1
00:00:04,400 --> 00:00:07,800
Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.

2
00:00:12,119 --> 00:00:15,160
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,

3
00:00:15,400 --> 00:00:18,520
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio

4
00:00:18,680 --> 00:00:21,279
Speaker 1: and I love all things tech. And this is the

5
00:00:21,320 --> 00:00:27,440
Speaker 1: tech news for Tuesday, July twenty one. And uh, there's

6
00:00:27,520 --> 00:00:30,360
Speaker 1: some some rough stuff in here. In fact, let's start

7
00:00:30,400 --> 00:00:34,040
Speaker 1: with some more bad news for software company Solar Winds.

8
00:00:34,680 --> 00:00:38,160
Speaker 1: You probably remember that late last year we had news

9
00:00:38,200 --> 00:00:42,920
Speaker 1: break that hackers had infiltrated solar Winds products and managed

10
00:00:42,960 --> 00:00:46,720
Speaker 1: to create a supply chain attack that affected thousands of

11
00:00:46,760 --> 00:00:50,360
Speaker 1: computer systems, though it appears the hackers really focused on

12
00:00:50,400 --> 00:00:54,080
Speaker 1: a much smaller number of very high profile targets, including

13
00:00:54,280 --> 00:00:58,360
Speaker 1: US Department of Defense systems, and that the hackers appeared

14
00:00:58,440 --> 00:01:02,080
Speaker 1: to be operating out of Russia. Well Over this past weekend,

15
00:01:02,360 --> 00:01:06,560
Speaker 1: Solar Winds announced that hackers were apparently able to exploit

16
00:01:06,720 --> 00:01:12,680
Speaker 1: previously unknown flaws in two of solar Winds products, and

17
00:01:12,760 --> 00:01:16,480
Speaker 1: that these flaws are completely unrelated to the attacks from

18
00:01:16,560 --> 00:01:20,800
Speaker 1: last year. So these would be called zero day vulnerabilities,

19
00:01:20,920 --> 00:01:24,600
Speaker 1: meaning that no one was aware that these things existed

20
00:01:25,080 --> 00:01:28,880
Speaker 1: when the products went live. This vulnerability is in the

21
00:01:28,920 --> 00:01:33,520
Speaker 1: company's Serve You that's s E r V DASH, the

22
00:01:33,600 --> 00:01:39,679
Speaker 1: letter You line of software products. Microsoft researchers apparently found

23
00:01:39,720 --> 00:01:43,280
Speaker 1: the bug, but not before hackers had already learned of

24
00:01:43,319 --> 00:01:48,000
Speaker 1: it themselves. As of this recording, that's pretty much all

25
00:01:48,040 --> 00:01:51,000
Speaker 1: the information I have on this. Solar Winds stated that

26
00:01:51,040 --> 00:01:54,280
Speaker 1: the company is quote unaware of the identity of the

27
00:01:54,320 --> 00:01:58,400
Speaker 1: potentially affected customers end quote, which is not a great

28
00:01:58,400 --> 00:02:03,200
Speaker 1: start either. Microsoft oft found evidence of quote limited targeted

29
00:02:03,320 --> 00:02:07,840
Speaker 1: customer impact end quote, and according to Ours Technica, the

30
00:02:07,920 --> 00:02:12,359
Speaker 1: vulnerability would allow hackers to gain privileged access after exploiting

31
00:02:12,400 --> 00:02:16,680
Speaker 1: machines that were running Serve You Managed File Transfer and

32
00:02:17,000 --> 00:02:22,880
Speaker 1: or Serve You Secure FTP. With this vulnerability, at that point,

33
00:02:22,919 --> 00:02:26,040
Speaker 1: the hackers would be able to access files on the

34
00:02:26,080 --> 00:02:29,160
Speaker 1: infected system. They might be able to delete data, They

35
00:02:29,160 --> 00:02:32,799
Speaker 1: could install new programs. They can essentially perform the sort

36
00:02:32,840 --> 00:02:36,760
Speaker 1: of tasks that any administrator level account could perform on

37
00:02:36,800 --> 00:02:40,320
Speaker 1: the system. Solar Winds has already issued a quick patch

38
00:02:40,440 --> 00:02:43,920
Speaker 1: to UH to be a temporary fix on this, while

39
00:02:43,919 --> 00:02:47,959
Speaker 1: working on a more permanent solution. On a slightly less

40
00:02:48,040 --> 00:02:51,760
Speaker 1: dramatic note, Twitter recently admitted that the company had mistakenly

41
00:02:51,919 --> 00:02:56,320
Speaker 1: verified a quote small number end quote of fake accounts

42
00:02:56,639 --> 00:03:01,280
Speaker 1: shortly after the company reinstated its verification program. This is

43
00:03:01,280 --> 00:03:04,960
Speaker 1: all according to The Daily Dot, a data scientist with

44
00:03:05,040 --> 00:03:10,480
Speaker 1: the truly amazing name Conspirator No. Tenno found six accounts

45
00:03:10,760 --> 00:03:15,040
Speaker 1: with that verified check mark next to them. And someone

46
00:03:15,160 --> 00:03:18,720
Speaker 1: created those six accounts back on June six, so they're

47
00:03:18,919 --> 00:03:22,960
Speaker 1: pretty darn recent. And while all six were verified, none

48
00:03:23,080 --> 00:03:25,840
Speaker 1: of them had posted so much as a single tweet,

49
00:03:26,120 --> 00:03:30,720
Speaker 1: and two of them were apparently using stock photographs for

50
00:03:30,760 --> 00:03:34,520
Speaker 1: their profile pictures. Twitter responded by copying up to the

51
00:03:34,520 --> 00:03:39,200
Speaker 1: fact that somehow the verification applications for a small number

52
00:03:39,320 --> 00:03:42,640
Speaker 1: of fake accounts had received approval, and the company has

53
00:03:42,680 --> 00:03:46,800
Speaker 1: since banned five of those six accounts. The sixth apparently

54
00:03:47,400 --> 00:03:52,440
Speaker 1: uh took itself down. Nortenno also pointed out that these

55
00:03:52,480 --> 00:03:55,600
Speaker 1: six accounts had a few suspicious followers in common across them,

56
00:03:55,600 --> 00:03:58,640
Speaker 1: to the tune of nearly one thousand accounts, and he

57
00:03:58,720 --> 00:04:01,040
Speaker 1: says that it looks as though these were all part

58
00:04:01,160 --> 00:04:04,320
Speaker 1: of a larger bot net that includes at least one thousand,

59
00:04:04,360 --> 00:04:08,120
Speaker 1: two hundred twelve accounts twelve twelve. I don't know if

60
00:04:08,120 --> 00:04:10,520
Speaker 1: that there's any significance to that. Probably not. I'm sure

61
00:04:10,560 --> 00:04:14,080
Speaker 1: it's just a weird fact that it's a repeating number.

62
00:04:14,360 --> 00:04:19,039
Speaker 1: Twitter's verification process is meant to allow notable people that's

63
00:04:19,160 --> 00:04:23,599
Speaker 1: at least notable in Twitter's estimation, to authenticate that a

64
00:04:23,640 --> 00:04:27,720
Speaker 1: Twitter feed that purporting to belong to them does in

65
00:04:27,760 --> 00:04:31,640
Speaker 1: fact belong to them. That way, you're you know, busy

66
00:04:31,720 --> 00:04:33,880
Speaker 1: tweeting at Neil Gaman, you can be certain that it's

67
00:04:33,880 --> 00:04:37,680
Speaker 1: the real Neil Gaiman who's seeing your messages. I mean, heck,

68
00:04:38,640 --> 00:04:40,960
Speaker 1: I actually have a blue check mark. I have a

69
00:04:41,080 --> 00:04:44,480
Speaker 1: verified Twitter account, So clearly that whole notability thing is

70
00:04:44,520 --> 00:04:48,479
Speaker 1: a pretty you know, Lucy goosey definition. Now, for the record,

71
00:04:48,520 --> 00:04:51,520
Speaker 1: I applied a few years ago when we first launched

72
00:04:51,560 --> 00:04:55,280
Speaker 1: the Forward Thinking video series, so it was for work purposes,

73
00:04:55,600 --> 00:04:57,479
Speaker 1: and the check mark has just kind of stuck with

74
00:04:57,520 --> 00:05:00,960
Speaker 1: me ever since. Not that I'm complaining about this now. Obviously,

75
00:05:00,960 --> 00:05:04,719
Speaker 1: the fake accounts getting verified, that raises questions as to

76
00:05:05,400 --> 00:05:07,560
Speaker 1: how did they do that, How did they sail through

77
00:05:07,600 --> 00:05:11,240
Speaker 1: the verification process in the first place, particularly when there

78
00:05:11,279 --> 00:05:14,960
Speaker 1: are actual, real life notable people out there who never

79
00:05:15,040 --> 00:05:18,640
Speaker 1: received a verification from Twitter. We don't have the answers

80
00:05:18,680 --> 00:05:23,160
Speaker 1: to that. Down in Cuba, we're seeing a pretty familiar

81
00:05:23,200 --> 00:05:26,680
Speaker 1: playbook being followed by the Cuban government there in response

82
00:05:26,760 --> 00:05:31,320
Speaker 1: to growing protests as citizens voice their anger and displeasure

83
00:05:31,360 --> 00:05:35,200
Speaker 1: regarding some major issues in the country like food and

84
00:05:35,279 --> 00:05:38,960
Speaker 1: medical shortages. Cuba is in the midst of a severe

85
00:05:39,120 --> 00:05:44,400
Speaker 1: economic recession, which was exacerbated by COVID nineteen and the

86
00:05:44,440 --> 00:05:49,679
Speaker 1: fact that the entire tourist industry was effectively shut down

87
00:05:49,720 --> 00:05:52,960
Speaker 1: for a year. Citizens have taken to the streets to

88
00:05:53,040 --> 00:05:56,719
Speaker 1: protest the government's response to this and issues with food

89
00:05:56,720 --> 00:05:59,920
Speaker 1: shortages and the like, and the government's response, in part

90
00:06:00,279 --> 00:06:03,039
Speaker 1: has been to shut down internet access, at least that

91
00:06:03,080 --> 00:06:06,600
Speaker 1: appears to be the case, and thus citizens have seen

92
00:06:06,640 --> 00:06:10,200
Speaker 1: their ability to communicate and organize with one another online

93
00:06:10,240 --> 00:06:13,719
Speaker 1: cut off. Now in some areas, such as Havana, where

94
00:06:13,760 --> 00:06:17,880
Speaker 1: the protests are particularly you know, large, the internet outages

95
00:06:17,920 --> 00:06:21,600
Speaker 1: were more severe, which seems to support the argument that

96
00:06:21,640 --> 00:06:26,919
Speaker 1: this was a government led project. And generally speaking, Communist

97
00:06:27,000 --> 00:06:31,240
Speaker 1: countries like Cuba and China traditionally maintain tight controls over

98
00:06:31,360 --> 00:06:34,560
Speaker 1: communication channels, and they use that control to limit what

99
00:06:34,680 --> 00:06:37,960
Speaker 1: citizens can say or access in an effort to maintain

100
00:06:38,040 --> 00:06:42,279
Speaker 1: authoritarian control. I'm not saying those are the only places

101
00:06:42,320 --> 00:06:45,800
Speaker 1: where that happens, or that authoritarian control is limited to

102
00:06:45,920 --> 00:06:49,480
Speaker 1: communist countries, just saying that that tends to be a

103
00:06:49,520 --> 00:06:55,000
Speaker 1: pretty common practice. Speaking of China, that country is leaning

104
00:06:55,040 --> 00:06:59,000
Speaker 1: heavily on facial recognition technology as it attempts to handle

105
00:06:59,400 --> 00:07:03,719
Speaker 1: new Corona of virus outbreaks. According to tech Explore, China

106
00:07:03,920 --> 00:07:09,560
Speaker 1: is pairing facial recognition technology with citizens coronavirus test results, So,

107
00:07:09,600 --> 00:07:13,520
Speaker 1: in other words, you get tested for coronavirus, the government

108
00:07:13,600 --> 00:07:17,160
Speaker 1: essentially gets access to those results, and your health status

109
00:07:17,160 --> 00:07:21,440
Speaker 1: becomes part of your identity, and the facial recognition systems

110
00:07:21,720 --> 00:07:24,320
Speaker 1: keep track of where you're going and who you happen

111
00:07:24,360 --> 00:07:27,560
Speaker 1: to be around, which probably sounds a bit scary to

112
00:07:27,640 --> 00:07:30,920
Speaker 1: most of you out there, including myself. Now. At the

113
00:07:30,960 --> 00:07:35,840
Speaker 1: same time, China is facing a pretty difficult situation that

114
00:07:35,880 --> 00:07:39,160
Speaker 1: it's in a tough position. The neighboring country of Myanmar

115
00:07:39,760 --> 00:07:43,360
Speaker 1: is the site of some massive political unrest stemming from

116
00:07:43,360 --> 00:07:46,800
Speaker 1: a coup that happened back in February, and some Myanmar

117
00:07:46,960 --> 00:07:51,280
Speaker 1: nationals have fled to China in order to escape regional violence.

118
00:07:52,000 --> 00:07:55,160
Speaker 1: Have of the new cases of coronavirus in this particular

119
00:07:55,200 --> 00:07:59,280
Speaker 1: region of China seem to link back to Myanmar nationals,

120
00:07:59,360 --> 00:08:04,320
Speaker 1: so AT raises safety concerns there. Apparently, the facial recognition

121
00:08:04,320 --> 00:08:08,160
Speaker 1: systems also have thermal detectors built in, so those can

122
00:08:08,200 --> 00:08:11,160
Speaker 1: spot people who might have elevated body temperatures, which is

123
00:08:11,160 --> 00:08:15,080
Speaker 1: a possible sign of infection. Not exactly fool proof or

124
00:08:15,080 --> 00:08:19,600
Speaker 1: anything like that. You should never, you know, depend solely

125
00:08:19,680 --> 00:08:24,320
Speaker 1: upon a temperature check. But human rights advocates are rightly

126
00:08:24,360 --> 00:08:27,920
Speaker 1: concerned that the trends we're seeing as far as surveillance

127
00:08:27,960 --> 00:08:31,480
Speaker 1: and facial recognition go, are going to continue even beyond

128
00:08:31,560 --> 00:08:35,480
Speaker 1: the pandemic, with China leaning on those technologies while targeting

129
00:08:35,520 --> 00:08:39,439
Speaker 1: ethnic minority groups or people who criticize the government, something

130
00:08:39,640 --> 00:08:43,680
Speaker 1: that the country has been known to do extensively in

131
00:08:43,720 --> 00:08:48,360
Speaker 1: the past. Google is protesting a nearly six hundred million

132
00:08:48,400 --> 00:08:51,840
Speaker 1: dollar fine that the company faces in France. At the

133
00:08:51,920 --> 00:08:54,160
Speaker 1: heart of the matter is that the French courts have

134
00:08:54,240 --> 00:08:58,200
Speaker 1: placed numerous injunctions on Google, requiring the company to pay

135
00:08:58,240 --> 00:09:01,679
Speaker 1: publishers for their content. It something the court says that

136
00:09:01,760 --> 00:09:05,360
Speaker 1: Google has largely disregarded. Now anyone who has worked in

137
00:09:05,360 --> 00:09:10,800
Speaker 1: the publishing industry knows that advertising revenue has dropped significantly

138
00:09:11,040 --> 00:09:14,520
Speaker 1: over the last couple of decades, making it harder to

139
00:09:14,640 --> 00:09:19,080
Speaker 1: run a viable publishing business online. The European Union holds

140
00:09:19,080 --> 00:09:23,440
Speaker 1: platforms like Google partly responsible for this, arguing that these

141
00:09:23,480 --> 00:09:27,760
Speaker 1: platforms make it possible for people to access publications without

142
00:09:27,800 --> 00:09:32,120
Speaker 1: actually visiting the home site of those publications, thus denying

143
00:09:32,160 --> 00:09:35,640
Speaker 1: those companies ad revenue. If you can read the whole

144
00:09:35,760 --> 00:09:39,200
Speaker 1: article through some sort of preview that's hosted on, say

145
00:09:39,200 --> 00:09:42,520
Speaker 1: a Google site, and you never go to the home

146
00:09:42,640 --> 00:09:46,240
Speaker 1: newspaper web page, well that that paper is generating work

147
00:09:46,320 --> 00:09:48,400
Speaker 1: but not seeing any revenue for it, at least not

148
00:09:48,440 --> 00:09:52,640
Speaker 1: for that instance. Google claims that it has been working

149
00:09:52,679 --> 00:09:56,119
Speaker 1: in good faith to address these issues, with a guarantee

150
00:09:56,160 --> 00:09:59,280
Speaker 1: that the company will eventually pay out around a billion

151
00:09:59,360 --> 00:10:02,840
Speaker 1: dollars over the next three years to various publishers, as

152
00:10:02,880 --> 00:10:05,720
Speaker 1: well as to collaborate on a licensing agreement that would

153
00:10:05,720 --> 00:10:09,719
Speaker 1: provide revenue to newsrooms. The French court requires Google to

154
00:10:09,760 --> 00:10:13,000
Speaker 1: pay the five million euro fine and to form a

155
00:10:13,000 --> 00:10:17,320
Speaker 1: compensation plan with publishers within two months or face additional fines.

156
00:10:18,040 --> 00:10:21,000
Speaker 1: This is similar to the stories out of Australia, with

157
00:10:21,160 --> 00:10:26,200
Speaker 1: media companies based in Australia having issues with platforms like

158
00:10:26,240 --> 00:10:29,240
Speaker 1: Facebook and Google, and it really points to the complicated

159
00:10:29,320 --> 00:10:35,400
Speaker 1: nature of business information and platforms. Technode reports that Bite Dance,

160
00:10:35,520 --> 00:10:38,280
Speaker 1: the Chinese company that's best known here in the United

161
00:10:38,320 --> 00:10:42,359
Speaker 1: States as the parent company of TikTok, will be eliminating

162
00:10:42,480 --> 00:10:46,559
Speaker 1: its nine nine six strategy that refers to a work

163
00:10:46,600 --> 00:10:50,560
Speaker 1: week that consists of nine am to nine pm. That's

164
00:10:50,600 --> 00:10:53,360
Speaker 1: the nine nine part, and the six part means that

165
00:10:53,400 --> 00:10:58,319
Speaker 1: you're working Sunday through Friday, or six days a week. Yes,

166
00:10:58,360 --> 00:11:01,880
Speaker 1: several Chinese companies operate with the strategy. Many of them

167
00:11:02,000 --> 00:11:05,720
Speaker 1: use a big week and small week approach, that is

168
00:11:05,800 --> 00:11:09,280
Speaker 1: where employees will alternate working either five days a week

169
00:11:09,440 --> 00:11:13,280
Speaker 1: or six days a week, alternating every other Sunday. But

170
00:11:13,640 --> 00:11:16,559
Speaker 1: this is coming to an end for byte Dance in August.

171
00:11:17,040 --> 00:11:19,800
Speaker 1: While the decreased workload might be nice, it is likely

172
00:11:19,920 --> 00:11:23,520
Speaker 1: to bring along with it a salary cut, perhaps as

173
00:11:23,600 --> 00:11:26,640
Speaker 1: much as twin deeper cent, which my math tells me

174
00:11:26,960 --> 00:11:30,400
Speaker 1: would be excessive. If you're cutting two work days out

175
00:11:30,400 --> 00:11:35,040
Speaker 1: of a typical month, right that for two days out

176
00:11:35,040 --> 00:11:39,160
Speaker 1: of the month, that's excessive. Anyway, Around a third of

177
00:11:39,200 --> 00:11:42,120
Speaker 1: the company's workforce, when surveyed about this, said they would

178
00:11:42,120 --> 00:11:44,080
Speaker 1: prefer to keep their base pay where it is and

179
00:11:44,120 --> 00:11:48,280
Speaker 1: continue working longer hours, which, y'all, that just makes my

180
00:11:48,440 --> 00:11:50,520
Speaker 1: heart ache. But if you're trying to make ends, me

181
00:11:50,679 --> 00:11:54,839
Speaker 1: to cut and pay is a real unwelcome complication. It

182
00:11:54,880 --> 00:11:58,680
Speaker 1: is a tough situation and I don't have any easy

183
00:11:58,720 --> 00:12:02,840
Speaker 1: solutions here, but it really paints a pretty bleak picture,

184
00:12:03,280 --> 00:12:06,760
Speaker 1: right this idea that, oh, I can't cut back on

185
00:12:06,880 --> 00:12:10,200
Speaker 1: working twelve twelve hours a day, six days a week

186
00:12:10,600 --> 00:12:15,240
Speaker 1: because I can't afford it. Ouch. On a much lighter note,

187
00:12:15,520 --> 00:12:18,080
Speaker 1: over in the UK, we're seeing a creative approach to

188
00:12:18,120 --> 00:12:21,600
Speaker 1: advertising at soccer games, or you know, in the UK

189
00:12:21,720 --> 00:12:24,079
Speaker 1: football games, but I'm American, so I tend to call

190
00:12:24,120 --> 00:12:28,720
Speaker 1: it soccer. But many football stadiums in England have digital

191
00:12:28,760 --> 00:12:31,520
Speaker 1: signs that can display ads, which is something that's pretty

192
00:12:31,559 --> 00:12:34,400
Speaker 1: common in modern sports facilities in many parts of the world.

193
00:12:35,200 --> 00:12:38,480
Speaker 1: But what's interesting here is that people will see different

194
00:12:38,520 --> 00:12:43,320
Speaker 1: ads depending upon where they are. Those attending a game

195
00:12:43,360 --> 00:12:47,520
Speaker 1: in person we'll see ads displayed on those digital screens,

196
00:12:47,920 --> 00:12:51,080
Speaker 1: but people watching the game on television might see a

197
00:12:51,240 --> 00:12:56,920
Speaker 1: totally different ad, essentially superimposed or digitally replacing the ad

198
00:12:56,960 --> 00:13:00,880
Speaker 1: that's quote unquote really there. Broadcast masters will be able

199
00:13:00,920 --> 00:13:04,480
Speaker 1: to work with advertisers and swap out ads, creating a

200
00:13:04,480 --> 00:13:07,640
Speaker 1: new source of revenue. So the sporting facility can make

201
00:13:07,679 --> 00:13:11,560
Speaker 1: deals with say local businesses, and the broadcasters might go

202
00:13:11,679 --> 00:13:15,640
Speaker 1: for larger regional businesses. Or you could imagine a deal

203
00:13:16,000 --> 00:13:18,760
Speaker 1: that includes both the in stadium experience for the people

204
00:13:18,760 --> 00:13:22,079
Speaker 1: who are there in person, as well as the televised audience,

205
00:13:22,200 --> 00:13:24,800
Speaker 1: and you just pay a larger fee to get both.

206
00:13:25,440 --> 00:13:28,520
Speaker 1: We've seen some other examples of this kind of digital advertising,

207
00:13:28,600 --> 00:13:32,120
Speaker 1: sometimes with glitches that can affect a TV audience is

208
00:13:32,240 --> 00:13:36,080
Speaker 1: viewing experience. Now, thankfully, if you're watching the game in person,

209
00:13:36,360 --> 00:13:38,920
Speaker 1: you would never know about those glitches because so far

210
00:13:39,240 --> 00:13:42,440
Speaker 1: they don't actually, you know, cross into reality yet. I'm

211
00:13:42,440 --> 00:13:46,280
Speaker 1: sure we will see more incorporations of technologies like this,

212
00:13:46,840 --> 00:13:50,520
Speaker 1: and when we see more augmented reality in the future

213
00:13:50,760 --> 00:13:56,559
Speaker 1: being incorporated into sporting events, we'll see even more targeted advertising. Potentially,

214
00:13:56,600 --> 00:13:59,959
Speaker 1: we can reach a point where every single person attend

215
00:14:00,200 --> 00:14:03,640
Speaker 1: a game is seeing a different targeted ad through their

216
00:14:03,679 --> 00:14:08,880
Speaker 1: own personalized a R system. What a world. I've got

217
00:14:08,920 --> 00:14:11,800
Speaker 1: a few more stories to cover, but before I get

218
00:14:11,840 --> 00:14:22,160
Speaker 1: to that, let's take a quick break. We were just

219
00:14:22,400 --> 00:14:25,400
Speaker 1: in the UK before the break. Now we're gonna take

220
00:14:25,440 --> 00:14:28,720
Speaker 1: a trip across the English Channel head over to the

221
00:14:28,800 --> 00:14:32,720
Speaker 1: continent of Europe. UK is not included in this, but

222
00:14:32,880 --> 00:14:36,600
Speaker 1: Intel recently announced that the company intends to invest as

223
00:14:36,640 --> 00:14:40,120
Speaker 1: much as twenty billion dollars over the next several years

224
00:14:40,360 --> 00:14:44,720
Speaker 1: to build out some chip manufacturing plants, potentially in Europe.

225
00:14:45,240 --> 00:14:48,520
Speaker 1: The world is still in a semiconductor shortage, which is

226
00:14:48,600 --> 00:14:52,680
Speaker 1: largely because of the coronavirus and how that completely disrupted

227
00:14:52,680 --> 00:14:56,640
Speaker 1: the semiconductor supply chain over in the EU. The plan

228
00:14:56,920 --> 00:15:00,160
Speaker 1: is to boost Europe's market share of semi conduct or

229
00:15:00,240 --> 00:15:04,840
Speaker 1: manufacturing from ten percent where it is today to twenty

230
00:15:04,920 --> 00:15:10,600
Speaker 1: percent by That's a pretty aggressive timeline, but the demand

231
00:15:10,760 --> 00:15:14,880
Speaker 1: for semi conductors is definitely there because we're seeing industries

232
00:15:14,920 --> 00:15:18,760
Speaker 1: from consumer electronics to the automotive industry struggling to find

233
00:15:18,840 --> 00:15:22,600
Speaker 1: the chips that they need to produce finished products. So

234
00:15:22,640 --> 00:15:26,560
Speaker 1: we're seeing shortages and lots of industries because of semiconductor shortages.

235
00:15:27,000 --> 00:15:30,320
Speaker 1: Intel executives have been meeting with various government officials in

236
00:15:30,360 --> 00:15:34,360
Speaker 1: Europe clearly feeling out where it might be most advantageous

237
00:15:34,400 --> 00:15:38,720
Speaker 1: to establish manufacturing facilities. Now, this is a complicated process,

238
00:15:39,080 --> 00:15:42,520
Speaker 1: one that often sees companies play regions against each other

239
00:15:42,560 --> 00:15:44,720
Speaker 1: in an effort to get the best deal out of

240
00:15:44,720 --> 00:15:48,200
Speaker 1: the situation. Sometimes that can get pretty ugly. We've seen

241
00:15:48,240 --> 00:15:51,280
Speaker 1: it happen several times here in the United States. Complicating

242
00:15:51,320 --> 00:15:54,360
Speaker 1: matters is that the cost of business in places like

243
00:15:54,440 --> 00:15:59,160
Speaker 1: Europe and the United States is higher than places like, say, China.

244
00:15:59,440 --> 00:16:03,920
Speaker 1: Sometimes it's higher to the tune of around thirty more costly.

245
00:16:04,360 --> 00:16:07,240
Speaker 1: Of course, that's partly because places like Europe and the

246
00:16:07,320 --> 00:16:10,680
Speaker 1: United States have tighter regulations in place to provide at

247
00:16:10,760 --> 00:16:14,040
Speaker 1: least some level of protection to employees, and places like

248
00:16:14,160 --> 00:16:19,520
Speaker 1: China largely do not. Fun times. On a related note,

249
00:16:19,920 --> 00:16:23,880
Speaker 1: the Verge reports that the PC market is easing back

250
00:16:23,960 --> 00:16:28,480
Speaker 1: a little bit after having a pretty booming The market

251
00:16:28,640 --> 00:16:32,560
Speaker 1: is still growing, but it is growing at a reduced pace,

252
00:16:32,680 --> 00:16:36,840
Speaker 1: so it's growing more slowly than it was, and possible

253
00:16:36,880 --> 00:16:40,840
Speaker 1: reasons for that include a slightly lower demand for PCs

254
00:16:40,920 --> 00:16:46,000
Speaker 1: after the initial pandemic rush and the growing semiconductor chip

255
00:16:46,120 --> 00:16:50,360
Speaker 1: shortage being part of a factor. There businesses might be

256
00:16:50,640 --> 00:16:54,800
Speaker 1: back into purchasing computers with more businesses reopening after a

257
00:16:54,880 --> 00:16:58,160
Speaker 1: year plus of being shut down, so that could change

258
00:16:58,200 --> 00:17:01,520
Speaker 1: things a bit. But on the consumers side, it could

259
00:17:01,560 --> 00:17:04,040
Speaker 1: be that things are slowing down because people have already

260
00:17:04,080 --> 00:17:07,520
Speaker 1: done bought their ding Dan computers last year. However, we

261
00:17:07,600 --> 00:17:11,440
Speaker 1: do have Windows eleven launching later this year, and that

262
00:17:11,640 --> 00:17:15,320
Speaker 1: might end up driving more PC sales in the near future.

263
00:17:15,920 --> 00:17:18,560
Speaker 1: Now again, I do want to stress this doesn't mean

264
00:17:18,600 --> 00:17:22,159
Speaker 1: we're seeing the PC market suddenly get into trouble. The

265
00:17:22,200 --> 00:17:25,840
Speaker 1: industry is still growing quarter over quarter, It's just doing

266
00:17:25,880 --> 00:17:28,560
Speaker 1: so at a slower rate than what it was doing earlier.

267
00:17:29,119 --> 00:17:33,520
Speaker 1: The company Amazon continues in its quest for world domination

268
00:17:33,800 --> 00:17:38,760
Speaker 1: and now has its sites set on Santa Clause you

269
00:17:38,840 --> 00:17:43,119
Speaker 1: heard it here first, Because like Santa, Amazon plans to

270
00:17:43,160 --> 00:17:46,440
Speaker 1: know when you are sleeping and know when you're awake.

271
00:17:47,280 --> 00:17:50,960
Speaker 1: But since I think Amazon is largely an a moral company,

272
00:17:51,000 --> 00:17:53,840
Speaker 1: I suspect they don't actually care if you've been bad

273
00:17:53,920 --> 00:17:57,000
Speaker 1: or good. So I mean, be good for goodness sake,

274
00:17:57,400 --> 00:18:00,720
Speaker 1: just you know, as a favor to me. But I

275
00:18:00,720 --> 00:18:03,240
Speaker 1: don't think Amazon cares one way or the other. Now

276
00:18:03,280 --> 00:18:07,520
Speaker 1: Amazon has secured permission from the United States Federal Communications

277
00:18:07,520 --> 00:18:11,720
Speaker 1: Commission or FCC, to make use of a sixty giga

278
00:18:11,800 --> 00:18:16,919
Speaker 1: Hurts radar system in some future unannounced consumer device that

279
00:18:16,960 --> 00:18:20,119
Speaker 1: would be able to sense gesture commands. And here's the

280
00:18:20,160 --> 00:18:25,320
Speaker 1: bigge monitor sleeping habits through radar. Now, this is all

281
00:18:25,359 --> 00:18:28,400
Speaker 1: from the Register, by the way, and the permission from

282
00:18:28,440 --> 00:18:32,000
Speaker 1: the f c C was a necessity because the sixty

283
00:18:32,000 --> 00:18:35,720
Speaker 1: giga Hurts frequency range is above what's typically allowed for

284
00:18:35,800 --> 00:18:42,000
Speaker 1: consumer devices. Every nation has divided up the electro magnetic

285
00:18:42,080 --> 00:18:47,280
Speaker 1: frequency spectrum to designate which slices of that spectrum can

286
00:18:47,320 --> 00:18:51,760
Speaker 1: be used for different purposes, and that way you avoid

287
00:18:51,840 --> 00:18:56,239
Speaker 1: having to competing technologies trying to make use of the

288
00:18:56,320 --> 00:18:59,400
Speaker 1: same frequency space, which would create a lot of interference.

289
00:18:59,760 --> 00:19:04,680
Speaker 1: So this case, the FCC was needed to be brought

290
00:19:04,720 --> 00:19:08,640
Speaker 1: in on this because that that frequency range is typically

291
00:19:08,640 --> 00:19:11,639
Speaker 1: not something that a consumer electronic product would be able

292
00:19:11,680 --> 00:19:15,320
Speaker 1: to take advantage of. So Amazon had to get permission

293
00:19:15,359 --> 00:19:21,200
Speaker 1: from the FCC, and the f c C granted that permission. Uh. Now,

294
00:19:22,480 --> 00:19:25,919
Speaker 1: the Register reports that as of now, the the proposed

295
00:19:25,960 --> 00:19:30,520
Speaker 1: device only has the vagueust of outlined purposes. It will

296
00:19:30,560 --> 00:19:34,359
Speaker 1: be a non mobile device, so Presumably this would be

297
00:19:34,400 --> 00:19:37,040
Speaker 1: something that you would just plug into a wall outlet

298
00:19:37,080 --> 00:19:40,920
Speaker 1: in your home, and the intended purpose, according to Amazon,

299
00:19:41,480 --> 00:19:43,800
Speaker 1: is to give people who might have difficulties with some

300
00:19:43,880 --> 00:19:48,280
Speaker 1: physical activities away to interact with Amazon systems more effectively,

301
00:19:48,600 --> 00:19:50,760
Speaker 1: that being like the gesture controls and stuff, to have

302
00:19:50,800 --> 00:19:54,760
Speaker 1: a more finely tuned approach to that. So that's good

303
00:19:54,880 --> 00:19:57,920
Speaker 1: in a way. I mean, it's a way to improve accessibility,

304
00:19:57,960 --> 00:20:00,800
Speaker 1: and I think that's a good thing, but also that

305
00:20:00,840 --> 00:20:03,360
Speaker 1: such a device would help for the purposes of quote

306
00:20:03,680 --> 00:20:07,680
Speaker 1: sleep hygiene end quote. Now, if you think it's a

307
00:20:07,720 --> 00:20:12,280
Speaker 1: little creepy to have a huge company keeping track of

308
00:20:12,359 --> 00:20:15,680
Speaker 1: when you're asleep and when you're awake, then you're thinking

309
00:20:15,720 --> 00:20:18,160
Speaker 1: a lot like yours truly right here, I think it's

310
00:20:18,280 --> 00:20:21,840
Speaker 1: really creepy. However, there are a lot of sleep tracking

311
00:20:21,840 --> 00:20:25,320
Speaker 1: devices out there, and many of them do phone home

312
00:20:25,480 --> 00:20:28,440
Speaker 1: to keep track of stats like how many hours you've

313
00:20:28,480 --> 00:20:31,480
Speaker 1: slept or how many times you tossed and turned or

314
00:20:31,480 --> 00:20:35,359
Speaker 1: woke up overnight or whatever. So honestly, this isn't really

315
00:20:35,480 --> 00:20:39,119
Speaker 1: new or unique to Amazon in that sense, like we

316
00:20:39,160 --> 00:20:41,880
Speaker 1: do have other technologies that do this kind of thing.

317
00:20:42,240 --> 00:20:44,800
Speaker 1: But however, I think it's the thought that this thing

318
00:20:44,880 --> 00:20:48,320
Speaker 1: is effectively watching you sleep that makes it seem creepy

319
00:20:48,359 --> 00:20:51,600
Speaker 1: to me. But again, many of us, myself included, have

320
00:20:51,800 --> 00:20:55,080
Speaker 1: used activity trackers that also act as sleep trackers, so

321
00:20:55,200 --> 00:20:58,879
Speaker 1: I admit I'm being a little bit hypocritical here. It

322
00:20:59,000 --> 00:21:02,520
Speaker 1: also has probably because Amazon's sheer size as a company

323
00:21:02,600 --> 00:21:05,439
Speaker 1: is something I find intimidating, and to think of a

324
00:21:05,560 --> 00:21:09,560
Speaker 1: really big company closely monitoring when people are asleep or

325
00:21:09,880 --> 00:21:13,520
Speaker 1: when they're awake is unsettling. I imagine a lot of

326
00:21:13,520 --> 00:21:17,800
Speaker 1: that information could go into all sorts of different algorithms,

327
00:21:18,080 --> 00:21:22,040
Speaker 1: including recommendations. Like if I logged into Amazon and suddenly

328
00:21:22,040 --> 00:21:24,600
Speaker 1: saw that all the recommendations were for pillows and white

329
00:21:24,640 --> 00:21:28,639
Speaker 1: noise machines, I'd think, Okay, Amazon knows too much about me.

330
00:21:28,680 --> 00:21:31,680
Speaker 1: It knows that I've been dealing with insomnia recently, right,

331
00:21:31,760 --> 00:21:35,480
Speaker 1: Like that would just be creepy. Who knows what this

332
00:21:35,560 --> 00:21:38,600
Speaker 1: will ultimately turn out to be, And we may not

333
00:21:38,720 --> 00:21:42,679
Speaker 1: ever actually see this consumer product. That's another possibility. We

334
00:21:42,800 --> 00:21:46,240
Speaker 1: just don't know enough yet. But uh, it does look

335
00:21:46,240 --> 00:21:49,879
Speaker 1: like it's yet another step into the world of quantifying

336
00:21:49,960 --> 00:21:53,600
Speaker 1: everything about ourselves and handing that data over to some

337
00:21:53,680 --> 00:21:56,800
Speaker 1: other party, something that I think we should probably re

338
00:21:56,960 --> 00:22:02,240
Speaker 1: examine sooner rather than later. And our last story is

339
00:22:02,280 --> 00:22:05,280
Speaker 1: that a group of researchers with the National Institute of

340
00:22:05,400 --> 00:22:09,880
Speaker 1: Information and Communications Technology or n i c T over

341
00:22:09,920 --> 00:22:14,200
Speaker 1: in Japan have used a four core optical fiber system

342
00:22:14,240 --> 00:22:18,840
Speaker 1: with a sophisticated multiplexing technology to send data across a

343
00:22:18,920 --> 00:22:23,720
Speaker 1: physical cable at the incredible throughput of three hundred nineteen

344
00:22:23,800 --> 00:22:27,880
Speaker 1: terabits per second across a distance of just over three

345
00:22:27,920 --> 00:22:32,680
Speaker 1: thousand kilometers three thousand and one to be precise. That

346
00:22:33,240 --> 00:22:37,440
Speaker 1: is a truly astonishing data throughput rate for that kind

347
00:22:37,480 --> 00:22:41,280
Speaker 1: of distance. These days, we talk about really fast home

348
00:22:41,320 --> 00:22:44,679
Speaker 1: internet connections having a throughput of around a gigabit per second,

349
00:22:44,920 --> 00:22:47,600
Speaker 1: maybe more like maybe up to ten gigabits per second.

350
00:22:48,359 --> 00:22:51,359
Speaker 1: That's what we think of as being screaming fast for

351
00:22:51,440 --> 00:22:55,280
Speaker 1: consumer internet. But a gigabit is a billion bits per second.

352
00:22:55,640 --> 00:23:01,439
Speaker 1: Three nineteen terabits is three nineteen trillion bits per second.

353
00:23:01,640 --> 00:23:05,840
Speaker 1: To be clear. We've seen even greater throughput than this before,

354
00:23:06,160 --> 00:23:10,520
Speaker 1: but only at extremely short distances. This marks a world

355
00:23:10,560 --> 00:23:14,160
Speaker 1: record for transmitting that much data per second at that

356
00:23:14,240 --> 00:23:16,960
Speaker 1: kind of distance. Now, this doesn't mean, we're right around

357
00:23:17,000 --> 00:23:20,719
Speaker 1: the corner from all having terribit per second home connections,

358
00:23:21,160 --> 00:23:24,439
Speaker 1: which would be nice, but it's not gonna happen. This

359
00:23:24,520 --> 00:23:27,119
Speaker 1: technology is more likely to be used in applications that

360
00:23:27,160 --> 00:23:31,120
Speaker 1: relate to backbone operations of the Internet, but it's an

361
00:23:31,160 --> 00:23:36,719
Speaker 1: incredible technical achievement. Now. One day, I hope to maybe

362
00:23:36,760 --> 00:23:40,639
Speaker 1: bring someone on the show to talk about fiber optics

363
00:23:40,680 --> 00:23:44,680
Speaker 1: and what multiplexing really means and how it works, because

364
00:23:44,960 --> 00:23:49,440
Speaker 1: that subject very quickly escalates beyond my own understanding of it.

365
00:23:49,800 --> 00:23:52,280
Speaker 1: I mean, I can always research into it and and

366
00:23:52,320 --> 00:23:56,159
Speaker 1: take copious notes and such, but really, I'm just saying

367
00:23:56,200 --> 00:23:58,639
Speaker 1: that if I try to do an episode about this

368
00:23:58,680 --> 00:24:01,679
Speaker 1: all by myself, I'm probably going to get something wrong

369
00:24:02,320 --> 00:24:06,320
Speaker 1: because it is a pretty complicated topic. But I think

370
00:24:06,359 --> 00:24:08,640
Speaker 1: I might have to get somebody on to really talk

371
00:24:08,680 --> 00:24:12,080
Speaker 1: about it and get into the nitty gritty of how

372
00:24:12,160 --> 00:24:15,800
Speaker 1: fiber optics work and also why it can be so

373
00:24:15,840 --> 00:24:19,760
Speaker 1: hard to get access to fiber optics service depending on

374
00:24:19,800 --> 00:24:23,800
Speaker 1: where you live. But that's something for a later episode.

375
00:24:24,000 --> 00:24:26,840
Speaker 1: If you have suggestions for topics I should cover in

376
00:24:26,920 --> 00:24:29,479
Speaker 1: tech stuff, reach out and get in touch with me.

377
00:24:29,760 --> 00:24:31,840
Speaker 1: The best way to do that is over on Twitter.

378
00:24:32,080 --> 00:24:34,879
Speaker 1: The handle for the show is text Stuff h s W,

379
00:24:35,320 --> 00:24:40,159
Speaker 1: which I don't think is verified, but I am and

380
00:24:40,200 --> 00:24:48,399
Speaker 1: I'll talk to you again really soon. Text Stuff is

381
00:24:48,400 --> 00:24:51,560
Speaker 1: an I Heart Radio production. For more podcasts from my

382
00:24:51,680 --> 00:24:55,280
Speaker 1: Heart Radio, visit the i Heart Radio app, Apple Podcasts,

383
00:24:55,400 --> 00:25:00,119
Speaker 1: or wherever you listen to your favorite shows now