1 00:00:04,440 --> 00:00:12,319 Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Hey there, 2 00:00:12,360 --> 00:00:15,600 Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland. 3 00:00:15,640 --> 00:00:18,959 Speaker 1: I'm an executive producer with iHeart Podcasts, and how the 4 00:00:19,079 --> 00:00:21,840 Speaker 1: tech are you? It's time for us to talk about 5 00:00:21,880 --> 00:00:25,840 Speaker 1: the tech news for the week ending on Friday, April fifth, 6 00:00:26,079 --> 00:00:30,120 Speaker 1: twenty twenty four. Had to think about that for a minute, 7 00:00:30,280 --> 00:00:33,400 Speaker 1: but starting off, Microsoft released a warning that says we 8 00:00:33,440 --> 00:00:36,360 Speaker 1: should all expect China to try and disrupt elections in 9 00:00:36,479 --> 00:00:40,160 Speaker 1: several countries, including the United States, which I guess is news, 10 00:00:40,400 --> 00:00:41,920 Speaker 1: though at this point I think a lot of folks 11 00:00:42,000 --> 00:00:44,000 Speaker 1: just assumed that was going to be on China's to 12 00:00:44,040 --> 00:00:47,680 Speaker 1: do list anyway. Microsoft also warned that North Korea could 13 00:00:47,720 --> 00:00:50,280 Speaker 1: be involved in this sort of effort as well, although 14 00:00:50,280 --> 00:00:52,640 Speaker 1: from what I gather, the two countries would largely be 15 00:00:52,720 --> 00:00:56,840 Speaker 1: working independently toward a similar goal. Microsoft's stated that China 16 00:00:56,840 --> 00:01:00,320 Speaker 1: went the very least lean heavily on AI generated content 17 00:01:00,440 --> 00:01:04,240 Speaker 1: that's intended to shape public opinion to favor political outcomes 18 00:01:04,240 --> 00:01:06,520 Speaker 1: that would align with China's own goals. In fact, the 19 00:01:06,640 --> 00:01:09,800 Speaker 1: country's already been doing this, and Microsoft said that right 20 00:01:09,840 --> 00:01:12,920 Speaker 1: now such content hasn't proven to be really that effective 21 00:01:13,040 --> 00:01:15,840 Speaker 1: in moving the needle of public opinion, but it is 22 00:01:15,880 --> 00:01:19,240 Speaker 1: important to pay attention to it because with every failure 23 00:01:19,319 --> 00:01:21,720 Speaker 1: comes the chance to learn from the stakes and to 24 00:01:21,920 --> 00:01:24,160 Speaker 1: get better. So it could just be a matter of 25 00:01:24,160 --> 00:01:28,000 Speaker 1: time before AI generated propaganda really does help push public 26 00:01:28,040 --> 00:01:32,360 Speaker 1: opinion in a specific direction. Microsoft says that various social 27 00:01:32,400 --> 00:01:35,920 Speaker 1: accounts linked to China have been posting AI generated content 28 00:01:36,040 --> 00:01:39,480 Speaker 1: with a call to action. So essentially, the posts push 29 00:01:39,600 --> 00:01:43,280 Speaker 1: conspiratorial language and then follow that up with what do 30 00:01:43,440 --> 00:01:47,240 Speaker 1: you think? And that call to engagement could both serve 31 00:01:47,319 --> 00:01:50,720 Speaker 1: to elevate the visibility of the post as well as 32 00:01:50,800 --> 00:01:53,560 Speaker 1: just you know, actually ask for feedback to judge how 33 00:01:53,560 --> 00:01:58,680 Speaker 1: well their propaganda is working. Oh Brave new world. Here 34 00:01:58,720 --> 00:02:01,880 Speaker 1: in the United States, the concept of net neutrality has 35 00:02:01,920 --> 00:02:05,680 Speaker 1: had a pretty rocky go of it. The idea is 36 00:02:05,720 --> 00:02:08,160 Speaker 1: a little bit complex, but one way to look at 37 00:02:08,200 --> 00:02:12,400 Speaker 1: it is that all parties involved in facilitating information moving 38 00:02:12,480 --> 00:02:15,920 Speaker 1: across the Internet would allow that data to travel freely 39 00:02:16,120 --> 00:02:19,679 Speaker 1: without interference, without regard of where it came from, where 40 00:02:19,680 --> 00:02:22,600 Speaker 1: it's going to, or what kind of device is accessing it. 41 00:02:22,960 --> 00:02:27,160 Speaker 1: So in a world with net neutrality, you would not 42 00:02:27,280 --> 00:02:30,640 Speaker 1: allow an Internet carrier to throttle some types of data 43 00:02:30,680 --> 00:02:33,200 Speaker 1: while allowing others to go on a fast track. You 44 00:02:33,240 --> 00:02:37,120 Speaker 1: wouldn't leverage your position to favor certain partners or even 45 00:02:37,160 --> 00:02:41,200 Speaker 1: your own services and content over that of your competitors, 46 00:02:41,440 --> 00:02:44,880 Speaker 1: so everyone would have a level playing field. The United 47 00:02:44,919 --> 00:02:49,720 Speaker 1: States Federal Communications Commission attempted to codify net neutrality during 48 00:02:49,720 --> 00:02:53,000 Speaker 1: the Obama administration, and in fact did so briefly, but 49 00:02:53,080 --> 00:02:59,440 Speaker 1: those decisions were overturned by the FCC of the Trump administration. Now, 50 00:03:00,040 --> 00:03:03,680 Speaker 1: during the Biden administration, the FCC plans to vote to 51 00:03:03,720 --> 00:03:07,079 Speaker 1: restore those net neutrality rules, or at least some of them. 52 00:03:07,600 --> 00:03:11,120 Speaker 1: That vote will officially happen on April twenty fifth, and 53 00:03:11,200 --> 00:03:13,960 Speaker 1: tech Dirt points out that the new rules are going 54 00:03:14,000 --> 00:03:16,840 Speaker 1: to have some exceptions and loopholes in them thanks to 55 00:03:16,880 --> 00:03:20,080 Speaker 1: a lot of lobbying, and links to a post by 56 00:03:20,280 --> 00:03:25,079 Speaker 1: Barbara Van Shuick, a law professor at Stanford that explains 57 00:03:25,080 --> 00:03:27,480 Speaker 1: it greater detail the differences of the new set of 58 00:03:27,560 --> 00:03:31,760 Speaker 1: rules compared to the previous attempt to really codify net neutrality. 59 00:03:32,280 --> 00:03:36,040 Speaker 1: So I might do a full episode about this because 60 00:03:36,080 --> 00:03:40,760 Speaker 1: it is a topic that's fairly complicated. In Google News, 61 00:03:40,960 --> 00:03:43,880 Speaker 1: the company has said that it will destroy data records 62 00:03:43,880 --> 00:03:47,080 Speaker 1: that number in the billions with a B and you 63 00:03:47,160 --> 00:03:50,000 Speaker 1: might wonder, well, what do these records involved, And it's 64 00:03:50,080 --> 00:03:53,480 Speaker 1: the kind of sort of information about what people were 65 00:03:53,560 --> 00:03:58,120 Speaker 1: doing when they were browsing the Internet while in incognito mode, 66 00:03:58,600 --> 00:04:01,920 Speaker 1: you know, that mode that at least implies that your 67 00:04:02,080 --> 00:04:05,920 Speaker 1: activities on your browser are you know, protected in private. 68 00:04:06,200 --> 00:04:08,480 Speaker 1: So Google is doing this as part of a settlement 69 00:04:09,040 --> 00:04:12,240 Speaker 1: that still must be approved, and it's for this big 70 00:04:12,240 --> 00:04:16,960 Speaker 1: old lawsuit. And the lawsuit accused Google of implying that 71 00:04:17,000 --> 00:04:20,600 Speaker 1: incognito mode would give Chrome users privacy as they skulked 72 00:04:20,600 --> 00:04:23,080 Speaker 1: around on the web doing whatever it was they were doing. 73 00:04:23,440 --> 00:04:27,400 Speaker 1: But all the while Google was actually tracking data and 74 00:04:27,480 --> 00:04:30,480 Speaker 1: being able to identify the user, meaning that incognito is 75 00:04:30,520 --> 00:04:33,600 Speaker 1: not that incognito. You know, you can't go incognito if 76 00:04:33,640 --> 00:04:36,479 Speaker 1: everybody recognizes you. This is the big complaint I have 77 00:04:36,560 --> 00:04:41,200 Speaker 1: about James Bond films, because he's a spy, but he 78 00:04:41,279 --> 00:04:45,160 Speaker 1: goes around introducing himself as James Bond. But I suppose 79 00:04:45,200 --> 00:04:48,800 Speaker 1: that doesn't really fit in a tech podcast anyway. It's 80 00:04:48,839 --> 00:04:51,200 Speaker 1: really a good reminder that the stuff you do on 81 00:04:51,240 --> 00:04:54,760 Speaker 1: the Internet isn't necessarily as private as you thought it was, 82 00:04:55,360 --> 00:04:58,400 Speaker 1: and that's just something to keep in mind, not to 83 00:04:58,480 --> 00:05:01,919 Speaker 1: prevent you from using the Internet, but being aware of 84 00:05:01,960 --> 00:05:06,200 Speaker 1: it is a good thing. Amazon has booted its cashierless 85 00:05:06,279 --> 00:05:09,479 Speaker 1: grocery store strategy at least a little bit. They have 86 00:05:09,640 --> 00:05:13,159 Speaker 1: opted to go with a different approach for their larger supermarkets. 87 00:05:13,320 --> 00:05:16,120 Speaker 1: So the company introduced this technology a few years ago, 88 00:05:16,240 --> 00:05:19,279 Speaker 1: and the idea, in case you're not familiar with it, 89 00:05:19,320 --> 00:05:22,560 Speaker 1: is that you would go into an Amazon store, like 90 00:05:22,600 --> 00:05:26,600 Speaker 1: an Amazon Ghost store or an Amazon Fresh grocery store. 91 00:05:26,960 --> 00:05:29,520 Speaker 1: Then you would do your normal shopping and you would 92 00:05:29,520 --> 00:05:31,839 Speaker 1: fill up your shopping cart, and then you could just 93 00:05:32,000 --> 00:05:35,120 Speaker 1: leave the store and Amazon would automatically bill you for 94 00:05:35,240 --> 00:05:37,719 Speaker 1: the stuff that was in your cart. But the company 95 00:05:37,760 --> 00:05:41,520 Speaker 1: says that customers didn't really gel with this technology, particularly 96 00:05:41,600 --> 00:05:45,799 Speaker 1: for like grocery store big shopping days, because that involved 97 00:05:45,839 --> 00:05:48,880 Speaker 1: not just you know, like prepackaged foods, that's one thing, 98 00:05:49,120 --> 00:05:52,200 Speaker 1: but also stuff like produce, where typically you would need 99 00:05:52,200 --> 00:05:54,760 Speaker 1: to weigh the produce in order to get a price 100 00:05:54,800 --> 00:05:57,160 Speaker 1: on what it was you were buying. And the company 101 00:05:57,200 --> 00:05:59,640 Speaker 1: says that the technology might be a better fit for 102 00:05:59,720 --> 00:06:03,640 Speaker 1: small stores rather than a full supermarket. CNN states that 103 00:06:03,839 --> 00:06:07,520 Speaker 1: Amazon is looking at some alternatives for the larger Amazon 104 00:06:07,560 --> 00:06:09,920 Speaker 1: Fresh stores in the United States, such as using the 105 00:06:10,040 --> 00:06:12,960 Speaker 1: dash cart. So this is a shopping cart that customers 106 00:06:12,960 --> 00:06:16,120 Speaker 1: can use to scan items that they are purchasing, so 107 00:06:16,120 --> 00:06:18,479 Speaker 1: they can purchase the items by scanning them and putting 108 00:06:18,520 --> 00:06:21,080 Speaker 1: them in their shopping cart. And they can also interact 109 00:06:21,120 --> 00:06:24,520 Speaker 1: with other elements of their account, like they can have 110 00:06:24,760 --> 00:06:27,520 Speaker 1: their shopping list active with their cart so that the 111 00:06:27,680 --> 00:06:30,000 Speaker 1: cart is guiding them to the items that are on 112 00:06:30,080 --> 00:06:33,640 Speaker 1: their list. They can have alerts as to sales that 113 00:06:33,680 --> 00:06:36,880 Speaker 1: are going on, that kind of thing. On a related note, 114 00:06:37,040 --> 00:06:40,640 Speaker 1: The Information published an article that says the automated technology 115 00:06:40,760 --> 00:06:44,559 Speaker 1: wasn't as automated as Amazon implied. So, according to the piece, 116 00:06:44,800 --> 00:06:48,440 Speaker 1: around one thousand workers in India reviewed up to seventy 117 00:06:48,480 --> 00:06:51,640 Speaker 1: percent of the purchases made through the just walk out 118 00:06:51,720 --> 00:06:54,200 Speaker 1: technology that's what was called and this was back in 119 00:06:54,240 --> 00:06:58,839 Speaker 1: twenty twenty two. So when seventy percent of your transactions 120 00:06:58,880 --> 00:07:02,200 Speaker 1: are actually going under human review to make sure that 121 00:07:02,440 --> 00:07:06,039 Speaker 1: you know you're getting charged for the right stuff, then 122 00:07:06,120 --> 00:07:09,280 Speaker 1: it's not really just walk out, like, at least not 123 00:07:09,360 --> 00:07:13,920 Speaker 1: on Amazon side. Now, Amazon has disputed this. They said that no, no, no, 124 00:07:14,240 --> 00:07:18,560 Speaker 1: that seventy percent is not reflective of reality, that it 125 00:07:18,640 --> 00:07:24,000 Speaker 1: was a much lower percentage of transactions that required human review, 126 00:07:24,320 --> 00:07:26,720 Speaker 1: and in fact, the staff was really there to help 127 00:07:26,800 --> 00:07:29,680 Speaker 1: train the AI to get better, so it's like, you know, 128 00:07:30,120 --> 00:07:34,720 Speaker 1: guided training. According to Amazon, that's a pretty big discrepancy 129 00:07:35,040 --> 00:07:38,440 Speaker 1: between seventy percent of all transactions and just a few. 130 00:07:39,040 --> 00:07:41,680 Speaker 1: I don't know where the truth is, but it is 131 00:07:41,920 --> 00:07:44,520 Speaker 1: true that that technology is no longer going to be 132 00:07:44,600 --> 00:07:47,400 Speaker 1: used in the fresh stores in the United States. It 133 00:07:47,520 --> 00:07:49,560 Speaker 1: will still be used in some of the smaller stores. 134 00:07:49,640 --> 00:07:53,240 Speaker 1: It has also kind of coincided with some other companies 135 00:07:53,280 --> 00:07:58,040 Speaker 1: saying that maybe going the cashierless way isn't the best 136 00:07:58,040 --> 00:08:01,200 Speaker 1: approach because people make mistakes or some people are just 137 00:08:01,200 --> 00:08:05,000 Speaker 1: plain dishonest, and that there's been a lot of loss associated, 138 00:08:05,080 --> 00:08:08,440 Speaker 1: perhaps more loss than what you would see if you, 139 00:08:08,640 --> 00:08:11,400 Speaker 1: I don't know, hired people to do the job. So 140 00:08:11,960 --> 00:08:15,480 Speaker 1: just a fun little thing about how technology doesn't always 141 00:08:15,640 --> 00:08:19,440 Speaker 1: replace people at a level that makes sense. A couple 142 00:08:19,440 --> 00:08:22,280 Speaker 1: of companies had a really rough day this week on 143 00:08:22,360 --> 00:08:25,840 Speaker 1: April third, on Wednesday, maybe it was delayed April Fool's 144 00:08:25,880 --> 00:08:29,400 Speaker 1: Prank or something. But Meta's WhatsApp service was unavailable for 145 00:08:29,520 --> 00:08:32,880 Speaker 1: many users this past Wednesday. But by many, we have 146 00:08:32,960 --> 00:08:36,800 Speaker 1: to really contextualize that we're talking about in the tens 147 00:08:36,840 --> 00:08:39,720 Speaker 1: of thousands. Now, granted that's a lot of people. Tens 148 00:08:39,720 --> 00:08:43,440 Speaker 1: of thousands of people is a lot, but WhatsApp boasts 149 00:08:43,520 --> 00:08:47,720 Speaker 1: around two billion users, so in the grand scheme of things, 150 00:08:48,000 --> 00:08:51,520 Speaker 1: it was hardly even a blip. Now, Meta resolved the issue, 151 00:08:51,600 --> 00:08:54,080 Speaker 1: and I have no clue what it was that went wrong. 152 00:08:54,160 --> 00:08:58,480 Speaker 1: The company didn't really say. And meanwhile, Apple service is 153 00:08:58,520 --> 00:09:02,480 Speaker 1: on that same day, April, including its streaming platforms, so 154 00:09:02,800 --> 00:09:07,520 Speaker 1: like Apple TV and Apple Music, its podcast app was affected. 155 00:09:07,600 --> 00:09:11,319 Speaker 1: The App store itself was affected by another outage. Now, 156 00:09:11,360 --> 00:09:13,920 Speaker 1: this issue lasted a bit more than an hour for 157 00:09:14,080 --> 00:09:17,600 Speaker 1: users in countries like the United States, the United Kingdom, India, 158 00:09:17,640 --> 00:09:20,640 Speaker 1: and China, and whatever the cause of that issue, Apple 159 00:09:20,840 --> 00:09:24,040 Speaker 1: was able to restore services just a little bit later. 160 00:09:24,160 --> 00:09:28,280 Speaker 1: So again, maybe just a delayed prank, Maybe it was Grimlins, 161 00:09:29,120 --> 00:09:31,520 Speaker 1: Maybe it was just two similar events that just happened 162 00:09:31,520 --> 00:09:34,400 Speaker 1: to happen at the same time by coincidence. It's probably 163 00:09:34,600 --> 00:09:38,199 Speaker 1: that last one. Okay, I got a few more news 164 00:09:38,240 --> 00:09:40,960 Speaker 1: stories for y'all. But before we get to that, let's 165 00:09:41,120 --> 00:09:55,920 Speaker 1: take a quick break so forward here in the United States, 166 00:09:56,000 --> 00:09:58,560 Speaker 1: is the most recent automaker to announce that it is 167 00:09:58,800 --> 00:10:03,240 Speaker 1: shifting its stra toward electric vehicles. It is pushing back 168 00:10:03,480 --> 00:10:06,080 Speaker 1: when it's going to produce all electric models of cars. 169 00:10:06,440 --> 00:10:08,880 Speaker 1: The plan was that twenty twenty five was going to 170 00:10:08,880 --> 00:10:11,200 Speaker 1: be the big year where Ford was going to bring 171 00:10:11,240 --> 00:10:14,160 Speaker 1: out all these all electric vehicles, you know, like cars, trucks, 172 00:10:14,160 --> 00:10:17,880 Speaker 1: and SUVs. And instead they're going to focus on hybrids 173 00:10:17,880 --> 00:10:20,480 Speaker 1: at least in the short term and push back the 174 00:10:20,800 --> 00:10:24,439 Speaker 1: electric vehicle approach for a few more years. And several 175 00:10:24,520 --> 00:10:27,720 Speaker 1: other car manufacturers have made similar decisions in the not 176 00:10:27,800 --> 00:10:33,400 Speaker 1: too distant past, and it's kind of created this slow 177 00:10:33,480 --> 00:10:37,040 Speaker 1: down in the conversion to electric vehicles. Now, the companies 178 00:10:37,040 --> 00:10:41,679 Speaker 1: have cited a general slow adoption rate among consumers for evs, 179 00:10:41,720 --> 00:10:44,600 Speaker 1: so they're saying consumers don't want electric vehicles, or at 180 00:10:44,679 --> 00:10:46,959 Speaker 1: least not enough of them. There's just been a very 181 00:10:46,960 --> 00:10:50,680 Speaker 1: slow uptake on electric vehicles. I think that part of 182 00:10:50,720 --> 00:10:53,560 Speaker 1: that is probably price. I think a big part of 183 00:10:53,600 --> 00:10:56,880 Speaker 1: that might be recent economic issues that have played a 184 00:10:56,960 --> 00:10:59,640 Speaker 1: huge part in the decision making process of buying a 185 00:10:59,679 --> 00:11:02,320 Speaker 1: new car, are you know, we were dealing with really 186 00:11:02,360 --> 00:11:05,559 Speaker 1: high inflation rates that made stuff like loans and financing 187 00:11:05,679 --> 00:11:08,199 Speaker 1: kind of scary, Like when you're paying more in your 188 00:11:08,240 --> 00:11:10,680 Speaker 1: interest than you are for the vehicle, that's an issue, right. 189 00:11:10,920 --> 00:11:14,200 Speaker 1: And then there was also inflation and that ended up 190 00:11:14,240 --> 00:11:17,200 Speaker 1: creating a real sticker shock situation too. You'd go in 191 00:11:17,280 --> 00:11:20,040 Speaker 1: and the car at the beginning would just be priced 192 00:11:20,080 --> 00:11:23,040 Speaker 1: at a really high level, and you know, that's hard 193 00:11:23,240 --> 00:11:27,000 Speaker 1: to deal with. So I am not fully convinced that 194 00:11:27,040 --> 00:11:30,880 Speaker 1: the general public is just reluctant to adopt evs. I 195 00:11:30,880 --> 00:11:34,520 Speaker 1: think it's more likely a more complicated situation that a 196 00:11:34,559 --> 00:11:37,840 Speaker 1: lot of the public can't afford a new car in general, 197 00:11:37,880 --> 00:11:40,480 Speaker 1: but specifically an EV which still they tend to be 198 00:11:40,520 --> 00:11:44,320 Speaker 1: pretty expensive. However, I'm no expert. I cannot pretend to 199 00:11:44,400 --> 00:11:47,719 Speaker 1: say like I have the insight here and it's one 200 00:11:47,800 --> 00:11:51,200 Speaker 1: hundred percent accurate. This is just sort of my perception, 201 00:11:51,600 --> 00:11:54,319 Speaker 1: and it could very well be that I'm totally off base, 202 00:11:54,400 --> 00:11:58,480 Speaker 1: And surely these car manufacturers have very intelligent people working 203 00:11:58,520 --> 00:12:01,439 Speaker 1: on these things, so so I don't know. Maybe it 204 00:12:01,520 --> 00:12:04,280 Speaker 1: is that the public in general is still a little 205 00:12:04,960 --> 00:12:07,880 Speaker 1: wary about evs. I can understand why. I mean, there's 206 00:12:07,880 --> 00:12:10,760 Speaker 1: this perception that you know, you're going to have a 207 00:12:10,800 --> 00:12:12,880 Speaker 1: limited range as far as you can drive, and that 208 00:12:12,960 --> 00:12:15,480 Speaker 1: kind of thing. I don't think that this means that 209 00:12:15,520 --> 00:12:18,320 Speaker 1: the entire plan to shift toward electric vehicles has taken 210 00:12:18,360 --> 00:12:20,920 Speaker 1: a totally wrong turn. This just might be one of 211 00:12:20,960 --> 00:12:24,280 Speaker 1: those cases where you know, you're on a car trip 212 00:12:24,320 --> 00:12:26,600 Speaker 1: and your dad says he knows a short cut, and 213 00:12:26,640 --> 00:12:28,960 Speaker 1: then next thing, you know, here four hours late to 214 00:12:29,000 --> 00:12:33,240 Speaker 1: Grandma's house because the shortcut wasn't that effective. Maybe that's 215 00:12:33,240 --> 00:12:38,880 Speaker 1: what's happening here. Metaphorically, in what was a really expected announcement, 216 00:12:38,920 --> 00:12:42,960 Speaker 1: this didn't come as a surprise Disney CEO Bob Iger, who, 217 00:12:42,960 --> 00:12:45,800 Speaker 1: by the way, recently posted a victory against a proxy 218 00:12:45,880 --> 00:12:49,600 Speaker 1: battle among activist shareholders. He said that the company is 219 00:12:49,640 --> 00:12:52,400 Speaker 1: going to start to crack down on password sharing among 220 00:12:52,480 --> 00:12:55,800 Speaker 1: Disney Plus customers starting this June. The rules have already 221 00:12:55,840 --> 00:12:58,520 Speaker 1: been in place. It's not like they're putting in new rules. 222 00:12:58,559 --> 00:13:02,319 Speaker 1: They're just really kind of being more proactive about it 223 00:13:02,800 --> 00:13:05,520 Speaker 1: later this summer. And of course we've seen lots of 224 00:13:05,600 --> 00:13:09,440 Speaker 1: other streaming services approach the same challenge, right because it 225 00:13:09,480 --> 00:13:13,040 Speaker 1: turns out that creating a profitable streaming service that can 226 00:13:13,120 --> 00:13:17,280 Speaker 1: sustain efforts to produce original content is tricky. Right, You've 227 00:13:17,280 --> 00:13:21,359 Speaker 1: just got subscribers coming in. You could base your performance 228 00:13:21,400 --> 00:13:24,280 Speaker 1: on growth, but eventually you're going to max out that growth. 229 00:13:24,280 --> 00:13:27,680 Speaker 1: You're gonna plateau. So how do you make enough money 230 00:13:27,920 --> 00:13:30,640 Speaker 1: where you can continue to create the content that people 231 00:13:30,720 --> 00:13:34,680 Speaker 1: want and still make a profit. So Netflix famously pushed 232 00:13:34,720 --> 00:13:38,000 Speaker 1: back against password sharing not too long ago and saw 233 00:13:38,040 --> 00:13:40,640 Speaker 1: some positive results in fact, despite the fact that a 234 00:13:40,640 --> 00:13:44,080 Speaker 1: lot of people complained about the whole practice. Iiger says 235 00:13:44,120 --> 00:13:46,080 Speaker 1: that one part of the plan is to create a 236 00:13:46,200 --> 00:13:49,760 Speaker 1: paid sharing option. So essentially, customers who want to share 237 00:13:49,800 --> 00:13:53,439 Speaker 1: a password with another household will get a little alert 238 00:13:53,480 --> 00:13:56,920 Speaker 1: popping up, and there will be a subscription tier priced 239 00:13:57,000 --> 00:13:59,200 Speaker 1: exactly for that kind of thing. So it costs more 240 00:13:59,240 --> 00:14:03,760 Speaker 1: than just your typical subscription for that level because it'll 241 00:14:03,760 --> 00:14:06,880 Speaker 1: be a shared level. Otherwise, Disney expects you to keep 242 00:14:06,880 --> 00:14:09,280 Speaker 1: your own password in your own grubby little hands and 243 00:14:09,360 --> 00:14:13,560 Speaker 1: let other households go and get their own passwords. So technically, Disney, 244 00:14:13,840 --> 00:14:15,840 Speaker 1: like I said, has had these rules in place for 245 00:14:15,880 --> 00:14:18,240 Speaker 1: a while now. But in June, you know, people that 246 00:14:18,320 --> 00:14:22,000 Speaker 1: Disney suspects are actually using a shared password will get 247 00:14:22,000 --> 00:14:24,320 Speaker 1: a little pop up message suggesting that, you know, they 248 00:14:24,360 --> 00:14:27,200 Speaker 1: sign up for their own subscription, or maybe Mickey Mouse 249 00:14:27,240 --> 00:14:29,880 Speaker 1: will come on over to their house and bust their kneecaps. 250 00:14:30,400 --> 00:14:33,240 Speaker 1: Not literally, I'm paraphrasing. Disney did not actually say that. 251 00:14:33,280 --> 00:14:38,800 Speaker 1: That's me taking some poetic license. The French Alternative Energies 252 00:14:38,840 --> 00:14:43,840 Speaker 1: and Atomic Energy Commission has produced the Azult MRI machine 253 00:14:44,320 --> 00:14:47,280 Speaker 1: or izult. I don't know how to pronounce it. I 254 00:14:47,320 --> 00:14:50,480 Speaker 1: don't I don't speak French. This MRI machine is a 255 00:14:50,520 --> 00:14:55,000 Speaker 1: real whopper, so your typical hospital MRI machine, the magnetic 256 00:14:55,120 --> 00:14:57,960 Speaker 1: resonance imaging. It's able to create a magnetic field that 257 00:14:58,040 --> 00:14:59,840 Speaker 1: has a strength of between one and a half to 258 00:15:00,040 --> 00:15:02,640 Speaker 1: three teslas. In this case, we're not talking about the 259 00:15:02,640 --> 00:15:05,960 Speaker 1: electric vehicle. We're talking about unit of measurement, but the 260 00:15:05,960 --> 00:15:08,240 Speaker 1: one that I'm talking about here, the new one, which 261 00:15:08,240 --> 00:15:10,240 Speaker 1: has been in practice for a while but has just 262 00:15:10,400 --> 00:15:14,080 Speaker 1: recently been used on human subjects. This sucker bumps up 263 00:15:14,160 --> 00:15:17,960 Speaker 1: the power of that magnetic field to eleven point seven teslas, 264 00:15:18,000 --> 00:15:20,920 Speaker 1: so significantly more powerful than what you're going to find 265 00:15:20,920 --> 00:15:24,360 Speaker 1: in your typical hospital and this isn't just like a 266 00:15:24,400 --> 00:15:28,280 Speaker 1: home improvement moment of more power. The benefit of such 267 00:15:28,320 --> 00:15:30,560 Speaker 1: a machine is that it can produce images with a 268 00:15:30,680 --> 00:15:33,800 Speaker 1: much higher resolution in a fraction of the time it 269 00:15:33,800 --> 00:15:36,480 Speaker 1: would take your standard machine. Like you might have to 270 00:15:36,840 --> 00:15:40,840 Speaker 1: lie motionless in a device for two hours to get 271 00:15:40,840 --> 00:15:43,440 Speaker 1: the same sort of image that this thing can produce 272 00:15:43,560 --> 00:15:45,800 Speaker 1: in just four minutes. And since you have to stay 273 00:15:45,880 --> 00:15:50,040 Speaker 1: perfectly still during an MRI scan, four minutes is a 274 00:15:50,120 --> 00:15:55,360 Speaker 1: much less taxing request than two hours. Now from what 275 00:15:55,440 --> 00:15:58,120 Speaker 1: I understand, the new MRI machine also has a larger 276 00:15:58,200 --> 00:16:01,600 Speaker 1: opening that the patient's would go into. That means it 277 00:16:01,600 --> 00:16:03,880 Speaker 1: should be a less daunting experience for those who have, 278 00:16:03,960 --> 00:16:07,760 Speaker 1: you know, kind of claustrophobic issues. To operate the machines, 279 00:16:07,960 --> 00:16:10,800 Speaker 1: engineers actually have to use liquid helium to cool some 280 00:16:10,840 --> 00:16:14,640 Speaker 1: of the components down so that they reach superconductor status. 281 00:16:15,040 --> 00:16:17,840 Speaker 1: And when you're talking about a machine that's as large 282 00:16:18,160 --> 00:16:22,960 Speaker 1: and complicated and challenging to operate as this is, it 283 00:16:23,000 --> 00:16:26,920 Speaker 1: means it's not really likely to replace the mr eyemachines 284 00:16:26,960 --> 00:16:29,640 Speaker 1: that are currently around the world, but this could be 285 00:16:29,720 --> 00:16:33,240 Speaker 1: really handy for researchers, you know, scientists and doctors, who 286 00:16:33,320 --> 00:16:35,360 Speaker 1: want to use it when they want to look into 287 00:16:35,800 --> 00:16:39,520 Speaker 1: different brain conditions and diseases in order to learn more 288 00:16:39,560 --> 00:16:44,520 Speaker 1: about how they advance and hopefully help inspire new treatments 289 00:16:44,560 --> 00:16:48,200 Speaker 1: and cures, which is super cool. Finally, I've got a 290 00:16:48,240 --> 00:16:51,280 Speaker 1: couple of article recommendations for you all this week. One 291 00:16:51,400 --> 00:16:53,480 Speaker 1: is a piece in The New York Times by Kevin 292 00:16:53,520 --> 00:16:57,720 Speaker 1: Bruce titled did One Guy Just Stop a Huge cyber Attack? 293 00:16:58,200 --> 00:17:01,040 Speaker 1: It tells the story of a German born programmer named 294 00:17:01,080 --> 00:17:05,600 Speaker 1: Andres Freund who spotted a back door in some software 295 00:17:05,640 --> 00:17:07,960 Speaker 1: and through his actions, was able to address it before 296 00:17:08,040 --> 00:17:11,760 Speaker 1: nefarious hackers could make use of that access to wreak havoc. 297 00:17:12,040 --> 00:17:14,400 Speaker 1: So that's a good piece to read. I also recommend 298 00:17:14,480 --> 00:17:18,560 Speaker 1: a piece in Fortune by Sage Lazaro titled Musicians are 299 00:17:18,680 --> 00:17:22,520 Speaker 1: up in Arms about Generative AI and stability. AI's new 300 00:17:22,600 --> 00:17:26,280 Speaker 1: music generators show why they are right to be. Both 301 00:17:26,280 --> 00:17:30,080 Speaker 1: of these stories touch on things that are ongoing conversations 302 00:17:30,119 --> 00:17:33,399 Speaker 1: in tech. You know, cybersecurity is always part of the conversation, 303 00:17:33,760 --> 00:17:38,840 Speaker 1: and then this concept of how AI could threaten various occupations, 304 00:17:39,200 --> 00:17:41,720 Speaker 1: you know, and art, that sort of thing, how its 305 00:17:41,760 --> 00:17:45,040 Speaker 1: impact on art could be really negative I'm sure we're 306 00:17:45,040 --> 00:17:48,240 Speaker 1: going to have lots more conversations about that, because not 307 00:17:48,359 --> 00:17:50,639 Speaker 1: a day goes by that I don't see another article 308 00:17:50,760 --> 00:17:54,280 Speaker 1: about how AI is going to impact the job market. 309 00:17:54,560 --> 00:17:57,479 Speaker 1: Then it's concerning in a lot of ways. I think 310 00:17:57,520 --> 00:18:01,199 Speaker 1: a lot of companies could potentially make bad decisions with 311 00:18:01,320 --> 00:18:04,880 Speaker 1: AI and then learn the hard way that those bad 312 00:18:04,920 --> 00:18:08,280 Speaker 1: decisions were bad, and they can then get back on track. 313 00:18:08,359 --> 00:18:10,119 Speaker 1: But it would be really nice if we could just 314 00:18:10,240 --> 00:18:13,879 Speaker 1: like avoid the pitfall stage and just kind of sidestep 315 00:18:13,960 --> 00:18:19,119 Speaker 1: around the issue. But I don't know how realistic that is. However, 316 00:18:19,960 --> 00:18:22,879 Speaker 1: I hope all of you out there listening are well, 317 00:18:23,440 --> 00:18:32,800 Speaker 1: and I will talk to you again really soon. Tech 318 00:18:32,880 --> 00:18:37,280 Speaker 1: Stuff is an iHeartRadio production. For more podcasts from iHeartRadio, 319 00:18:37,600 --> 00:18:41,320 Speaker 1: visit the iHeartRadio app, Apple Podcasts, or wherever you listen 320 00:18:41,359 --> 00:18:46,000 Speaker 1: to your favorite shows.