1 00:00:00,160 --> 00:00:02,040 Speaker 1: Rich Tomorrow. It is Tuesday. 2 00:00:02,840 --> 00:00:05,360 Speaker 2: Rich on Tech every Saturday right here at eleven am 3 00:00:05,400 --> 00:00:06,199 Speaker 2: to two pm. 4 00:00:06,600 --> 00:00:08,240 Speaker 1: Is on KTLA TV. 5 00:00:08,080 --> 00:00:13,240 Speaker 2: Every morning, Instagram at rich on Tech website, Richontech dot TV, 6 00:00:14,120 --> 00:00:16,319 Speaker 2: and Happy Tuesday, Rich, Good. 7 00:00:16,239 --> 00:00:21,239 Speaker 3: Morning, Happy Tuesday too. I'm surprised you didn't say Taco Tuesday. 8 00:00:21,760 --> 00:00:25,200 Speaker 2: I generally do say Taco Tuesday. By the way, I 9 00:00:25,280 --> 00:00:28,920 Speaker 2: just missed out. Yeah today, It's only eighty percent of 10 00:00:28,960 --> 00:00:31,600 Speaker 2: the time that I've been saying Taco Tuesday. So I 11 00:00:31,720 --> 00:00:36,680 Speaker 2: humbly apologize that I didn't say it. Starting with this segment, Okay, 12 00:00:36,720 --> 00:00:38,680 Speaker 2: we got a lot of stuff to cover, and hope 13 00:00:38,680 --> 00:00:41,440 Speaker 2: we get to as many of them as we can. 14 00:00:41,920 --> 00:00:45,400 Speaker 2: Let's start the most controversial gadget you have ever tested. 15 00:00:47,000 --> 00:00:50,960 Speaker 3: This one's wild. This is called b It's a fifty 16 00:00:51,000 --> 00:00:56,640 Speaker 3: dollars wristband, and it basically listens to your day and 17 00:00:57,040 --> 00:01:01,760 Speaker 3: captures that audio, transcribes it, and uses AI to come 18 00:01:01,880 --> 00:01:05,319 Speaker 3: up with insights, to come up with patterns, to come 19 00:01:05,400 --> 00:01:08,759 Speaker 3: up with facts about you, to do lists, I mean, 20 00:01:08,840 --> 00:01:11,039 Speaker 3: all kinds of stuff. It's kind of like a if 21 00:01:11,080 --> 00:01:13,399 Speaker 3: you had a personal assistant that walked around with you 22 00:01:13,560 --> 00:01:18,120 Speaker 3: all day and just took notes and to the app, 23 00:01:18,120 --> 00:01:21,199 Speaker 3: but it's all there, yeah, analyzes, so it's wow. Yeah. 24 00:01:21,240 --> 00:01:24,560 Speaker 2: So if you so, if you're you get religion during 25 00:01:24,880 --> 00:01:27,400 Speaker 2: the day in the evening and you're screaming oh God, 26 00:01:27,520 --> 00:01:30,360 Speaker 2: oh God at the top of your lungs. Uh, that 27 00:01:30,440 --> 00:01:32,280 Speaker 2: will be analyzed, correct. 28 00:01:33,440 --> 00:01:37,400 Speaker 3: Yes, it will be. Yeah, you should maybe take this 29 00:01:37,480 --> 00:01:41,400 Speaker 3: thing off if if you're you're practicing your religion. It's 30 00:01:41,440 --> 00:01:43,199 Speaker 3: called b by the way, and this is a company. 31 00:01:43,240 --> 00:01:46,679 Speaker 3: It was a startup. Amazon bought them shortly after they 32 00:01:46,720 --> 00:01:49,480 Speaker 3: were created, so now it's owned by Amazon. They call 33 00:01:49,520 --> 00:01:53,160 Speaker 3: it an ambient AI computing band, so, uh, it looks 34 00:01:53,200 --> 00:01:55,960 Speaker 3: like a fitbit basically, it's really small. I wore it 35 00:01:56,000 --> 00:01:58,800 Speaker 3: for a couple of weeks and uh, you know it's 36 00:01:58,880 --> 00:02:01,040 Speaker 3: kind of and you're the lawyer here, but you know 37 00:02:01,160 --> 00:02:03,960 Speaker 3: it's listening. So a lot of people have emailed me said, Rich, 38 00:02:04,000 --> 00:02:06,120 Speaker 3: this is legal in California. You can't it's a two 39 00:02:06,160 --> 00:02:10,800 Speaker 3: party consent state. Amazon says that this is actually not recording, 40 00:02:10,919 --> 00:02:15,480 Speaker 3: it's it's capturing whatever that like, the audio is not saved, 41 00:02:15,680 --> 00:02:18,839 Speaker 3: so it's I just found it really fascinating. I don't 42 00:02:18,880 --> 00:02:20,720 Speaker 3: know if I want to wear this thing long term 43 00:02:20,760 --> 00:02:22,520 Speaker 3: because it does capture everything. 44 00:02:22,840 --> 00:02:25,720 Speaker 2: Yeah, that is an interesting legal issue. 45 00:02:26,040 --> 00:02:28,040 Speaker 1: I love that. Is it for sale now? Is it 46 00:02:28,080 --> 00:02:28,480 Speaker 1: out there? 47 00:02:29,240 --> 00:02:31,840 Speaker 3: Yeah, it's for sales. Fifty bucks the battery last two week. 48 00:02:31,919 --> 00:02:33,840 Speaker 2: Right, you have said that's I mean, that's not very 49 00:02:33,919 --> 00:02:39,560 Speaker 2: much money. Okay, let's let's keep on going. There's a 50 00:02:39,680 --> 00:02:43,640 Speaker 2: trial and we talked about this before, but it's going 51 00:02:43,680 --> 00:02:47,760 Speaker 2: on right now in Los Angeles. And this is huge. 52 00:02:47,800 --> 00:02:50,160 Speaker 2: I mean it's not being covered enough. And that is 53 00:02:50,360 --> 00:02:55,320 Speaker 2: the addiction trial where all the major platforms basically are 54 00:02:55,360 --> 00:03:00,200 Speaker 2: being sued because kids are addicted and they're planning it, 55 00:03:01,080 --> 00:03:03,920 Speaker 2: I meaning their platforms. 56 00:03:03,960 --> 00:03:05,040 Speaker 1: So what's going on with that. 57 00:03:06,400 --> 00:03:08,280 Speaker 3: Right Well, that's the question they're trying to figure out 58 00:03:08,360 --> 00:03:11,120 Speaker 3: in the court of law here in Los Angeles. So 59 00:03:11,160 --> 00:03:14,680 Speaker 3: the defendants right now are Meta, which owns Facebook and Instagram, 60 00:03:14,880 --> 00:03:17,119 Speaker 3: and then Google's YouTube which a lot of kids watch 61 00:03:17,160 --> 00:03:21,200 Speaker 3: what's called YouTube shorts, that's their version of TikTok. TikTok. 62 00:03:21,400 --> 00:03:24,800 Speaker 3: And Snap actually already settled right before the trial started, 63 00:03:24,840 --> 00:03:27,400 Speaker 3: so we don't know what they settled for, how much 64 00:03:27,440 --> 00:03:29,920 Speaker 3: they settle. But the plaintiff here is a twenty year 65 00:03:29,960 --> 00:03:32,720 Speaker 3: old woman who says she became addicted to these platforms 66 00:03:32,720 --> 00:03:38,280 Speaker 3: as a teenager, she developed anxiety depression, body dysmorphia, and 67 00:03:38,320 --> 00:03:40,920 Speaker 3: her lawyers say that it was all because these apps 68 00:03:40,920 --> 00:03:43,119 Speaker 3: are designed to keep you scrolling. They use all kinds 69 00:03:43,160 --> 00:03:46,560 Speaker 3: of hacks and tricks to just get capture attention and 70 00:03:46,640 --> 00:03:50,200 Speaker 3: never let it go. Meanwhile, YouTube and Meta deny all 71 00:03:50,240 --> 00:03:52,120 Speaker 3: of this, of course, as they would as they are 72 00:03:52,160 --> 00:03:55,920 Speaker 3: big companies. They say that no, it's not their apps 73 00:03:55,960 --> 00:03:58,520 Speaker 3: that caused all these things for her, it's her family 74 00:03:58,600 --> 00:04:01,000 Speaker 3: trauma that caused it all. And so now this is 75 00:04:01,040 --> 00:04:04,360 Speaker 3: the first big test case. And if if this woman 76 00:04:04,440 --> 00:04:08,040 Speaker 3: wins basically as I understand it, there would it would 77 00:04:08,080 --> 00:04:11,400 Speaker 3: open the floodgates for thousands of other similar cases across 78 00:04:11,440 --> 00:04:14,280 Speaker 3: the US, which might trigger, you know, some sort of 79 00:04:14,280 --> 00:04:15,480 Speaker 3: class action or something like that. 80 00:04:15,640 --> 00:04:19,000 Speaker 2: I can't imagine that it would be a class action lawsuit. 81 00:04:19,160 --> 00:04:21,560 Speaker 2: It couldn't even begin to think that it would not be. 82 00:04:22,400 --> 00:04:25,960 Speaker 2: And the as you said, the settlement of those two 83 00:04:26,040 --> 00:04:29,880 Speaker 2: big ones, and they never talk about the amount of 84 00:04:29,880 --> 00:04:33,440 Speaker 2: money that settled, or admitting liability or any of it. 85 00:04:33,440 --> 00:04:36,479 Speaker 1: It has to be in the billions and billions of 86 00:04:36,520 --> 00:04:38,600 Speaker 1: dollars that the settlement has already happened. 87 00:04:38,640 --> 00:04:43,320 Speaker 2: It almost reminds me of the big tobacco That settlement 88 00:04:43,520 --> 00:04:46,480 Speaker 2: was I think over one hundred billion dollars and the 89 00:04:46,480 --> 00:04:53,520 Speaker 2: pharma industry with fall with the Purdue leading the leading 90 00:04:53,520 --> 00:04:58,160 Speaker 2: the list of defendants, and that went for set I 91 00:04:58,200 --> 00:04:59,040 Speaker 2: don't even know how much. 92 00:04:59,040 --> 00:05:01,360 Speaker 1: It went for one hundreds something billion dollars. I mean, 93 00:05:01,400 --> 00:05:02,400 Speaker 1: it's uh. 94 00:05:02,640 --> 00:05:05,320 Speaker 2: And the number of planets as astronomical as you said, 95 00:05:05,320 --> 00:05:07,840 Speaker 2: this is going to just explode in terms of these 96 00:05:07,920 --> 00:05:11,159 Speaker 2: lawsuits to the point where these companies are going to take. 97 00:05:11,000 --> 00:05:14,720 Speaker 1: A really good hit, a big hit, and then they 98 00:05:14,760 --> 00:05:15,520 Speaker 1: have to rea not. 99 00:05:15,480 --> 00:05:17,560 Speaker 3: Just a hit, but yeah, they got to they got 100 00:05:17,560 --> 00:05:20,000 Speaker 3: to think about, you know, their actions in the future. 101 00:05:20,279 --> 00:05:22,560 Speaker 3: But you know how they design these apps? How you know, 102 00:05:22,839 --> 00:05:25,080 Speaker 3: are they addictive? Do they are they a little mini 103 00:05:25,160 --> 00:05:27,280 Speaker 3: slot machine in your pocket? You know? Are they are 104 00:05:27,360 --> 00:05:30,719 Speaker 3: they targeting kids? And I think Bill, you can comment 105 00:05:30,720 --> 00:05:32,560 Speaker 3: on this more. I think it really comes down to 106 00:05:33,240 --> 00:05:35,520 Speaker 3: the jury here is is there I assume there's a 107 00:05:35,600 --> 00:05:38,520 Speaker 3: jury in this case, But it comes down to you know, 108 00:05:38,600 --> 00:05:41,360 Speaker 3: if anyone has kids and they've seen the effect that 109 00:05:41,400 --> 00:05:45,000 Speaker 3: these apps and services have on their children, or their 110 00:05:45,000 --> 00:05:48,760 Speaker 3: grandkids or any kids or their teacher. They know that 111 00:05:48,839 --> 00:05:51,880 Speaker 3: they do hook kids in and these kids cannot escape it. 112 00:05:52,040 --> 00:05:54,279 Speaker 3: Some adults can't escape it. So I think that that 113 00:05:54,440 --> 00:05:56,720 Speaker 3: is the big question here is you know who in 114 00:05:56,760 --> 00:05:58,560 Speaker 3: the world is going to say that these apps are 115 00:05:58,600 --> 00:06:02,960 Speaker 3: not designed to keep you going forever until your eyeballs 116 00:06:03,000 --> 00:06:03,640 Speaker 3: fall out of your head. 117 00:06:03,680 --> 00:06:05,720 Speaker 1: Like I say, by the way, just. 118 00:06:05,839 --> 00:06:07,479 Speaker 2: A personal note, And I don't know if you can 119 00:06:07,680 --> 00:06:10,440 Speaker 2: make this prediction be you being a new person. Do 120 00:06:10,520 --> 00:06:16,760 Speaker 2: you believe that those those apps are designed to grab kids? 121 00:06:17,000 --> 00:06:19,479 Speaker 3: There's not even a doubt in my mind. Now is 122 00:06:19,480 --> 00:06:22,200 Speaker 3: it written on paper bill like in the emails between 123 00:06:22,279 --> 00:06:25,120 Speaker 3: Zuckerberg and you know his staff saying hey make this 124 00:06:25,160 --> 00:06:28,039 Speaker 3: more addictive? Probably not. But if you don't think that 125 00:06:28,120 --> 00:06:31,120 Speaker 3: these companies are sitting there trying to figure out a 126 00:06:31,160 --> 00:06:33,720 Speaker 3: way to make these apps stickier than the other one, 127 00:06:34,880 --> 00:06:37,280 Speaker 3: it's just there's no number one from a business standpoint, 128 00:06:37,279 --> 00:06:39,120 Speaker 3: that's what you want. They're not sitting here saying how 129 00:06:39,120 --> 00:06:41,720 Speaker 3: can we protect kids? They only protect kids when the 130 00:06:41,800 --> 00:06:44,320 Speaker 3: law tells them they have to, or they're worried about 131 00:06:44,360 --> 00:06:45,520 Speaker 3: the law telling them they have to. 132 00:06:46,279 --> 00:06:52,840 Speaker 2: Right Rich chat GPT where you go to is now, 133 00:06:53,120 --> 00:06:55,600 Speaker 2: well you may start seeing ads. 134 00:06:55,680 --> 00:06:56,760 Speaker 1: And here is the question. 135 00:06:56,880 --> 00:07:01,200 Speaker 2: Normally, don't they make enough money simply by data mining 136 00:07:01,400 --> 00:07:06,320 Speaker 2: selling uh information about people that come into chat gpt. 137 00:07:07,040 --> 00:07:10,440 Speaker 2: Uh is it ever enough money or does everything have 138 00:07:10,480 --> 00:07:11,280 Speaker 2: to go to ads? 139 00:07:11,320 --> 00:07:11,640 Speaker 1: Also? 140 00:07:13,440 --> 00:07:16,040 Speaker 3: Uh, everything has to go to ads because chatchybt at 141 00:07:16,040 --> 00:07:19,240 Speaker 3: this point is not data mining. They're not selling the 142 00:07:19,280 --> 00:07:23,400 Speaker 3: information they gather so far. They primarily make their money 143 00:07:23,480 --> 00:07:27,200 Speaker 3: right now through their API, which means big companies license 144 00:07:27,360 --> 00:07:31,480 Speaker 3: their their information, you know, and their and their their 145 00:07:31,560 --> 00:07:34,640 Speaker 3: AI in general. And then of course the users that 146 00:07:34,680 --> 00:07:37,720 Speaker 3: pay a lot of people pay big bucks to access chatchybt, 147 00:07:37,920 --> 00:07:40,480 Speaker 3: and so that's been the primary way. But here's the thing. 148 00:07:40,960 --> 00:07:43,920 Speaker 3: They know that this is expensive. This is not a 149 00:07:44,320 --> 00:07:47,000 Speaker 3: I mean, technically open AI I think is still a nonprofit. 150 00:07:47,080 --> 00:07:49,800 Speaker 3: But they're you know, they're in it for the investors, 151 00:07:49,840 --> 00:07:52,360 Speaker 3: which have put a lot of money into open ai. 152 00:07:52,560 --> 00:07:54,760 Speaker 3: So they need to turn a profit, and the way 153 00:07:54,760 --> 00:07:56,800 Speaker 3: to do that is to squeeze the people that are 154 00:07:56,880 --> 00:08:00,280 Speaker 3: using this for free. So if you are on chatchyt 155 00:08:00,480 --> 00:08:02,800 Speaker 3: for free at this point, you may start to see 156 00:08:02,840 --> 00:08:06,720 Speaker 3: ads underneath your I call them search results, but I 157 00:08:06,760 --> 00:08:09,640 Speaker 3: guess it's just your your answers on chat GBT. So 158 00:08:09,680 --> 00:08:12,600 Speaker 3: this is rolling out starting today. If you are on 159 00:08:12,640 --> 00:08:14,760 Speaker 3: a free plan, if you're on the plan where you're 160 00:08:14,760 --> 00:08:17,960 Speaker 3: paying eight dollars a month with which they just introduced, 161 00:08:17,960 --> 00:08:19,760 Speaker 3: you're also going to pay or you're also going to 162 00:08:19,760 --> 00:08:22,240 Speaker 3: see ads. So bottom line, you're going to start to 163 00:08:22,240 --> 00:08:24,280 Speaker 3: see ads. Chattypt is doing it in a way bill 164 00:08:24,320 --> 00:08:26,560 Speaker 3: where they say it's going to be private. They're not 165 00:08:26,640 --> 00:08:29,160 Speaker 3: sharing your data with the advertisers, they're not sharing your 166 00:08:29,240 --> 00:08:31,920 Speaker 3: chats with the advertisers, and they're keeping everything in a 167 00:08:31,960 --> 00:08:34,680 Speaker 3: separate kind of section of the app. But you'll see 168 00:08:34,720 --> 00:08:36,640 Speaker 3: it'll say sponsored. 169 00:08:36,920 --> 00:08:39,720 Speaker 2: At what time or in your opinion, do you think 170 00:08:39,800 --> 00:08:45,040 Speaker 2: that chat gpt is going to not only sell ads, 171 00:08:45,440 --> 00:08:50,000 Speaker 2: have ads, but also sell to the data mining organizations 172 00:08:50,640 --> 00:08:53,040 Speaker 2: and to license itself to the majors. 173 00:08:53,640 --> 00:08:55,040 Speaker 1: I hit all three of them. 174 00:08:55,280 --> 00:08:58,000 Speaker 3: I mean yeah, I mean here, here's the deal. We 175 00:08:58,080 --> 00:09:02,120 Speaker 3: know that people are using these AI chatbots for everything. 176 00:09:02,240 --> 00:09:07,160 Speaker 3: There is a treasure trove of information about trends, what 177 00:09:07,200 --> 00:09:10,040 Speaker 3: people are interested in, what people are looking at, what 178 00:09:10,080 --> 00:09:14,920 Speaker 3: are they researching, and that includes products, services, ailments, whatever 179 00:09:14,960 --> 00:09:17,480 Speaker 3: you can imagine. So the data that they are sitting 180 00:09:17,520 --> 00:09:20,600 Speaker 3: on is huge. It is it is the new kind 181 00:09:20,640 --> 00:09:23,520 Speaker 3: of you know, the new thought system of America. Like 182 00:09:23,559 --> 00:09:26,760 Speaker 3: everything that's that we're thinking is inside CHATGBT. It used 183 00:09:26,760 --> 00:09:28,959 Speaker 3: to be Google, and it still is to a certain extent. 184 00:09:29,000 --> 00:09:32,640 Speaker 3: Obviously people are still using that, but you know, they 185 00:09:32,679 --> 00:09:36,040 Speaker 3: have the ability to monetize that in various ways. I 186 00:09:36,040 --> 00:09:38,160 Speaker 3: think it depends on this company and the way that 187 00:09:38,160 --> 00:09:40,040 Speaker 3: they want to respect the people that are using it 188 00:09:40,840 --> 00:09:43,880 Speaker 3: to decide how do they want to proceed, because it 189 00:09:43,920 --> 00:09:47,200 Speaker 3: only takes a small misstep for them to go down 190 00:09:47,240 --> 00:09:50,040 Speaker 3: the lines of a Facebook or a Meta where people 191 00:09:50,080 --> 00:09:52,400 Speaker 3: don't trust them anymore. So you have to be very, 192 00:09:52,520 --> 00:09:54,800 Speaker 3: very careful. And right now they're still building their business, 193 00:09:55,080 --> 00:09:56,640 Speaker 3: so they're going to tread carefully, I think. 194 00:09:57,280 --> 00:09:57,559 Speaker 1: Okay. 195 00:09:57,600 --> 00:10:01,600 Speaker 2: The last one, Waimo is admitting that humans sometimes take over. 196 00:10:01,600 --> 00:10:03,800 Speaker 2: You go, wait a minute, those Weimo cars, there's nobody 197 00:10:03,800 --> 00:10:04,520 Speaker 2: in him to drive. 198 00:10:04,880 --> 00:10:05,640 Speaker 1: How does that work? 199 00:10:06,840 --> 00:10:10,080 Speaker 3: Okay, this I thought was wild because we know that 200 00:10:10,120 --> 00:10:12,679 Speaker 3: Weaimo says their software, they call it the most experienced 201 00:10:12,720 --> 00:10:15,960 Speaker 3: driver in the world. They've logged many, many millions of 202 00:10:15,960 --> 00:10:20,600 Speaker 3: miles autonomously. But they just admitted in a Senate hearing 203 00:10:21,040 --> 00:10:24,679 Speaker 3: that some of its robotaxis actually phone a friend when 204 00:10:24,720 --> 00:10:27,520 Speaker 3: they need help, and the friend is in the Philippines. 205 00:10:27,840 --> 00:10:30,520 Speaker 3: These are workers that are not necessarily driving the cars, 206 00:10:30,880 --> 00:10:34,319 Speaker 3: but they basically help the cars figure out when they 207 00:10:34,360 --> 00:10:37,360 Speaker 3: run into an odd situation like a construction zone or 208 00:10:37,400 --> 00:10:40,520 Speaker 3: like a traffic pattern, and that's what happens. So the 209 00:10:40,880 --> 00:10:43,800 Speaker 3: operator looked through the car's sensors and video feeds and 210 00:10:44,440 --> 00:10:47,560 Speaker 3: you tell it how to do it. So it's kind 211 00:10:47,559 --> 00:10:50,679 Speaker 3: of interesting because we always thought that Weymo's were fully autonomous. 212 00:10:51,080 --> 00:10:53,719 Speaker 3: Now we're learning through this Senate hearing that they may 213 00:10:53,720 --> 00:10:54,000 Speaker 3: not be. 214 00:10:54,520 --> 00:10:59,559 Speaker 2: Wow and the Philippines do those operators in the Philippines 215 00:10:59,600 --> 00:11:01,240 Speaker 2: sing ariochi while they're doing this. 216 00:11:02,679 --> 00:11:04,959 Speaker 3: I don't know what they're doing. But the reality is 217 00:11:05,080 --> 00:11:09,560 Speaker 3: the senators were wondering about the distance between the car 218 00:11:09,880 --> 00:11:13,560 Speaker 3: and the operator because clearly there's not much latency if 219 00:11:13,600 --> 00:11:17,160 Speaker 3: they can be operating from remote of a distance that long. 220 00:11:17,400 --> 00:11:21,160 Speaker 3: By the way, there is a car service in Las 221 00:11:21,240 --> 00:11:25,719 Speaker 3: Vegas called vey Vay, and what they do is they 222 00:11:25,760 --> 00:11:29,000 Speaker 3: make no bones about it. They're driving their cars remotely. 223 00:11:29,400 --> 00:11:32,080 Speaker 3: And so Bill, instead of getting an uber you would, 224 00:11:32,160 --> 00:11:35,319 Speaker 3: let's say you need a rental car or a ride somewhere. Okay, 225 00:11:35,559 --> 00:11:39,400 Speaker 3: they will drive this car autonomously to your house, pick 226 00:11:39,440 --> 00:11:41,679 Speaker 3: you up, drive you to wherever you need to go, 227 00:11:42,000 --> 00:11:44,080 Speaker 3: and then pick up the next person. And the person 228 00:11:44,120 --> 00:11:46,760 Speaker 3: that's driving this car is remotely driving. So imagine your 229 00:11:46,800 --> 00:11:49,520 Speaker 3: Uber driver is sitting in an office building with a 230 00:11:49,520 --> 00:11:52,960 Speaker 3: bunch of computer monitors and a steering wheel in front 231 00:11:53,000 --> 00:11:53,280 Speaker 3: of them. 232 00:11:53,840 --> 00:11:56,640 Speaker 1: Okay, and that's the company called Oivy. Do I have 233 00:11:56,720 --> 00:11:57,040 Speaker 1: that right? 234 00:11:58,400 --> 00:12:01,359 Speaker 3: I think it's just Vey, but I think fired by 235 00:12:01,720 --> 00:12:04,480 Speaker 3: So I understood you might be saying that when you're 236 00:12:04,480 --> 00:12:05,120 Speaker 3: in the car though. 237 00:12:05,280 --> 00:12:09,600 Speaker 2: Yeah, all right, rich Well we'll talk again next Tuesday. 238 00:12:09,679 --> 00:12:13,320 Speaker 2: This weekend eleven am to two pm rich On Tech, 239 00:12:13,440 --> 00:12:18,800 Speaker 2: the segment KTLA every morning Instagram at rich on Tech website, 240 00:12:18,880 --> 00:12:21,959 Speaker 2: richon Tech dot tv. And we'll catch you next week. 241 00:12:23,240 --> 00:12:23,760 Speaker 3: Thanks Bill. 242 00:12:23,920 --> 00:12:25,160 Speaker 1: All right, wame o. 243 00:12:27,520 --> 00:12:30,480 Speaker 2: Drivers Remote drivers in the Philippines. 244 00:12:31,080 --> 00:12:34,560 Speaker 1: Boy, that's news to me. And I'll bet you that 245 00:12:34,640 --> 00:12:35,360 Speaker 1: they sing. 246 00:12:37,280 --> 00:12:40,760 Speaker 2: Peelings, nothing more than peelings. 247 00:12:42,200 --> 00:12:43,520 Speaker 1: Okay, we're done, guys,