00:23:07,680 --> 00:23:11,440 Assuming I could fit it into the requirements of the project. 354 00:23:11,440 --> 00:23:14,520 I mean you always get languages that fit a certain set of things. 355 00:23:14,580 --> 00:23:18,740 And you can't just choose a language in order to boost your employability. 356 00:23:18,740 --> 00:23:20,900 You have to look at what you're doing for the customer. 357 00:23:20,900 --> 00:23:30,300 There's also a very interesting thing that happens in the past year in that all scripting languages have suddenly got a high level of interest out of nowhere. 358 00:23:30,300 --> 00:23:32,180 And I don't know what drives that. 359 00:23:35,420 --> 00:23:36,080 YMAX. 360 00:23:36,080 --> 00:23:37,740 How many people know YMAX? 361 00:23:38,300 --> 00:23:39,740 YMAX is going to be big. 362 00:23:39,740 --> 00:23:42,280 I believe YMAX is going to be a big technology. 363 00:23:42,280 --> 00:23:52,920 YMAX basically replaces 802.11b with the same imagine 802.11b with a 30 mile range. 364 00:23:53,560 --> 00:23:57,220 And also I think, you guys can correct me I'm far from perfect. 365 00:23:57,220 --> 00:23:58,840 You can correct me if I'm wrong. 366 00:23:58,840 --> 00:24:04,320 But I believe that YMAX already has permission to be able to tap into cell phone networks. 367 00:24:04,320 --> 00:24:12,620 So you're going to see a huge amount of grassroots competition against the major wireless carriers from people setting up their own shops in YMAX. 368 00:24:12,620 --> 00:24:24,240 I can easily imagine someone getting a few million dollars of capital, dumping a few YMAX things in the center of maybe 30 cities and just cutting the hell out of Verizon's market or Singular's market. 369 00:24:27,900 --> 00:24:28,340 Blogs. 370 00:24:28,340 --> 00:24:29,760 This is an interesting one. 371 00:24:31,100 --> 00:24:32,420 This is a little bit more 372 00:24:35,720 --> 00:24:36,860 This is a question. 373 00:24:36,860 --> 00:24:38,260 This is a t-shirt question. 374 00:24:39,420 --> 00:24:40,900 You can see pretty clearly here. 375 00:24:40,900 --> 00:24:42,120 This is the moving average. 376 00:24:42,120 --> 00:24:43,160 You got to do a moving average. 377 00:24:43,160 --> 00:24:44,720 There's too many spikes that happen on the internet. 378 00:24:44,720 --> 00:24:46,160 Too many weird nuances. 379 00:24:46,420 --> 00:24:48,480 But basically by looking at a moving average you can get an idea. 380 00:24:48,480 --> 00:24:50,920 And we can see that blogs are clearly rising since 2002. 381 00:24:50,920 --> 00:24:55,020 And it was probably a good technology to get on around January 2004, which a lot of people did. 382 00:24:56,720 --> 00:25:05,740 Did anybody read the article that was in USA Today or one of the major papers about two months ago where they said that 27% of the public does not know what a blog is. 383 00:25:05,740 --> 00:25:06,860 Did anybody read that? 384 00:25:08,480 --> 00:25:10,180 Now tie those two numbers together. 385 00:25:10,180 --> 00:25:12,080 I have an inflection graph here, right? 386 00:25:12,140 --> 00:25:14,240 It hasn't reached a peak point yet. 387 00:25:14,420 --> 00:25:21,040 I know it's an exponential function and I know that 27% of the people have not been exposed to the meme yet. 388 00:25:21,720 --> 00:25:26,100 What kind of thing can I derive from that? 389 00:25:26,100 --> 00:25:27,840 I can make a prediction from that. 390 00:25:28,460 --> 00:25:29,140 T-shirt. 391 00:25:29,140 --> 00:25:30,680 Anybody that can tell me gets a t-shirt. 392 00:25:30,680 --> 00:25:32,900 Anybody that makes a good guess gets a t-shirt. 393 00:25:41,060 --> 00:25:42,760 Can you give me more detail? 394 00:25:46,180 --> 00:25:47,760 I don't want to go down the calculus path. 395 00:25:47,760 --> 00:25:48,960 It's too much stuff for me. 396 00:25:48,960 --> 00:25:51,780 I took what I needed from it and I threw the rest away. 397 00:25:52,420 --> 00:25:53,360 Anybody else? 398 00:25:53,360 --> 00:25:54,060 Down there. 399 00:25:54,080 --> 00:25:54,520 Black. 400 00:25:54,520 --> 00:25:55,320 Black shirt. 401 00:26:00,280 --> 00:26:02,420 It's going to peak within the next year. 402 00:26:02,540 --> 00:26:03,260 T-shirt. 403 00:26:20,770 --> 00:26:22,450 It's not going to be a big money maker. 404 00:26:22,530 --> 00:26:27,790 What you'll see is you'll see a lot of hysteria in the media over the next year and then that'll be it. 405 00:26:27,790 --> 00:26:29,530 It'll have peaked and it'll be ramping down. 406 00:26:29,530 --> 00:26:31,290 That doesn't mean you can't make money in it. 407 00:26:31,330 --> 00:26:32,810 All it is is an indicator. 408 00:26:32,810 --> 00:26:35,690 There are technologies that have peaked that you can still make money in. 409 00:26:37,430 --> 00:26:48,090 That's one thing I don't want to tell you is that if it goes through an inflection point and it peaks that you can't make money in anymore it's a warning indicator that tells you you need to look at the surroundings you need to look at your competition, 410 00:26:48,090 --> 00:26:53,050 you need to look at your skill set and make a knowledgeable decision about what you're going to do. 411 00:26:53,050 --> 00:26:55,810 You can make money in post like J2EE. 412 00:26:56,210 --> 00:26:58,130 I don't know, probably nobody here has read my site. 413 00:26:58,130 --> 00:27:07,990 I put a controversial article out about 3 months ago that got a lot of Java people riled up which basically says that J2EE is about to go through its inflection point. 414 00:27:08,010 --> 00:27:09,950 That it's peaked out as a technology. 415 00:27:09,990 --> 00:27:29,030 I have no interest in moving on to another technology right now because I still make money in it and I'll probably ride it for 3 or 4 more years but if I were an entry level person getting into the market I don't think I would choose J2EE because there's already going to be a bunch of guys like me that have experience and knowledge that are going to compete against you and the market isn't expanding anymore. 416 00:27:31,630 --> 00:27:34,050 Now, it's time for the half time here. 417 00:27:40,040 --> 00:27:44,880 How many people think so far that this has been more interesting than you thought it would be? 418 00:27:45,820 --> 00:27:47,420 Oh, that's so gratifying. 419 00:27:49,280 --> 00:27:51,200 I mean, I kind of took this as a lark. 420 00:27:51,200 --> 00:27:59,820 I sent in like a basic program, you know, basic speech People that have looked on the disk realize now that it's like about one third of what I'm doing right now. 421 00:27:59,820 --> 00:28:05,140 It was like a perfunctory effort and then I decided a couple days ago, well, I really need to do something serious on this. 422 00:28:05,540 --> 00:28:06,340 So that's nice. 423 00:28:06,340 --> 00:28:11,340 That's what was my aim was to get, to have people interested and have some kind of value out of this presentation. 424 00:28:13,300 --> 00:28:14,280 Wi-Fi phone. 425 00:28:14,280 --> 00:28:15,820 How many people know Wi-Fi phone? 426 00:28:16,820 --> 00:28:17,820 That's another big one. 427 00:28:17,820 --> 00:28:19,720 It's going to be tied into WiMAX, I think. 428 00:28:22,080 --> 00:28:23,680 Okay, so we already talked about this. 429 00:28:23,680 --> 00:28:26,160 Inflection point tends to be at about the 50% saturation point. 430 00:28:26,160 --> 00:28:27,520 That's not always true. 431 00:28:27,680 --> 00:28:28,860 That's just a rule of thumb. 432 00:28:28,860 --> 00:28:36,800 It's very easy to get and we'll look at another graph here later on where you get a quick ramp up but the infrastructure is not in place to support a technology. 433 00:28:36,800 --> 00:28:41,240 There's two technologies that tried to go through inflection points. 434 00:28:41,240 --> 00:28:43,800 They tried to go through a growth phase and the support just wasn't there. 435 00:28:43,800 --> 00:28:44,800 One of them is Bluetooth. 436 00:28:44,800 --> 00:28:48,180 I was here two years ago and there was a lot of Bluetooth fervor. 437 00:28:48,180 --> 00:28:49,740 There was a lot of Bluetooth hacking, things like that. 438 00:28:49,740 --> 00:29:00,760 So I went back and I did a graph on Bluetooth and I was surprised to see that Bluetooth tried to take off three or four years ago and it died out because there wasn't a critical mass to make it go. 439 00:29:00,920 --> 00:29:02,840 And then within the last two years it's picked up a lot. 440 00:29:02,840 --> 00:29:09,200 So a lot of times you'll see new technologies sputter and try and start and then they'll die out because there's some missing factor there. 441 00:29:09,200 --> 00:29:11,360 Service-oriented architecture is another one. 442 00:29:11,360 --> 00:29:16,560 It came out around 2000, 2001, the buzzword, all that, and it tried to take off and it died. 443 00:29:16,560 --> 00:29:20,320 But for the past 17 or 18 months it's been rising steadily. 444 00:29:20,320 --> 00:29:28,280 It's now something that organizations either understand and feel that they need or there's some critical component there that makes it viable. 445 00:29:30,240 --> 00:29:31,960 We already did the blogging. 446 00:29:32,380 --> 00:29:33,400 RSS feeds. 447 00:29:33,700 --> 00:29:35,800 This is very highly correlated to blogs. 448 00:29:35,800 --> 00:29:36,740 Same difference. 449 00:29:36,740 --> 00:29:39,540 By doing a search on and you can see here I used a qualifier. 450 00:29:39,600 --> 00:29:41,080 RSS RDF. 451 00:29:41,080 --> 00:29:42,900 I don't know if everybody can see that or not. 452 00:29:42,900 --> 00:29:44,520 People in back probably can't. 453 00:29:44,920 --> 00:29:48,420 So I used a qualified word here because RSS wasn't a good search. 454 00:29:51,300 --> 00:29:53,400 And now we're going to talk about the problems with this. 455 00:29:53,600 --> 00:29:57,000 The biggest single problem that I run into is that I'm part of the meme. 456 00:29:57,340 --> 00:29:58,900 How do I know to search for something? 457 00:29:58,900 --> 00:30:00,140 How do I know about RSS? 458 00:30:00,140 --> 00:30:01,140 I read it in an article. 459 00:30:01,140 --> 00:30:08,860 I'm part of the meme propagation and statistically I will learn about the meme at about the 50% mark which means I can't make any money in it. 460 00:30:10,660 --> 00:30:15,340 So I've got to figure out a way to track the meme before it gets to the 50% mark. 461 00:30:15,340 --> 00:30:17,840 I don't want to be like everybody else and be the average. 462 00:30:19,300 --> 00:30:22,220 So that's one problem with the methodology I'm using right now. 463 00:30:22,220 --> 00:30:30,640 What it requires is me to be reading articles all the time I have to spend a lot of time trying to be at the forefront of technology when there are easier ways to do it. 464 00:30:30,680 --> 00:30:34,400 It is subject to manipulation although not anywhere near as much as you would think. 465 00:30:34,400 --> 00:30:39,800 When you do a search off Deja News you are doing a search against hundreds of thousands and millions of people. 466 00:30:39,800 --> 00:30:43,420 It's very hard to inject a meme and create an artificial result. 467 00:30:43,420 --> 00:30:44,900 I know because I've tried. 468 00:30:45,420 --> 00:30:47,500 It's not statistically rigorous. 469 00:30:47,500 --> 00:30:50,080 There's a lot of criticism from people that are mathematicians. 470 00:30:50,080 --> 00:30:55,940 I've heard a lot of criticism about it and it is kind of flaky but it's worked well for me for 13 years. 471 00:30:56,160 --> 00:31:02,100 It's helped me make a lot of decisions where I could have easily gone off onto a bad path and ended up in another industry. 472 00:31:02,100 --> 00:31:06,160 Maybe that would be good, maybe that would be bad but that's not the path I chose. 473 00:31:07,460 --> 00:31:09,920 It works very well for technical trends. 474 00:31:10,140 --> 00:31:12,380 It does not work as well for social trends. 475 00:31:12,380 --> 00:31:18,780 It doesn't work for things that have lifetimes of 20 years or 30 years. 476 00:31:18,780 --> 00:31:22,720 It works very well for a range of 4 to 5 years and we'll look at why in a few minutes. 477 00:31:24,260 --> 00:31:33,660 If I were serious about using this as a technology to drive my company and make decisions with, I would throw away the current methodology of using Deja News. 478 00:31:34,120 --> 00:31:45,620 I would start capturing RSS feeds and I would build my own database and that will allow me to capture trends as they happen in real time and I guarantee you that there's people out there right now that are doing it. 479 00:31:46,200 --> 00:31:47,060 I did it. 480 00:31:47,060 --> 00:31:49,600 I wrote a little piece about 6 months ago. 481 00:31:49,660 --> 00:31:53,880 It has some technical problems but you can easily get around them if you spend enough time on it. 482 00:31:53,880 --> 00:32:06,260 I have a lot of other things to do but there is a lot of value to be done in applying this methodology to pulling down real time RSS feeds, building a database and looking at rates of change that are happening in keywords. 483 00:32:06,260 --> 00:32:07,940 I believe there's a lot of value there. 484 00:32:09,040 --> 00:32:11,260 We already talked about skewing factor. 485 00:32:11,260 --> 00:32:15,720 One of the problems is you lose abstract relationships with the way you store the RSS. 486 00:32:15,720 --> 00:32:18,220 There's some things there but they can be gotten around. 487 00:32:20,580 --> 00:32:23,700 Okay, so now we did the business process. 488 00:32:23,700 --> 00:32:28,500 We did a tactical implementation that gives us real decision making tools. 489 00:32:28,560 --> 00:32:36,820 Now what we're going to do is we're going to push this back up into a strategic framework that will let us make decisions about more than just about what technology I choose. 490 00:32:36,820 --> 00:32:39,540 And this, I admit, this is going to be kind of flaky. 491 00:32:42,000 --> 00:32:45,880 One of the big justifications for Moore's Law people like to quote Moore's Law. 492 00:32:45,880 --> 00:32:47,640 Everybody knows Moore's Law, right? 493 00:32:47,640 --> 00:32:49,540 How many people don't know Moore's Law? 494 00:32:52,620 --> 00:32:54,180 It's a trade off. 495 00:32:54,180 --> 00:32:56,220 I can't let Moore's Law go. 496 00:32:57,520 --> 00:33:07,960 It gets quoted a lot because it's used as a justification that the number of transistors will double every year so there will always be an IT industry that will continue booming. 497 00:33:09,260 --> 00:33:12,720 And I would agree with that if there were no other factors. 498 00:33:15,360 --> 00:33:19,160 People have a finite amount of time and effort to spend on anything. 499 00:33:21,940 --> 00:33:30,660 Geeks, techno geeks, they like technical things, they like trends, they like detail, but ultimately people are social animals. 500 00:33:30,660 --> 00:33:36,980 They will spend time on things that they enjoy or things that they're forced to do. 501 00:33:37,500 --> 00:33:42,520 Other things they will throw away in favor of things that they enjoy or things that they're forced to do. 502 00:33:42,800 --> 00:33:46,000 And this is part of the reason why the Memminer works off of Deja News. 503 00:33:46,000 --> 00:33:50,120 People talk about things that they enjoy or that they're forced to do. 504 00:33:51,200 --> 00:34:00,560 For the average person, they spend their time sleeping, working, I'm glad I got a laugh, that's good, shopping, eating, having sex. 505 00:34:01,440 --> 00:34:07,480 The range of that variance is not a lot from person to person on average. 506 00:34:07,840 --> 00:34:17,040 So if I want somebody to read the internet two hours a day and I get a certain level of growth, now to double that, I've got to have them read the internet four hours a day, it's not going to happen. 507 00:34:17,300 --> 00:34:18,840 They've got other things they want to go do. 508 00:34:18,840 --> 00:34:22,280 They want to go eat, they want to go have sex, they want to go visit Las Vegas. 509 00:34:22,380 --> 00:34:27,580 So there is a fundamental limiting factor in the growth of the internet based on what people's time is. 510 00:34:27,580 --> 00:34:29,240 There's other factors on top of that. 511 00:34:30,320 --> 00:34:34,440 Now for some people, you do get a wide variance. 512 00:34:36,860 --> 00:34:37,580 For instance... 513 00:34:41,670 --> 00:34:44,650 But I don't think we're going to see a society that looks like this. 514 00:34:47,700 --> 00:34:51,580 Now we're going to look at Deja News again, and what we're going to do is we're going to invert. 515 00:34:52,020 --> 00:34:54,180 What I was looking for was uniqueness, right? 516 00:34:54,800 --> 00:34:59,100 What we're going to look for now is the ether of Deja News. 517 00:34:59,100 --> 00:35:04,600 We're going to look for the rate of growth of Deja News abstracted of all uniqueness. 518 00:35:06,040 --> 00:35:13,560 What I'm going to do is I'm going to use keywords that have no identifying ability, that are used in anything, anytime. 519 00:35:14,120 --> 00:35:16,480 This, have, one, all, them, will, other. 520 00:35:16,480 --> 00:35:20,520 That comes out of the top number of people that do crypto analysis. 521 00:35:20,520 --> 00:35:22,900 E-T-A-O-N-R-I-S-H-D, right? 522 00:35:22,900 --> 00:35:26,420 That's what you do a frequency analysis to be able to crack codes that are not well done. 523 00:35:26,420 --> 00:35:28,400 Well, you can do the same thing with keywords. 524 00:35:28,560 --> 00:35:38,280 What I did was I went through the top 100 keywords and I picked out ones that were fairly generic, and then I did a search and you can see very clearly exponential growth in Deja News. 525 00:35:38,400 --> 00:35:44,660 This is one reason why the MemMiner works is because over any small period like from here to here, it looks linear. 526 00:35:45,800 --> 00:35:50,400 There's not skew being introduced by Deja News into the uniqueness of a meme. 527 00:35:50,400 --> 00:35:52,260 There's a little bit, but not enough to matter. 528 00:35:52,260 --> 00:35:57,320 Okay, so this is what the ether of Deja News looks like. 529 00:35:57,960 --> 00:35:58,920 The transport. 530 00:36:00,020 --> 00:36:04,340 If you do a really detailed search, you can pick out events that cause excitement on the internet. 531 00:36:05,520 --> 00:36:09,720 And these are admittedly, I guessed at them, I think I'm right on most of them. 532 00:36:09,800 --> 00:36:12,780 JFK crash, a lot of people can't see this, but there's a spike right here. 533 00:36:14,220 --> 00:36:17,020 Y2K causes a spike, there's a spike here I didn't hunt down. 534 00:36:17,180 --> 00:36:20,020 Bush election 2000, that definitely caused a controversy. 535 00:36:20,020 --> 00:36:21,820 9-11 causes a big spike. 536 00:36:21,900 --> 00:36:31,860 What's interesting about 9-11 is that if you do keyword searches on other terms, you get spikes. 537 00:36:31,860 --> 00:36:34,560 If you look for death around that time period, you get a spike. 538 00:36:34,560 --> 00:36:38,000 If you look for peace, you get a spike. 539 00:36:38,360 --> 00:36:39,980 What you don't get a spike in... 540 00:36:39,980 --> 00:36:43,060 Okay, remember, we're talking about people that have finite bandwidth, right? 541 00:36:43,060 --> 00:36:49,020 They're using more bandwidth to talk about 9-1-1, they're using more bandwidth to talk about death, they're using more bandwidth to talk about peace. 542 00:36:49,320 --> 00:36:54,660 What is being cut out of the equation to free up that bandwidth for those things? 543 00:36:54,920 --> 00:36:56,940 Can anybody give me an idea or a guess? 544 00:36:56,940 --> 00:36:58,700 It took me weeks to figure this out. 545 00:37:00,360 --> 00:37:05,940 No, there's, well, there's a particular thing that it cuts into, and I think it'll make sense to everybody once they hear. 546 00:37:06,700 --> 00:37:07,400 No. 547 00:37:12,720 --> 00:37:14,380 Work, who said work? 548 00:37:14,460 --> 00:37:15,260 T-shirt. 549 00:37:15,620 --> 00:37:16,640 Work goes down. 550 00:37:16,640 --> 00:37:18,880 And I remember 9-1-1, what did I do on 9-1-1? 551 00:37:18,880 --> 00:37:21,140 We all sat around talking, we didn't do any work. 552 00:37:25,550 --> 00:37:27,410 Now, here's the bad news. 553 00:37:29,990 --> 00:37:32,450 Deja News gets very flaky after 2004. 554 00:37:33,530 --> 00:37:35,590 I got a couple theories about it. 555 00:37:37,530 --> 00:37:39,390 I have three theories about it. 556 00:37:39,910 --> 00:37:41,710 One is the shift of blogging, clearly. 557 00:37:41,710 --> 00:37:44,270 What people were using Deja News for, they now use blogging for. 558 00:37:44,270 --> 00:37:46,690 But that does not account for the rate of change that you see here. 559 00:37:46,690 --> 00:37:47,890 This is almost instantaneous. 560 00:37:47,890 --> 00:37:55,150 You see the moving average here, but the actual numbers, it changes within like two months, and I know that's not happening. 561 00:37:55,150 --> 00:37:56,870 Blogging is taking away chunks. 562 00:37:57,390 --> 00:38:00,110 Google changes their methodology, their search methodology. 563 00:38:00,110 --> 00:38:03,010 If I go back and I run a query two or three months later, it changes. 564 00:38:03,010 --> 00:38:06,250 They're doing subtle shifts in the way they do things, and it shows up. 565 00:38:06,510 --> 00:38:13,390 And I do think that there's some kind of error in the way that they're manipulating or accounting for things after 2004. 566 00:38:13,470 --> 00:38:19,030 But I think a lot of what you're seeing is the inflection point in the internet itself. 567 00:38:19,250 --> 00:38:26,570 If you read enough articles, you see a couple articles came up in the past year or two that talk about a slowing rate of growth in the internet. 568 00:38:26,570 --> 00:38:27,830 I think that that's what you're seeing. 569 00:38:27,830 --> 00:38:36,450 I think you're seeing a slowing rate of growth in the internet, and it will impact all the other industries that are associated with that, mostly consumer-related industries. 570 00:38:36,630 --> 00:38:41,510 Chip industry, business software, it won't affect niche markets so much. 571 00:38:41,970 --> 00:38:44,110 And it probably won't affect security very much. 572 00:38:44,110 --> 00:38:54,610 And now, we're going to take a look at a couple concepts to make strategic decisions about how you're going to spend your resources. 573 00:38:58,030 --> 00:38:59,730 Very abstract concept. 574 00:38:59,770 --> 00:39:01,330 What caused the IT boom? 575 00:39:02,070 --> 00:39:18,390 If I were to create a market basket of all the items that create a cost of how I get information, chips cost me money, people cost me money, I have to develop methodologies, there's a lot of communications costs, I could create a market basket of the cost of information, 576 00:39:18,390 --> 00:39:24,950 assign it to a unit of information, and I would be able to get a rough number that each unit of information cost me a certain amount of money. 577 00:39:25,830 --> 00:39:28,830 Now, up until 2000, everybody was making money, right? 578 00:39:28,910 --> 00:39:31,390 That's because I have a price of information. 579 00:39:31,610 --> 00:39:35,910 I'm selling that information to somebody somewhere and I'm making a profit margin on it. 580 00:39:36,330 --> 00:39:49,250 As we get down to 2000, cost of information is not decreasing like it used to, and companies that are used to this curve, you know, they get into this mindset of seeing this, they overran it and they went into debt and they went out of business. 581 00:39:49,630 --> 00:39:53,570 Some companies veered off to the side and adapted and survived. 582 00:39:53,770 --> 00:40:02,270 But ultimately, if the cost of information stops falling, there are fundamental changes in the marketplace that companies are going to have to adapt to. 583 00:40:02,270 --> 00:40:14,250 And ultimately what you have to do, because market forces force you to adapt to a pricing model that the public sets, or governments, you have to find some way to drop your cost of information. 584 00:40:14,250 --> 00:40:17,050 And that's why you see outsourcing over the last 3 or 4 years. 585 00:40:17,050 --> 00:40:17,950 Companies have to. 586 00:40:17,950 --> 00:40:19,290 They have no choice. 587 00:40:19,430 --> 00:40:23,110 Otherwise they'll go out of business, because there is a ceiling on what they can charge. 588 00:40:23,590 --> 00:40:25,370 That's a very strategic concept. 589 00:40:25,990 --> 00:40:27,270 It sets the stage. 590 00:40:27,270 --> 00:40:28,890 You can't do anything with it directly. 591 00:40:28,890 --> 00:40:30,070 It's not a tool. 592 00:40:31,390 --> 00:40:35,730 And this is another picture that shows you roughly the same thing from an economic standpoint. 593 00:40:35,870 --> 00:40:40,310 As a market matures, your marginal cost of processing stuff rises. 594 00:40:40,310 --> 00:40:41,890 Your marginal return falls. 595 00:40:41,890 --> 00:40:46,310 You eventually reach a point where there is no profit margin, as you pick up all the easy things. 596 00:40:46,710 --> 00:40:49,250 What that means is that there is money in hard things. 597 00:40:50,170 --> 00:40:51,270 And the same difference. 598 00:40:51,950 --> 00:40:54,510 Now this is a theory of my own, just from watching the market. 599 00:40:55,030 --> 00:41:00,590 Watching the IT market for the last 10 or 15 years, the market rewarded diversity. 600 00:41:00,590 --> 00:41:09,250 As I created programs that did more and more stuff like Word, it does all the bells and whistles and stuff, I got a bigger and bigger share of the market, and people bought my product. 601 00:41:09,930 --> 00:41:16,850 But once I reached the point, the inflection point, the inflection point punishes diversity, and it rewards cost-cutting. 602 00:41:16,850 --> 00:41:21,290 And that's the point that we're at right now, for consumer-related industries. 603 00:41:21,290 --> 00:41:24,810 Like I said, there are niche markets that don't get impacted this way right now. 604 00:41:26,170 --> 00:41:28,810 So, from my standpoint, this is what I see. 605 00:41:29,430 --> 00:41:39,550 I see the up-cycle favoring diversity, and everyone pursuing that, and they get into a mindset over the last 20 years that diversity, diversity, diversity, I want to create a diverse product and get as much market share as possible. 606 00:41:39,550 --> 00:41:45,030 We've seen a fundamental change around 2000, which now punishes diversity and rewards cost. 607 00:41:45,090 --> 00:41:48,130 And most people's minds are still in this state. 608 00:41:54,300 --> 00:41:56,540 I don't know if I should go into this or not. 609 00:41:59,920 --> 00:42:03,380 This is the single most read picture on my site. 610 00:42:05,680 --> 00:42:07,240 And it surprised me a little bit. 611 00:42:08,780 --> 00:42:11,240 In a nutshell, 612 00:42:17,060 --> 00:42:20,600 diversity functions on contexts that are mismatched. 613 00:42:21,480 --> 00:42:32,300 If I had two clones, and they had identical information sets, and they know the exact same information, and they've had the exact same experiences, their communications and teamwork will be perfect. 614 00:42:32,300 --> 00:42:34,760 There will be no miscommunications, correct? 615 00:42:34,760 --> 00:42:48,220 As those clones have different life experiences, their contexts will shift apart, and there will be a set in the middle that they share, but there will be unique features that they each have, and then you'll start getting miscommunications. 616 00:42:48,340 --> 00:43:01,800 If I wanted to cut my cost of information in teamwork or software development, what I would do is I would try to get contexts to be as matched as possible within a team framework. 617 00:43:02,800 --> 00:43:16,220 Like I said, this is very high level, and there's some other things I played around with it, but I put it in there just to maybe get people thinking about ways that they could drive their teams or their software development towards a competitive methodology, 618 00:43:16,220 --> 00:43:22,100 and what you have to focus on is reducing transaction costs internally in your organization. 619 00:43:25,620 --> 00:43:26,640 There's a couple other things here. 620 00:43:26,640 --> 00:43:31,560 I'm sitting in a microbrewery, and I realized, wow, microbreweries are a lot like the software industry in certain ways. 621 00:43:32,020 --> 00:43:49,240 The company that I work for right now basically resells IBM software, but what we do is we tweak it to a very minimum level, five or ten percent, and match it to that set of customers that are willing to deal with changing their business processes to map to what the software does, 622 00:43:49,240 --> 00:43:52,680 and that's a very efficient model that I think can last over time. 623 00:43:52,680 --> 00:43:59,200 I don't think a lot of very customized software, it's going to have a very hard time surviving in business software over the next ten years. 624 00:44:00,760 --> 00:44:03,000 And we'll let that go. 625 00:44:03,000 --> 00:44:04,620 I'll go ahead and I'll take some questions. 626 00:44:19,030 --> 00:44:26,710 The question is, do I think that the difference between the dichotomy between diversity and cost-cutting is driving some of the open source movement? 627 00:44:27,090 --> 00:44:28,090 I don't know. 628 00:44:28,090 --> 00:44:32,870 I don't... I've looked at the open source movement and I still honestly don't have an opinion about it one way or the other. 629 00:44:32,870 --> 00:44:36,210 I can't get a reading on it out of the graphs that I've run. 630 00:44:36,390 --> 00:44:38,010 I can't speak to it one way or the other. 631 00:44:44,450 --> 00:44:53,970 I haven't done any analysis of that, but I would say companies that are doing Six Sigma are probably unless they're in like a financial industry, I think they're probably at a competitive disadvantage. 632 00:44:53,970 --> 00:44:56,570 I think they're producing quality that the market isn't going to reward. 633 00:44:58,450 --> 00:45:00,350 That's a guess off the top of my head. 634 00:45:05,890 --> 00:45:07,450 Yeah, you can use the search engines. 635 00:45:07,450 --> 00:45:09,850 You can get a lot of the same data out of Google. 636 00:45:10,090 --> 00:45:14,210 It comes out in a different format and you've got to massage it and you've got to work with it and it's very crude. 637 00:45:14,210 --> 00:45:17,250 It doesn't give you the same detail. 638 00:45:18,350 --> 00:45:19,990 But yeah, you can pull it out of other sources. 639 00:45:19,990 --> 00:45:20,930 I used to use Monster. 640 00:45:20,930 --> 00:45:22,630 I used to run queries against Monster. 641 00:45:22,630 --> 00:45:23,350 I used to use Dice. 642 00:45:23,350 --> 00:45:27,630 I used to use Miscellaneous Jobs News Group for people that remember that far back. 643 00:45:36,010 --> 00:45:38,710 No, I haven't done anything on security because that's not my field. 644 00:45:40,610 --> 00:45:41,470 One more. 645 00:45:43,230 --> 00:45:45,390 A lot of what you just saw, not in so much detail. 646 00:45:45,390 --> 00:45:49,070 There's more business here than I have on my website because I haven't updated for a while. 647 00:45:49,070 --> 00:45:55,450 There's a lot more graphs that show you more detail in different industries like religion. 648 00:45:55,450 --> 00:45:58,150 I did some queries on religion, social trends, things like that. 649 00:45:58,150 --> 00:45:59,790 So you can get an idea of different things. 650 00:45:59,790 --> 00:46:01,650 And actually, I did mean to bring that up. 651 00:46:03,610 --> 00:46:07,470 I'm not out of time yet, but we can look at a couple of those real quick. 652 00:46:13,940 --> 00:46:15,020 Or maybe not. 653 00:46:34,120 --> 00:46:40,300 There's no doubt in my mind after watching what's going on in the marketplace, there are a lot of people that are smarter than me. 654 00:46:40,620 --> 00:46:42,040 MBA program teaches all these things. 655 00:46:42,040 --> 00:46:42,860 I haven't been through MBA. 656 00:46:42,860 --> 00:46:46,580 I did a little bit of an MBA, but they teach you these kind of concepts and there are guys out there that are applying them. 657 00:46:46,580 --> 00:46:47,520 I have no doubts. 658 00:46:47,520 --> 00:46:51,480 You can see it in the way the information has been changing over the last five years. 659 00:46:51,480 --> 00:46:55,660 There's someone that's taken a chunk, taken a slice of the profit margin out of it. 660 00:46:57,760 --> 00:46:59,300 Let's see, what can we look at? 661 00:46:59,300 --> 00:47:01,180 Oh, here's saving J2E. 662 00:47:01,240 --> 00:47:05,160 If you go through here, you can see that J2E looks a lot like it's topping out. 663 00:47:06,100 --> 00:47:08,740 Yeah, these are good right here, Republicans. 664 00:47:09,380 --> 00:47:11,520 Does anybody care about the federal deficit? 665 00:47:13,140 --> 00:47:14,520 You bet people care. 666 00:47:14,520 --> 00:47:18,200 Whether the media tells you they care or not, it's being talked about a lot. 667 00:47:18,720 --> 00:47:19,580 Trade deficit. 668 00:47:19,580 --> 00:47:21,240 Does anybody care about the trade deficit? 669 00:47:22,520 --> 00:47:25,980 Media doesn't talk about it, but people are talking about it. 670 00:47:27,040 --> 00:47:31,160 You can get a lot of interesting information that runs counter to what the media is telling you. 671 00:47:31,540 --> 00:47:38,280 As a closing comment, I'll tell you that when you see Alan Greenspan talking on TV, don't listen to his words anymore. 672 00:47:38,320 --> 00:47:41,760 Watch the beads of perspiration on his forehead. 673 00:47:41,760 --> 00:47:43,180 That's what matters. 674 00:47:44,380 --> 00:47:45,440 And that's it. 675 00:47:45,680 --> 00:47:47,500 I got two more t-shirts up here. 676 00:47:47,500 --> 00:47:49,460 Two more t-shirts if people want to nab them. 677 00:47:56,040 --> 00:47:58,140 Oh, am I out of time? 678 00:47:58,360 --> 00:48:00,180 Do I have like two more minutes? 679 00:48:06,420 --> 00:48:07,400 Real meme. 680 00:48:07,400 --> 00:48:09,800 R-E-A-L-M-E-M-E. 681 00:48:15,820 --> 00:48:17,180 Yeah, yeah, that's what I'm doing right now. 682 00:48:17,180 --> 00:48:17,940 I'm going to run it. 683 00:48:18,180 --> 00:48:19,420 I got like a minute. 684 00:48:30,500 --> 00:48:32,040 It's a very simple program. 685 00:48:33,380 --> 00:48:35,120 Send me an email and I'll send you the base to it. 686 00:48:35,120 --> 00:48:39,400 I'm not going to support it because it's got a couple bugs in it that I work around because I don't want to spend time on it. 687 00:48:41,360 --> 00:48:43,600 But we'll run one real quick here that might be funny. 688 00:49:00,470 --> 00:49:01,750 No, I think there's profit. 689 00:49:01,750 --> 00:49:07,710 I think ultimately what you're going to be driven into is, at least in the United States, I think you're going to be driven into niche markets. 690 00:49:10,990 --> 00:49:12,990 In a single phrase. 691 00:49:13,490 --> 00:49:21,550 Niche markets that are supported by small industries that have high profit margins that are willing to pay for some level of customized software development. 692 00:49:22,550 --> 00:49:25,670 But that's a trend that's going to run over, I think, five to ten years. 693 00:49:25,670 --> 00:49:26,630 It's hard to say. 694 00:49:28,410 --> 00:49:31,650 I do think, for anybody that cares, I do think J2EE has peaked. 695 00:49:31,650 --> 00:49:39,250 And if I were entering the market, I don't think I would put any effort into trying to learn J2EE as an enterprise system. 696 00:49:39,250 --> 00:49:41,790 I think there's alternatives that are on the horizon. 697 00:49:42,530 --> 00:49:50,110 I think your time would be better spent in other things that are built upon the infrastructure of the existing S-curve that's already run. 698 00:49:51,550 --> 00:49:53,690 Oh, I was going to mention Newbridge. 699 00:49:54,070 --> 00:49:55,390 The Newberry guys in there. 700 00:49:55,390 --> 00:50:03,990 The Newberry guys in there that are running that that tracker, that wireless tracker, that's an example of a technology that's built on a foundation that's been built over the last ten years. 701 00:50:03,990 --> 00:50:05,530 That's the kind of thing I would look at. 702 00:50:07,490 --> 00:50:08,210 Okay. 703 00:50:27,600 --> 00:50:28,800 I look for it. 704 00:50:28,800 --> 00:50:30,780 I see it. 705 00:50:30,780 --> 00:50:32,880 It comes up in different places in different ways. 706 00:50:32,880 --> 00:50:34,100 It's intuitive. 707 00:50:34,100 --> 00:50:35,240 It's from seeing it so often. 708 00:50:35,240 --> 00:50:38,260 It happens around 2004, 2005. 709 00:50:41,700 --> 00:50:43,460 Gosh, I'm really sorry here. 710 00:50:43,460 --> 00:50:44,540 One more minute. 711 00:51:06,720 --> 00:51:11,120 Well, if I have a good net connection and I'm running it threaded, probably 20, 30 seconds. 712 00:51:14,080 --> 00:51:16,680 Yeah, I have done run RFID and that's on my site. 713 00:51:17,740 --> 00:51:18,700 It's in an uptrend. 714 00:51:18,700 --> 00:51:20,180 It's in a pre-inflection state. 715 00:51:21,640 --> 00:51:23,300 Definitely worth putting money into. 716 00:51:25,880 --> 00:51:26,500 Hmm? 717 00:51:34,030 --> 00:51:35,610 That's a whole other session. 718 00:51:36,970 --> 00:51:38,610 That's a political session. 719 00:51:40,150 --> 00:51:41,390 No, I don't blame you. 720 00:51:42,290 --> 00:51:44,090 Anyway, here's Paris Hilton. 721 00:51:45,750 --> 00:51:47,670 She's still got some life there. 722 00:51:47,670 --> 00:51:48,390 I'm surprised. 723 00:51:48,390 --> 00:51:49,590 I didn't expect it. 724 00:51:50,470 --> 00:51:51,710 Okay, thank you.