1 00:00:04,400 --> 00:00:07,800 Speaker 1: Welcome to tech Stuff, a production from I Heart Radio. 2 00:00:11,760 --> 00:00:14,960 Speaker 1: Hey there, and welcome to text Uff. I'm your host 3 00:00:15,160 --> 00:00:18,599 Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio, 4 00:00:18,800 --> 00:00:21,599 Speaker 1: and how the tech are you. It's time for the 5 00:00:21,640 --> 00:00:26,840 Speaker 1: tech news for Thursday, September twenty two. The other day, 6 00:00:26,920 --> 00:00:29,840 Speaker 1: I mentioned that Twitter shareholders were voting on whether or 7 00:00:29,880 --> 00:00:34,159 Speaker 1: not to approve Elon Musk's offer to acquire Twitter, an 8 00:00:34,159 --> 00:00:39,479 Speaker 1: offer that Musk has famelessly reconsidered since that happened all 9 00:00:39,520 --> 00:00:43,800 Speaker 1: earlier this year. The shareholders voted in favor, which was 10 00:00:43,840 --> 00:00:46,879 Speaker 1: not a surprise. Musk's offer was to buy Twitter at 11 00:00:46,920 --> 00:00:50,479 Speaker 1: fifty four dollars twenty cents per share, which is higher 12 00:00:50,520 --> 00:00:54,840 Speaker 1: than where it's trading right now. It was at eight 13 00:00:54,960 --> 00:00:57,720 Speaker 1: cents a share as of the writing of this episode. 14 00:00:58,600 --> 00:01:01,520 Speaker 1: Musk is currently in of in a lawsuit with Twitter. 15 00:01:02,440 --> 00:01:05,800 Speaker 1: The company is attempting to force Musk to go through 16 00:01:05,840 --> 00:01:09,760 Speaker 1: the deal, while Musk is trying to extricate himself from it. 17 00:01:10,120 --> 00:01:14,720 Speaker 1: One of Musk's arguments is that Twitter knowingly withheld information 18 00:01:14,840 --> 00:01:19,240 Speaker 1: from him, then from agencies like the SEC that would 19 00:01:19,240 --> 00:01:24,440 Speaker 1: have otherwise impacted the company's value, and thus that would 20 00:01:24,480 --> 00:01:28,319 Speaker 1: negate the terms of the deal, and while I was 21 00:01:28,560 --> 00:01:32,840 Speaker 1: skeptical about those claims at first, our next news item 22 00:01:33,440 --> 00:01:38,240 Speaker 1: definitely muddies the waters a bit, and that is because 23 00:01:38,720 --> 00:01:42,080 Speaker 1: of a former head of security at Twitter who has 24 00:01:42,160 --> 00:01:45,280 Speaker 1: testified in front of Congress that Twitter has had truly 25 00:01:45,520 --> 00:01:49,800 Speaker 1: terrible security practices in place, including going so far as 26 00:01:49,840 --> 00:01:53,520 Speaker 1: to accuse Twitter of having employed foreign government agents in 27 00:01:53,600 --> 00:01:58,000 Speaker 1: positions where they could potentially access a huge amount of 28 00:01:58,080 --> 00:02:03,600 Speaker 1: company data, including user data. Obviously, that poses as a 29 00:02:03,680 --> 00:02:07,560 Speaker 1: massive security risk, not just for corporate security or even 30 00:02:07,680 --> 00:02:12,760 Speaker 1: for personal security, but potentially national security. The former head 31 00:02:12,800 --> 00:02:17,520 Speaker 1: of security, Peter Mudge Zako, was fired from his position 32 00:02:17,560 --> 00:02:22,040 Speaker 1: earlier this year. Twitter reps claim that zach Co's accounts 33 00:02:22,080 --> 00:02:26,520 Speaker 1: are misleading and filled with misinformation. Zacho argues that Twitter 34 00:02:26,600 --> 00:02:31,640 Speaker 1: has knowingly practiced poor security despite numerous warnings. The whole 35 00:02:31,639 --> 00:02:36,080 Speaker 1: thing is ugly and definitely of massive concern. If zach 36 00:02:36,120 --> 00:02:39,200 Speaker 1: COO's allegations have even a little bit of truth to them, 37 00:02:39,360 --> 00:02:41,919 Speaker 1: and for the record, I have no reason to disbelieve 38 00:02:42,000 --> 00:02:44,800 Speaker 1: za Co, but then I don't have any insider knowledge 39 00:02:44,800 --> 00:02:48,120 Speaker 1: one way or the other. If Zak's accusations are true, 40 00:02:49,120 --> 00:02:52,320 Speaker 1: could this information be what Musk needs to get out 41 00:02:52,320 --> 00:02:56,959 Speaker 1: of his acquisition deal. That is possible. A court will 42 00:02:57,000 --> 00:02:59,920 Speaker 1: have to determine if the revelations were likely to have 43 00:03:00,000 --> 00:03:04,000 Speaker 1: an impact on Twitter's valuation, which is kind of crazy 44 00:03:04,040 --> 00:03:06,840 Speaker 1: to say, but from my understanding, that's what this boils 45 00:03:06,880 --> 00:03:10,720 Speaker 1: down to. It's not so much about legality or responsibility 46 00:03:10,840 --> 00:03:14,560 Speaker 1: or anything like that. It's about whether or not Twitter's 47 00:03:14,600 --> 00:03:18,320 Speaker 1: actions would have had a negative impact on Twitter's value, 48 00:03:18,840 --> 00:03:22,720 Speaker 1: because if Twitter misrepresented its value, you could then argue 49 00:03:22,760 --> 00:03:25,880 Speaker 1: that Musk's offer was based on a lie and that 50 00:03:25,960 --> 00:03:27,960 Speaker 1: this would be grounds to allow him to back out 51 00:03:27,960 --> 00:03:31,120 Speaker 1: of the deal, though not without paying a billion dollar 52 00:03:31,240 --> 00:03:35,640 Speaker 1: fee to do so. This massive chaotic mess with the 53 00:03:35,680 --> 00:03:39,200 Speaker 1: Twitter acquisition might have been avoided with a different kind 54 00:03:39,200 --> 00:03:42,839 Speaker 1: of deal in place, but Musk essentially waive the right 55 00:03:42,880 --> 00:03:46,320 Speaker 1: to do diligence as part of the deal. Honestly, this 56 00:03:46,360 --> 00:03:49,640 Speaker 1: whole story has become so complicated and controversial that I 57 00:03:49,640 --> 00:03:52,440 Speaker 1: imagine I will have to do a really thorough episode 58 00:03:52,480 --> 00:03:55,880 Speaker 1: about the whole thing once it concludes one way or 59 00:03:55,920 --> 00:03:59,440 Speaker 1: the other. As for odds on whether the deal goes through, 60 00:03:59,800 --> 00:04:03,080 Speaker 1: I just don't know. It's still down to the courts 61 00:04:03,080 --> 00:04:06,120 Speaker 1: to decide if any of this matters or if it doesn't, 62 00:04:06,640 --> 00:04:10,760 Speaker 1: or whether the deal conditions remain unaffected. Up until the 63 00:04:10,800 --> 00:04:15,240 Speaker 1: whistleblower story broke, the general sense I got from analysts 64 00:04:15,400 --> 00:04:17,960 Speaker 1: was that Musk's legal team was failing to put up 65 00:04:17,960 --> 00:04:21,039 Speaker 1: a solid argument for being able to back out of 66 00:04:21,040 --> 00:04:24,440 Speaker 1: the deal. However, that might have changed. I haven't seen 67 00:04:24,480 --> 00:04:27,200 Speaker 1: a whole lot of analysis about this yet, and I 68 00:04:27,240 --> 00:04:30,120 Speaker 1: am by no means an expert on the subject. So 69 00:04:30,400 --> 00:04:32,240 Speaker 1: we'll just have to keep our eyes on this and 70 00:04:32,279 --> 00:04:36,360 Speaker 1: we'll follow up as more develops. The United States Senate 71 00:04:36,400 --> 00:04:40,200 Speaker 1: put social media, including Twitter, in the spotlight yesterday with 72 00:04:40,240 --> 00:04:45,160 Speaker 1: a congressional hearing investigating how social media can escalate harmful narratives, 73 00:04:45,680 --> 00:04:48,480 Speaker 1: how it can spread misinformation, and how it can present 74 00:04:48,480 --> 00:04:53,440 Speaker 1: a risk to national security. Representatives from YouTube, Meta, Twitter, 75 00:04:53,560 --> 00:04:56,760 Speaker 1: and TikTok were present and had to answer questions from 76 00:04:56,839 --> 00:05:01,040 Speaker 1: various senators that ran the gambit from a allowing misinformation 77 00:05:01,040 --> 00:05:05,880 Speaker 1: to propagate across communities to the very tired accusations claiming 78 00:05:05,880 --> 00:05:09,240 Speaker 1: that platforms have an anti conservative bias, which has been 79 00:05:09,320 --> 00:05:12,520 Speaker 1: thoroughly disproven numerous times, but it's a favorite talking point 80 00:05:12,760 --> 00:05:15,960 Speaker 1: at these sort of hearings and other questions would probe 81 00:05:15,960 --> 00:05:20,160 Speaker 1: things like TikTok's relationship with its Chinese parent company, Byte Dance. 82 00:05:20,680 --> 00:05:23,240 Speaker 1: That's something that has also been a frequent topic of 83 00:05:23,279 --> 00:05:27,080 Speaker 1: conversation for the past few years, and the tone in 84 00:05:27,120 --> 00:05:31,760 Speaker 1: the hearings was reportedly pretty tense and antagonistic. Both sides 85 00:05:31,800 --> 00:05:35,599 Speaker 1: of the political spectrum have access to grind with these 86 00:05:35,600 --> 00:05:39,320 Speaker 1: tech companies, though the points of view can be pretty different, 87 00:05:39,920 --> 00:05:42,760 Speaker 1: and there has been an increase in pressure on the 88 00:05:42,760 --> 00:05:47,840 Speaker 1: tech industry from US regulators to pull back in some areas. 89 00:05:47,880 --> 00:05:51,800 Speaker 1: That's pretty tough to do when for years these companies 90 00:05:51,839 --> 00:05:54,520 Speaker 1: were given a ton of freedom to expand without many 91 00:05:54,680 --> 00:05:58,200 Speaker 1: checks and balances. You know, it's always harder to correct 92 00:05:58,600 --> 00:06:01,839 Speaker 1: after the fact and prevent it in the first place. 93 00:06:01,880 --> 00:06:05,240 Speaker 1: But here we are anyway. The cynical folks out there 94 00:06:05,279 --> 00:06:09,280 Speaker 1: will likely say that the hearings, well uncomfortable for the reps, 95 00:06:09,320 --> 00:06:13,800 Speaker 1: are unlikely to lead to meaningful change. The more optimistic 96 00:06:14,160 --> 00:06:16,680 Speaker 1: might say that this is another step on a journey 97 00:06:16,760 --> 00:06:19,680 Speaker 1: for the United States that will see the country take 98 00:06:19,720 --> 00:06:23,640 Speaker 1: a firmer stance against the increased influence of tech companies 99 00:06:24,160 --> 00:06:28,080 Speaker 1: and how that influence can lead to dangerous situations. I 100 00:06:28,320 --> 00:06:31,520 Speaker 1: honestly don't know where I fall on this. I would 101 00:06:31,560 --> 00:06:34,240 Speaker 1: like to think that we'll see some real change in 102 00:06:34,279 --> 00:06:37,479 Speaker 1: an effort to better protect citizens. But you know, fool 103 00:06:37,520 --> 00:06:42,479 Speaker 1: me once. Shame on you, fully three twenty nine congressional hearings, 104 00:06:42,520 --> 00:06:45,840 Speaker 1: and something's actually gonna get done about this, and shame 105 00:06:45,920 --> 00:06:49,600 Speaker 1: on me. One place in the United States that does 106 00:06:49,720 --> 00:06:52,800 Speaker 1: tend to take a pretty tough stance against overreach in 107 00:06:52,839 --> 00:06:56,480 Speaker 1: the tech industry is California. Considering that's where a ton 108 00:06:56,520 --> 00:07:00,359 Speaker 1: of tech companies make their headquarters. That's impressive. Now. I 109 00:07:00,400 --> 00:07:03,520 Speaker 1: say that because we have to acknowledge that the influence 110 00:07:03,520 --> 00:07:07,040 Speaker 1: of tech companies extends beyond their influence in the market, 111 00:07:07,680 --> 00:07:12,200 Speaker 1: and it then rolls over into political influence through things 112 00:07:12,280 --> 00:07:16,760 Speaker 1: like lobbyists and other means. Anyway, the state of California 113 00:07:16,840 --> 00:07:21,280 Speaker 1: has brought a lawsuit against Amazon, accusing the company of 114 00:07:21,320 --> 00:07:28,280 Speaker 1: practicing anti competitive behavior. Specifically, California's Attorney General accuses Amazon 115 00:07:28,520 --> 00:07:32,880 Speaker 1: of burying or even preventing listings that are from other 116 00:07:32,960 --> 00:07:37,480 Speaker 1: companies like Target, if those listings are for products that 117 00:07:37,520 --> 00:07:41,560 Speaker 1: are priced at a level that's below Amazon's own products, 118 00:07:41,560 --> 00:07:46,160 Speaker 1: if it's too competitive against Amazon. Then that, according to 119 00:07:46,200 --> 00:07:50,160 Speaker 1: the allegations, means the Amazon will bury it far down 120 00:07:50,160 --> 00:07:52,640 Speaker 1: in the listing so that likely no one's going to 121 00:07:52,640 --> 00:07:55,840 Speaker 1: see it, or just outright prevents it from being listed 122 00:07:55,840 --> 00:08:00,000 Speaker 1: in the first place, and thus presents the the cuss 123 00:08:00,000 --> 00:08:04,040 Speaker 1: summer with the idea that Amazon's version is the most 124 00:08:04,600 --> 00:08:08,280 Speaker 1: uh you know, cost effective and the best for the 125 00:08:08,400 --> 00:08:12,600 Speaker 1: whatever the product is. So they're saying anything that doesn't 126 00:08:13,440 --> 00:08:16,880 Speaker 1: uh beat Amazon's price, that's fine, but anything that does 127 00:08:17,800 --> 00:08:22,520 Speaker 1: gets treated like this. That's that's the accusation. It also 128 00:08:22,600 --> 00:08:29,480 Speaker 1: says that Amazon has reportedly collaborated with third party sellers 129 00:08:29,520 --> 00:08:33,080 Speaker 1: to fix pricing on various products, so, in other words, 130 00:08:33,640 --> 00:08:37,760 Speaker 1: essentially forcing smaller businesses to adjust their prices so that 131 00:08:37,840 --> 00:08:40,960 Speaker 1: they do not go below the kind of stuff that 132 00:08:41,040 --> 00:08:45,560 Speaker 1: Amazon offers. Now, price fixing is illegal, it is anti competitive. 133 00:08:45,679 --> 00:08:49,320 Speaker 1: It hurts the consumer. If all parties that are selling 134 00:08:49,360 --> 00:08:52,800 Speaker 1: widgets agree upon a price for widgets, then there's no 135 00:08:52,880 --> 00:08:56,440 Speaker 1: competition there. Right, there's no fair market. No one is 136 00:08:56,480 --> 00:09:00,200 Speaker 1: going to offer a budget widget for less because of 137 00:09:00,240 --> 00:09:04,720 Speaker 1: this agreed upon price fixing. Now, Amazon reps say that 138 00:09:04,800 --> 00:09:08,199 Speaker 1: this lawsuit is baseless. They actually point to a similar 139 00:09:08,240 --> 00:09:10,480 Speaker 1: court case that was brought against the company in Washington, 140 00:09:10,559 --> 00:09:15,040 Speaker 1: d C. The court in that instance dismissed that earlier case, 141 00:09:15,360 --> 00:09:17,440 Speaker 1: and so the reps are saying that's evidence that this 142 00:09:17,520 --> 00:09:21,080 Speaker 1: California lawsuit is without merit because these same issues were 143 00:09:21,120 --> 00:09:23,760 Speaker 1: brought up in d C and the court dismissed the case. 144 00:09:24,320 --> 00:09:28,040 Speaker 1: That's true, But it's also true that the Attorney General 145 00:09:28,080 --> 00:09:32,760 Speaker 1: in d C has appealed that court decision, so it 146 00:09:32,800 --> 00:09:35,280 Speaker 1: could turn out that this matter heads back to court 147 00:09:35,360 --> 00:09:37,880 Speaker 1: in d C as well, So it might not be 148 00:09:37,960 --> 00:09:41,800 Speaker 1: the best long term defense for Amazon. Over in South Korea, 149 00:09:41,880 --> 00:09:45,079 Speaker 1: the Personal Information Protection Commission or p i p C 150 00:09:45,360 --> 00:09:48,400 Speaker 1: has issued a fine to Google and to Meta for 151 00:09:48,440 --> 00:09:51,319 Speaker 1: the way that those companies have collected personal information for 152 00:09:51,360 --> 00:09:56,120 Speaker 1: the purposes of advertising, which appears to violate the laws 153 00:09:56,160 --> 00:09:59,880 Speaker 1: of South Korea. The finest for one hundred billion one 154 00:10:00,640 --> 00:10:05,480 Speaker 1: that's equivalent to about seventy two million dollars. Most of that, 155 00:10:05,679 --> 00:10:09,720 Speaker 1: in fact, nearly se of that is going to Google 156 00:10:10,040 --> 00:10:12,480 Speaker 1: and Meta has to cover the rest of it, and 157 00:10:12,720 --> 00:10:15,880 Speaker 1: it's the most that the agency has ever find companies 158 00:10:16,320 --> 00:10:20,480 Speaker 1: for allegedly violating laws pertaining to personal information in South Korea. 159 00:10:21,200 --> 00:10:24,800 Speaker 1: That's impressive though, you know, with companies like Google and Meta, 160 00:10:25,440 --> 00:10:29,440 Speaker 1: it's not that much money when the grand scheme of things, 161 00:10:29,480 --> 00:10:32,559 Speaker 1: I mean, obviously, no executive ever wants to have to 162 00:10:32,600 --> 00:10:35,840 Speaker 1: pay a fine, no matter how small or large it 163 00:10:35,960 --> 00:10:39,720 Speaker 1: might be. No word yet on whether Google or Meta 164 00:10:39,960 --> 00:10:43,760 Speaker 1: will appeal this decision. Okay, we've got a few more 165 00:10:43,760 --> 00:10:45,760 Speaker 1: news stories to cover before we get to that, Let's 166 00:10:45,800 --> 00:10:57,880 Speaker 1: take a quick break. Research company news Guard issued a 167 00:10:57,920 --> 00:11:02,160 Speaker 1: report yesterday that says nearly d percent of TikTok videos 168 00:11:02,160 --> 00:11:05,600 Speaker 1: that popped up in search results for specific topics would 169 00:11:05,679 --> 00:11:09,640 Speaker 1: contain misinformation, and those topics are ones that you can 170 00:11:09,720 --> 00:11:13,600 Speaker 1: probably guess for yourself. It's stuff ranging from COVID nineteen 171 00:11:13,840 --> 00:11:19,400 Speaker 1: and vaccines to Russia's invasion of Ukraine to US politics, 172 00:11:19,400 --> 00:11:25,920 Speaker 1: including very polarizing things like the January six insurrection. TikTok 173 00:11:26,040 --> 00:11:29,840 Speaker 1: has a policy to remove videos that spread misinformation, but 174 00:11:29,880 --> 00:11:33,120 Speaker 1: even so, the researchers claimed that a casual search frequently 175 00:11:33,120 --> 00:11:37,960 Speaker 1: pulls up videos that push misleading or outright false statements, 176 00:11:38,320 --> 00:11:41,440 Speaker 1: and that these videos are spreading harmful lies, such as 177 00:11:41,760 --> 00:11:45,080 Speaker 1: ones that claim vaccines against COVID can cause quote unquote 178 00:11:45,200 --> 00:11:51,400 Speaker 1: permanent damage in children's Organs. Steve Brill, the founder of NewsGuard, 179 00:11:51,920 --> 00:11:56,080 Speaker 1: didn't mince words. He said that TikTok's practices show either 180 00:11:56,240 --> 00:11:59,400 Speaker 1: the company is incompetent when it comes to dealing with 181 00:11:59,440 --> 00:12:05,360 Speaker 1: misinform nation or quote it's something worse end quote. Now, 182 00:12:05,400 --> 00:12:09,800 Speaker 1: to me, that implies that the spread of misinformation might 183 00:12:09,880 --> 00:12:13,679 Speaker 1: not be a bug, it's a feature. And when you 184 00:12:13,800 --> 00:12:16,679 Speaker 1: keep in mind the fact that TikTok does have a 185 00:12:16,800 --> 00:12:20,720 Speaker 1: Chinese parent company, and China has long had a reputation 186 00:12:20,760 --> 00:12:25,640 Speaker 1: for using tech to spread misinformation and otherwise disrupt business 187 00:12:25,720 --> 00:12:29,880 Speaker 1: and life in countries like the United States, that accusation 188 00:12:29,960 --> 00:12:33,880 Speaker 1: can get real ugly, real quick now. TikTok has long 189 00:12:33,920 --> 00:12:37,200 Speaker 1: maintained that it doesn't have that kind of relationship with 190 00:12:37,280 --> 00:12:41,440 Speaker 1: its parent company, Byte Dance, but that hasn't gone very 191 00:12:41,480 --> 00:12:44,680 Speaker 1: far to quell fears that the opposite might be true. 192 00:12:45,080 --> 00:12:47,840 Speaker 1: TikTok has pointed out that it has removed more than 193 00:12:47,880 --> 00:12:50,480 Speaker 1: a hundred million videos that were posted in the first 194 00:12:50,520 --> 00:12:54,079 Speaker 1: quarter of this year alone, But according to news outlets 195 00:12:54,160 --> 00:12:58,800 Speaker 1: like ABC, TikTok removed many of those videos for other reasons. 196 00:12:59,120 --> 00:13:01,960 Speaker 1: It wasn't because they misinformation, it was because they violated 197 00:13:02,080 --> 00:13:05,720 Speaker 1: some other policy of TikTok, and that the ones that 198 00:13:05,840 --> 00:13:11,240 Speaker 1: were removed from because they reportedly contained misinformation represent only 199 00:13:11,320 --> 00:13:15,680 Speaker 1: a small percentage of the overall group that TikTok purged. Further, 200 00:13:16,320 --> 00:13:18,679 Speaker 1: the researchers at news Guards said that when they were 201 00:13:18,720 --> 00:13:23,040 Speaker 1: searching for terms like COVID vaccine, TikTok's own search tool 202 00:13:23,600 --> 00:13:29,480 Speaker 1: started to suggest autocomplete options like COVID vaccine injury. So, 203 00:13:29,520 --> 00:13:32,920 Speaker 1: in other words, the researchers are saying that TikTok's own 204 00:13:33,000 --> 00:13:37,840 Speaker 1: search tool is helping push misinformation campaigns out to users, 205 00:13:38,320 --> 00:13:41,199 Speaker 1: and considering that a large number of TikTok users are 206 00:13:41,320 --> 00:13:45,240 Speaker 1: young people, the real fear is that kids who use 207 00:13:45,320 --> 00:13:49,240 Speaker 1: TikTok extensively are going to be depending heavily on TikTok 208 00:13:49,400 --> 00:13:53,920 Speaker 1: has a source of information, and if that information isn't valid, 209 00:13:54,000 --> 00:13:58,439 Speaker 1: if it's misinformation, if it's purposefully misleading people, that's a 210 00:13:58,520 --> 00:14:02,120 Speaker 1: huge problem. One really interesting bit of news this week 211 00:14:02,200 --> 00:14:06,520 Speaker 1: is that cryptocurrency Ethereum has made the transition from a 212 00:14:06,640 --> 00:14:10,520 Speaker 1: proof of work coin to proof of steak. So what 213 00:14:10,600 --> 00:14:14,680 Speaker 1: does that actually mean. Well, a proof of work cryptocurrency 214 00:14:14,720 --> 00:14:18,920 Speaker 1: like Bitcoin relies on computers that are connected to the 215 00:14:18,920 --> 00:14:22,480 Speaker 1: crypto network to compete against one another in order to 216 00:14:22,560 --> 00:14:26,800 Speaker 1: validate the most recent block of transactions. This is what 217 00:14:27,240 --> 00:14:31,240 Speaker 1: mining really is. The validation process is meant to take 218 00:14:31,280 --> 00:14:33,960 Speaker 1: a specific amount of time. In the case of bitcoin, 219 00:14:34,160 --> 00:14:37,040 Speaker 1: it's about ten minutes. It's much shorter, or it was 220 00:14:37,120 --> 00:14:41,160 Speaker 1: much shorter for ethereum. But how do you guarantee that 221 00:14:41,280 --> 00:14:43,920 Speaker 1: it's going to take ten minutes to complete a computer 222 00:14:44,000 --> 00:14:47,880 Speaker 1: problem when you cannot predict how powerful the computer systems 223 00:14:47,920 --> 00:14:50,960 Speaker 1: connected to your network are going to be. Well, you 224 00:14:51,000 --> 00:14:54,360 Speaker 1: do it by tweaking the difficulty of the computer problem. 225 00:14:54,720 --> 00:14:57,840 Speaker 1: So if you notice that computers are starting to solve 226 00:14:57,920 --> 00:15:02,120 Speaker 1: problems more quickly, you make that problem harder to solve. 227 00:15:02,720 --> 00:15:06,160 Speaker 1: Has more powerful machines under the network, the task continues 228 00:15:06,160 --> 00:15:08,760 Speaker 1: to get harder and harder, which prompts people to add 229 00:15:08,800 --> 00:15:12,400 Speaker 1: even more powerful machines to the network, and this escalates 230 00:15:12,440 --> 00:15:14,920 Speaker 1: until you get to a point where it wouldn't make 231 00:15:14,960 --> 00:15:18,800 Speaker 1: sense to add a more powerful machine because the cost 232 00:15:18,840 --> 00:15:21,920 Speaker 1: of operating the machine is greater than the profit you 233 00:15:21,960 --> 00:15:24,640 Speaker 1: would get from mining the crypto in the first place. 234 00:15:25,480 --> 00:15:29,440 Speaker 1: So while this is happening, it means that the miners 235 00:15:29,680 --> 00:15:32,800 Speaker 1: are using up more and more electricity as they're dedicating 236 00:15:32,840 --> 00:15:36,480 Speaker 1: increasingly powerful processing networks in order to be the first 237 00:15:36,520 --> 00:15:40,000 Speaker 1: to mind the next block of transactions and thus read 238 00:15:40,120 --> 00:15:43,760 Speaker 1: the rewards. Because this is how new cryptocurrency gets minted. 239 00:15:44,360 --> 00:15:49,840 Speaker 1: It is minted and then awarded to whichever system managed 240 00:15:49,880 --> 00:15:55,160 Speaker 1: to validate the transaction that last block of transactions, and 241 00:15:55,360 --> 00:15:59,800 Speaker 1: until Ethereum transition to proof of stake this week, that's 242 00:15:59,840 --> 00:16:04,480 Speaker 1: how all things worked on ethereum. Uh. You know, if 243 00:16:04,840 --> 00:16:08,240 Speaker 1: the the ether value was not anywhere close to bitcoin, 244 00:16:08,680 --> 00:16:13,360 Speaker 1: so it was much less valuable than Bitcoin was. So 245 00:16:13,560 --> 00:16:17,960 Speaker 1: your typical Ethereum mining system did not run on the 246 00:16:18,000 --> 00:16:21,200 Speaker 1: same sort of mega powerful rigs that are used for Bitcoin, 247 00:16:21,600 --> 00:16:25,600 Speaker 1: but still really chunky machines, and they use things like 248 00:16:25,640 --> 00:16:31,080 Speaker 1: graphics processing cards to power the actual operations. Bitcoin had 249 00:16:31,160 --> 00:16:35,840 Speaker 1: graduated beyond graphics processing cards. It is into custom built 250 00:16:35,920 --> 00:16:40,160 Speaker 1: rigs that are way more expensive to buy and operate, 251 00:16:40,280 --> 00:16:43,080 Speaker 1: and thus, you know, again, it would make no sense 252 00:16:43,120 --> 00:16:47,040 Speaker 1: to use that kind of machine for ethere Um because 253 00:16:47,080 --> 00:16:49,000 Speaker 1: you'd be spending more money on the machine than you 254 00:16:49,000 --> 00:16:53,320 Speaker 1: would make in the mining process. Anyway, the proof of 255 00:16:53,400 --> 00:16:56,880 Speaker 1: stake approach is different. It requires Ethereum holders who want 256 00:16:56,960 --> 00:17:01,000 Speaker 1: to participate in the mining process to put up a 257 00:17:01,120 --> 00:17:06,920 Speaker 1: stake a percentage of their Ether holdings in order to participate, 258 00:17:06,960 --> 00:17:10,920 Speaker 1: and essentially, parties that have the most ether put up 259 00:17:10,960 --> 00:17:13,600 Speaker 1: at steak end up being the ones that even stand 260 00:17:13,600 --> 00:17:18,000 Speaker 1: a chance at mining the next block of transactions successfully. 261 00:17:18,080 --> 00:17:21,600 Speaker 1: So while proof of steak means Ethereum is going to 262 00:17:21,680 --> 00:17:25,600 Speaker 1: put a much smaller demand on electricity, which is a 263 00:17:25,640 --> 00:17:30,000 Speaker 1: good thing, don't get me wrong, that's important, it does, however, 264 00:17:30,080 --> 00:17:34,960 Speaker 1: mean that the parties most likely to earn newly minted 265 00:17:35,000 --> 00:17:38,439 Speaker 1: ether are the ones that are already swimming in the stuff, 266 00:17:38,840 --> 00:17:41,119 Speaker 1: so the rich get richer. You could actually argue that 267 00:17:41,200 --> 00:17:45,440 Speaker 1: this approach centralizes what is supposed to be a decentralized 268 00:17:45,520 --> 00:17:49,960 Speaker 1: form of currency. It centralizes it into a cabal of 269 00:17:50,560 --> 00:17:54,439 Speaker 1: ether's biggest holders, but that is a matter for a 270 00:17:54,520 --> 00:17:58,520 Speaker 1: different episode. In fact, I've actually recorded an episode like 271 00:17:58,640 --> 00:18:01,840 Speaker 1: that in the past, so if you want to learn more, 272 00:18:01,880 --> 00:18:04,480 Speaker 1: you can go through the back catalog and find my 273 00:18:04,560 --> 00:18:08,000 Speaker 1: discussion about proof of work versus proof of steak. The 274 00:18:08,080 --> 00:18:11,240 Speaker 1: Register reports that John Deer, the company known for making 275 00:18:11,280 --> 00:18:15,960 Speaker 1: farm machinery, expects software fees to make up to ten 276 00:18:16,119 --> 00:18:18,359 Speaker 1: percent of the company's revenue by the end of the 277 00:18:18,359 --> 00:18:23,840 Speaker 1: twenty twenties. That's kind of wild, right, that a company 278 00:18:23,880 --> 00:18:28,679 Speaker 1: that makes farm machinery expects ten percent of its revenue 279 00:18:28,720 --> 00:18:33,520 Speaker 1: to come from software fees. You know, if you're a 280 00:18:33,560 --> 00:18:37,119 Speaker 1: company that makes tractors, you probably you aren't thought of 281 00:18:37,160 --> 00:18:41,200 Speaker 1: as being a software company. That seems counterintuitive, but it's 282 00:18:41,240 --> 00:18:45,800 Speaker 1: true that new farm machinery is surprisingly sophisticated, or at 283 00:18:45,840 --> 00:18:48,960 Speaker 1: least it's surprising if you aren't familiar with farm equipment. 284 00:18:49,000 --> 00:18:50,919 Speaker 1: If you're a farmer and you've worked with the stuff, 285 00:18:50,960 --> 00:18:54,600 Speaker 1: you know it already. But for you know, hay seeds 286 00:18:54,600 --> 00:18:57,560 Speaker 1: like myself, it can come as a bit of a shock. 287 00:18:58,320 --> 00:19:01,040 Speaker 1: But yeah, farm machines can be InCred doably complex, and 288 00:19:01,080 --> 00:19:04,480 Speaker 1: they can include features like an autopilot setting that heavily 289 00:19:04,520 --> 00:19:08,760 Speaker 1: automates operations. That's something that's really important to farmers in 290 00:19:08,800 --> 00:19:13,120 Speaker 1: a market where there might be labor shortages. Now there 291 00:19:13,280 --> 00:19:16,920 Speaker 1: is another edge to this here plow as it happens, 292 00:19:17,160 --> 00:19:19,840 Speaker 1: and that's the fact that companies like John Deer are 293 00:19:19,840 --> 00:19:25,720 Speaker 1: frequently criticized as resisting the right to repair movement. That 294 00:19:25,720 --> 00:19:28,480 Speaker 1: that a part of John Deere's strategy is to make 295 00:19:28,520 --> 00:19:32,479 Speaker 1: it difficult or impossible for farmers to maintain and repair 296 00:19:32,800 --> 00:19:36,240 Speaker 1: their own equipment or to take that equipment to a 297 00:19:36,520 --> 00:19:41,600 Speaker 1: shop of their choice. Instead, they are locked into John 298 00:19:41,680 --> 00:19:46,080 Speaker 1: Deere's ecosystem, which means they can only bring their equipment 299 00:19:46,119 --> 00:19:51,880 Speaker 1: to officially licensed parties, parties that the company has granted 300 00:19:51,920 --> 00:19:55,560 Speaker 1: a license to in order to work on these machines. 301 00:19:56,119 --> 00:19:59,440 Speaker 1: And software plays a really big part in that strategy, 302 00:19:59,480 --> 00:20:03,480 Speaker 1: and farmers have argued that John Deer has purposefully withheld 303 00:20:03,560 --> 00:20:06,760 Speaker 1: tools and software that are needed in order to make 304 00:20:06,840 --> 00:20:11,679 Speaker 1: necessary repairs. So the story illustrates both the incredible innovation 305 00:20:11,760 --> 00:20:16,040 Speaker 1: that is powering agriculture as well as the ongoing struggle 306 00:20:16,200 --> 00:20:19,160 Speaker 1: between customers and companies when it comes to the right 307 00:20:19,240 --> 00:20:24,040 Speaker 1: to repair devices and machines. Okay, we've got a couple 308 00:20:24,119 --> 00:20:26,320 Speaker 1: more stories that we want to cover. Before we get 309 00:20:26,320 --> 00:20:38,560 Speaker 1: to that, Let's take another quick break. E A, the 310 00:20:38,600 --> 00:20:43,359 Speaker 1: company that once um actually twice upon a time, was 311 00:20:43,480 --> 00:20:46,399 Speaker 1: voted as the worst company in America. That was in 312 00:20:46,440 --> 00:20:52,280 Speaker 1: The Consumerist several years ago, I think twelve and maybe anyway. 313 00:20:52,320 --> 00:20:55,840 Speaker 1: E A is rolling out a new anti cheat tool 314 00:20:56,560 --> 00:21:00,520 Speaker 1: that has some security and privacy experts concerned. Now just 315 00:21:00,600 --> 00:21:04,000 Speaker 1: to be clear e A is not the first video 316 00:21:04,040 --> 00:21:06,440 Speaker 1: game company to do this kind of thing, but e 317 00:21:06,640 --> 00:21:09,360 Speaker 1: A is a big deal in the video game industry 318 00:21:09,359 --> 00:21:13,080 Speaker 1: because it's a gargantuan company and it publishes some of 319 00:21:13,080 --> 00:21:18,080 Speaker 1: the most popular game titles in the world, like FIFA. Anyway, 320 00:21:18,720 --> 00:21:22,720 Speaker 1: this tool will install a driver that gets kernel level 321 00:21:22,840 --> 00:21:25,840 Speaker 1: access to a player's computer. But if you're not a 322 00:21:25,840 --> 00:21:28,359 Speaker 1: computer person, you might wonder, well, what the heck does 323 00:21:28,400 --> 00:21:30,960 Speaker 1: that matter? What is kernel level access? What does that 324 00:21:31,000 --> 00:21:35,359 Speaker 1: even mean? You can think of a computer's kernel as 325 00:21:35,400 --> 00:21:40,560 Speaker 1: the core of its operating system, like this is the 326 00:21:40,680 --> 00:21:44,359 Speaker 1: nexus at the center of the operating system, which I 327 00:21:44,440 --> 00:21:47,840 Speaker 1: realize is both redundant and repetitive, but forgive me. The 328 00:21:47,960 --> 00:21:52,600 Speaker 1: kernel ultimately has complete control over everything happening within the 329 00:21:52,640 --> 00:21:56,520 Speaker 1: computer system. So it's like being in the room where 330 00:21:56,520 --> 00:22:00,600 Speaker 1: it happens. As Aaron Burr would say, Well, say, I'm 331 00:22:00,600 --> 00:22:03,640 Speaker 1: getting off track again. Kernel level access is a big deal. 332 00:22:03,920 --> 00:22:06,760 Speaker 1: You're at the very heart of the operating system. Potentially 333 00:22:07,160 --> 00:22:12,480 Speaker 1: that can lead to big, be big t bad things. 334 00:22:13,119 --> 00:22:18,199 Speaker 1: So why is e A seeking kernel access in the 335 00:22:18,320 --> 00:22:22,200 Speaker 1: first place. Why is a company that previously has been 336 00:22:22,200 --> 00:22:25,960 Speaker 1: called the worst in America saying hey, trust us, let 337 00:22:26,080 --> 00:22:29,920 Speaker 1: us into the heart of your operating system on your machine. Well, 338 00:22:30,119 --> 00:22:32,879 Speaker 1: company reps say this is really the only way to 339 00:22:32,960 --> 00:22:37,840 Speaker 1: detect and prevent specific types of cheating software that are 340 00:22:37,880 --> 00:22:42,080 Speaker 1: meant to give players an advantage in online multiplayer games. 341 00:22:42,760 --> 00:22:45,040 Speaker 1: That there are cheap programs that get all the way 342 00:22:45,080 --> 00:22:49,440 Speaker 1: down to the kernel level, and these programs use methods 343 00:22:49,480 --> 00:22:53,479 Speaker 1: to mask their presence, so it's very hard for anti 344 00:22:53,600 --> 00:22:57,520 Speaker 1: cheat software to detect and prevent them. And then you 345 00:22:57,560 --> 00:23:03,800 Speaker 1: get these events online where legitimate players are beside themselves 346 00:23:03,840 --> 00:23:07,040 Speaker 1: because they can't get a fair match in whatever game 347 00:23:07,080 --> 00:23:10,200 Speaker 1: they're playing. The people they're playing against are using these 348 00:23:10,200 --> 00:23:15,760 Speaker 1: sophisticated cheat programs and are just wiping the floor with them. 349 00:23:15,840 --> 00:23:18,440 Speaker 1: And you know, that's an issue when we're talking about 350 00:23:18,480 --> 00:23:22,119 Speaker 1: competitive multiplayer online games. If you've ever had that experience 351 00:23:22,119 --> 00:23:24,560 Speaker 1: where you've played in an online game and you were 352 00:23:24,760 --> 00:23:27,480 Speaker 1: absolutely certain that the person you were playing against cheated 353 00:23:27,600 --> 00:23:30,720 Speaker 1: in order to beat you, or you watch content creators 354 00:23:30,720 --> 00:23:33,000 Speaker 1: who you know they play games for a living they 355 00:23:33,119 --> 00:23:37,560 Speaker 1: frequently encounter cheaters, is very upsetting, you know, it's it's 356 00:23:38,200 --> 00:23:42,560 Speaker 1: anytime you encounter a cheater who uses unfair advantage against you, 357 00:23:42,600 --> 00:23:45,919 Speaker 1: it's upsetting. And while e A promises that the company 358 00:23:46,000 --> 00:23:50,480 Speaker 1: takes privacy and security very seriously and that kernel level 359 00:23:50,560 --> 00:23:54,520 Speaker 1: access is necessary in order to detect and prevent this 360 00:23:54,640 --> 00:23:58,240 Speaker 1: kind of cheating, critics still worry that giving more programs 361 00:23:58,280 --> 00:24:02,800 Speaker 1: kernel level access in reduces potential weak points that others 362 00:24:02,840 --> 00:24:06,960 Speaker 1: might exploit. For example, a hacker might design a tool 363 00:24:07,520 --> 00:24:10,320 Speaker 1: that uses this sort of anti cheap process as an 364 00:24:10,480 --> 00:24:13,920 Speaker 1: entry point to target systems and get kernel level access 365 00:24:13,920 --> 00:24:17,959 Speaker 1: to other machines. Now, whether that could actually happen or not, 366 00:24:18,160 --> 00:24:22,080 Speaker 1: I don't know. I don't know how this particular tool 367 00:24:22,200 --> 00:24:25,639 Speaker 1: has been created. I don't know if there are any vulnerabilities, 368 00:24:25,640 --> 00:24:29,119 Speaker 1: but the potential for it is something to be concerned about. 369 00:24:29,600 --> 00:24:32,080 Speaker 1: I don't feel super comfortable with the idea of granting 370 00:24:32,119 --> 00:24:36,200 Speaker 1: kernel access to an anti cheap program, or really, to know, 371 00:24:36,240 --> 00:24:39,760 Speaker 1: any program really if I can avoid it. At the 372 00:24:39,800 --> 00:24:41,760 Speaker 1: same time, it's hard to come up with a strong 373 00:24:42,119 --> 00:24:46,520 Speaker 1: cheat prevention model when the cheaters have no resistance to 374 00:24:46,600 --> 00:24:50,720 Speaker 1: installing kernel level cheat software, like they're not holding back. 375 00:24:51,040 --> 00:24:53,000 Speaker 1: But by the way, I also think that that is 376 00:24:53,000 --> 00:24:55,840 Speaker 1: a terrible idea. It does open up your computer to 377 00:24:56,240 --> 00:25:00,840 Speaker 1: potential exploitation. UM like, out of all the companies that 378 00:25:00,880 --> 00:25:04,719 Speaker 1: make software, I would trust the ones that are making 379 00:25:04,880 --> 00:25:07,240 Speaker 1: or not just companies, but programs that are making software, 380 00:25:07,240 --> 00:25:09,600 Speaker 1: I would trust the ones that are making cheat software 381 00:25:09,640 --> 00:25:18,080 Speaker 1: the least, like pirated material is slightly above cheat software. Finally, 382 00:25:18,560 --> 00:25:21,840 Speaker 1: in China, there's a text to image tool called ernie 383 00:25:22,240 --> 00:25:25,680 Speaker 1: v I l G which does something similar to other 384 00:25:25,800 --> 00:25:30,240 Speaker 1: AI powered image generators like doll E two or mid 385 00:25:30,320 --> 00:25:34,120 Speaker 1: Journey UH. These tools allow a user to create a 386 00:25:34,280 --> 00:25:39,200 Speaker 1: text prompt, and then the text prompt sends that information 387 00:25:39,240 --> 00:25:43,239 Speaker 1: to the image generation tool, which will then create an 388 00:25:43,240 --> 00:25:48,280 Speaker 1: image based off that prompt. Sometimes the AI generated image 389 00:25:48,320 --> 00:25:54,560 Speaker 1: is incredible, Sometimes it's really upsetting, sometimes it's hilarious. Sometimes 390 00:25:54,560 --> 00:25:57,359 Speaker 1: it's a combination of the three or more. But the 391 00:25:57,600 --> 00:26:03,000 Speaker 1: Chinese tool has another feature. It is heavily censored. There 392 00:26:03,040 --> 00:26:06,880 Speaker 1: are some prompts that the tool will filter out immediately. 393 00:26:07,080 --> 00:26:12,480 Speaker 1: For example, you can't really generate any image relating to politics. 394 00:26:13,200 --> 00:26:17,000 Speaker 1: That includes if you put in a political leader's name 395 00:26:17,080 --> 00:26:20,960 Speaker 1: in the prompt that will trigger this, or if you 396 00:26:21,520 --> 00:26:24,840 Speaker 1: try to create an image that incorporates the Chinese flag, 397 00:26:25,560 --> 00:26:30,160 Speaker 1: or if you mentioned Tianamen Square, which is really a 398 00:26:30,160 --> 00:26:33,520 Speaker 1: a taboo subject in China. To put it lightly, but 399 00:26:33,640 --> 00:26:35,760 Speaker 1: if you put anything like that in the prompt of 400 00:26:35,800 --> 00:26:39,359 Speaker 1: this tool, you get an alert that says that the 401 00:26:39,480 --> 00:26:43,080 Speaker 1: request violates the rules of the tool and that you 402 00:26:43,119 --> 00:26:46,600 Speaker 1: have to reword it. And while most AI text too 403 00:26:46,640 --> 00:26:50,080 Speaker 1: image tools do contain filters that prevent users from making 404 00:26:50,160 --> 00:26:55,640 Speaker 1: outright objectionable material, in those cases it's self imposed. It's 405 00:26:55,760 --> 00:26:59,959 Speaker 1: it's an effort to create a healthy, stable, non contentious community, 406 00:27:00,240 --> 00:27:04,160 Speaker 1: but it's not something that is dictated to the companies 407 00:27:04,240 --> 00:27:08,280 Speaker 1: from some other outside source. In China, it's pretty much 408 00:27:08,320 --> 00:27:12,879 Speaker 1: mandated by the state, or rather by the Chinese Communist Party, 409 00:27:12,960 --> 00:27:18,280 Speaker 1: which many people equate with the state because in many 410 00:27:18,320 --> 00:27:25,600 Speaker 1: contexts that's fair. So yeah, political censorship in the Chinese 411 00:27:26,080 --> 00:27:29,640 Speaker 1: image to our text to Image tool not a big surprise, 412 00:27:29,680 --> 00:27:31,640 Speaker 1: but an interesting story that I thought I would throw 413 00:27:31,640 --> 00:27:33,960 Speaker 1: in here. That's it for this episode. If you have 414 00:27:34,080 --> 00:27:36,560 Speaker 1: suggestions for topics I should cover in future episodes of 415 00:27:36,560 --> 00:27:38,760 Speaker 1: tech Stuff, please reach out to me. One way to 416 00:27:38,800 --> 00:27:41,480 Speaker 1: do that is to download the I Heart radio app. 417 00:27:42,080 --> 00:27:44,399 Speaker 1: It's free to download and use. You can navigate over 418 00:27:44,440 --> 00:27:47,159 Speaker 1: to tech Stuff. There's a little microphone icon click on 419 00:27:47,240 --> 00:27:49,439 Speaker 1: that you can leave a message up to thirty seconds 420 00:27:49,440 --> 00:27:51,639 Speaker 1: in length let me know what you would like to 421 00:27:51,680 --> 00:27:55,119 Speaker 1: hear about, or you can reach out on Twitter handle 422 00:27:55,160 --> 00:27:58,960 Speaker 1: for the show is Text Stuff HSW and I'll talk 423 00:27:59,000 --> 00:28:08,360 Speaker 1: to you again really soon. YEA. Text Stuff is an 424 00:28:08,359 --> 00:28:12,080 Speaker 1: I Heart Radio production. For more podcasts from I Heart Radio, 425 00:28:12,400 --> 00:28:15,560 Speaker 1: visit the i Heart Radio app, Apple Podcasts, or wherever 426 00:28:15,640 --> 00:28:17,159 Speaker 1: you listen to your favorite shows.