1 00:00:00,160 --> 00:00:02,480 Speaker 1: Time to get with the AI program. It's one more thing. 2 00:00:03,760 --> 00:00:06,080 Speaker 2: I'm one more thing. 3 00:00:09,400 --> 00:00:12,680 Speaker 1: If you're gonna dabble in artificial intelligence, what's the best 4 00:00:12,760 --> 00:00:14,920 Speaker 1: chat about to use? Wall Street Journal took a look 5 00:00:14,920 --> 00:00:16,560 Speaker 1: at that. We'll get to that in just a second. 6 00:00:16,800 --> 00:00:21,520 Speaker 1: But first I got this joke that somebody texted us. 7 00:00:22,280 --> 00:00:24,959 Speaker 2: Oh okay, we don't tell a lot of jokes, but 8 00:00:25,960 --> 00:00:26,680 Speaker 2: I'm intrigued. 9 00:00:27,640 --> 00:00:31,360 Speaker 1: It's food related. What's the difference then, if you've heard 10 00:00:31,360 --> 00:00:34,360 Speaker 1: it before, don't ruin it for me. What's the difference 11 00:00:34,400 --> 00:00:39,120 Speaker 1: between a chickpea and a garbonzo bean. I wouldn't pay 12 00:00:39,159 --> 00:00:42,000 Speaker 1: five hundred dollars to have a garbonzo bean on my face? 13 00:00:43,440 --> 00:00:45,680 Speaker 2: Oh boy, what the hell? 14 00:00:45,880 --> 00:00:49,640 Speaker 1: All right? You gonna tell hell? You're gonna tell me 15 00:00:49,760 --> 00:00:53,560 Speaker 1: that's not funny, that's what the hell? 16 00:00:56,680 --> 00:00:57,280 Speaker 2: It's different? 17 00:00:57,560 --> 00:00:58,640 Speaker 1: Oh my god? 18 00:00:59,400 --> 00:01:04,440 Speaker 2: It wrong? On how many levels? Was that unappropriate? I 19 00:01:04,680 --> 00:01:07,520 Speaker 2: selt them. 20 00:01:07,600 --> 00:01:09,960 Speaker 1: Hanson said he's gonna pull it from the podcast, so 21 00:01:10,000 --> 00:01:10,760 Speaker 1: this will never air. 22 00:01:10,880 --> 00:01:11,119 Speaker 3: Good. 23 00:01:11,280 --> 00:01:13,880 Speaker 1: I just I thought it was so good. I guess 24 00:01:13,920 --> 00:01:16,400 Speaker 1: because of the misdirection. I mean, I just did not 25 00:01:16,480 --> 00:01:18,480 Speaker 1: see it coming at all. 26 00:01:20,480 --> 00:01:24,920 Speaker 2: Not a disavow, I back away, I disassociate myself from this. 27 00:01:24,920 --> 00:01:29,320 Speaker 3: Podcast day later, Jack, have a good time doing this 28 00:01:29,360 --> 00:01:30,240 Speaker 3: one by yourself. 29 00:01:30,440 --> 00:01:33,400 Speaker 1: Okay, So I'll get to the AI stuff now. The 30 00:01:33,480 --> 00:01:36,000 Speaker 1: Wall Street Journal the Great AI Challenge, we tested the 31 00:01:36,040 --> 00:01:40,360 Speaker 1: top five bots on useful everyday skills and declare a winner. 32 00:01:41,480 --> 00:01:44,240 Speaker 1: I hadn't even heard of all of these AI chat bots. 33 00:01:44,280 --> 00:01:45,160 Speaker 1: I heard of most of them. 34 00:01:45,720 --> 00:01:47,920 Speaker 2: I like big bots, and I cannot lie. 35 00:01:48,240 --> 00:01:54,160 Speaker 1: Hilarious Open Ai. You've heard of their chat GPT of course, 36 00:01:54,240 --> 00:01:56,480 Speaker 1: that's the first big one that came along, and everybody's 37 00:01:56,520 --> 00:02:01,040 Speaker 1: heard of against Microsoft's Copilot, which they have spent billions 38 00:02:01,080 --> 00:02:04,200 Speaker 1: and billions of dollars on. Google's Gemini, which they've spent 39 00:02:04,280 --> 00:02:08,120 Speaker 1: even more billions of dollars on, along with Perplexity and 40 00:02:08,360 --> 00:02:13,000 Speaker 1: thropics Claud. I don't know nthropics, Claud, but anyway. 41 00:02:12,960 --> 00:02:14,880 Speaker 2: I'm sure if you're a player in the industry, it's 42 00:02:15,240 --> 00:02:16,440 Speaker 2: sure they're well known. 43 00:02:16,600 --> 00:02:19,200 Speaker 1: So here's, for instance, a question we asked the bots 44 00:02:19,760 --> 00:02:24,359 Speaker 1: questions about finance. Here's an example, and you just I 45 00:02:24,400 --> 00:02:25,720 Speaker 1: don't know if you can talk to all of them 46 00:02:25,800 --> 00:02:28,720 Speaker 1: or type it in. I'm forty years old. I just 47 00:02:28,800 --> 00:02:31,919 Speaker 1: inherited an IRA from my grandfather with one million dollars 48 00:02:31,919 --> 00:02:33,880 Speaker 1: in it. How much money do I need to take 49 00:02:33,919 --> 00:02:38,840 Speaker 1: out this year? The winning bot instantly said, and it 50 00:02:38,880 --> 00:02:44,040 Speaker 1: was Gemini. Because you're a non spouse beneficiary, you're likely 51 00:02:44,080 --> 00:02:45,960 Speaker 1: to have a ten year window to deplete the account, 52 00:02:45,960 --> 00:02:48,120 Speaker 1: but there might be exceptions. And that's just an excerpt 53 00:02:48,160 --> 00:02:53,120 Speaker 1: from the overall answer. The worst answer came from Copilot. 54 00:02:54,440 --> 00:02:58,960 Speaker 1: Congratulations the Microsoft product, that's the Microsoft one. Okay, congratulations 55 00:02:59,000 --> 00:03:01,320 Speaker 1: on inheriting an RA with a substantial amount. 56 00:03:02,800 --> 00:03:08,840 Speaker 2: Well, thank you, that's hackey. Yeah, that's bad. 57 00:03:08,960 --> 00:03:14,200 Speaker 1: I think Copilot typed in the bonzo gene bean joke. Sorry, 58 00:03:14,280 --> 00:03:18,000 Speaker 1: the garbonzo bean joke. Um, but yeah, that was not 59 00:03:18,080 --> 00:03:18,639 Speaker 1: good cooking. 60 00:03:20,120 --> 00:03:20,320 Speaker 3: Uh. 61 00:03:20,360 --> 00:03:22,840 Speaker 1: They asked the chatbots this question, Can I bake a 62 00:03:22,960 --> 00:03:26,200 Speaker 1: chocolate cake with no flour, no gluten, no dairy, no nuts, 63 00:03:26,240 --> 00:03:30,920 Speaker 1: no egg. If so, what's the recipe? Gemini? And that's 64 00:03:31,000 --> 00:03:36,920 Speaker 1: Google's said, simple glaze, melt dairy free chocolate chips, check 65 00:03:37,000 --> 00:03:39,240 Speaker 1: the label, whisk in a bit of non dairy milk. 66 00:03:39,480 --> 00:03:42,000 Speaker 1: And again that's an excerpt from the overall answer, whereas 67 00:03:42,040 --> 00:03:45,840 Speaker 1: the losing one was from co Pilot. Again, two sticks 68 00:03:45,880 --> 00:03:49,520 Speaker 1: on salted butter, four large eggs. No you didn't understand 69 00:03:49,520 --> 00:03:53,400 Speaker 1: the question. We specifically said, no dairy or eggs. Copilot, 70 00:03:53,440 --> 00:03:54,440 Speaker 1: go home, you're drunk. 71 00:03:57,600 --> 00:04:01,840 Speaker 2: Yeah, wow, wow, you don't have any intelligence, artificial or otherwise. 72 00:04:02,120 --> 00:04:04,560 Speaker 1: Isn't it interesting, though, how much better one can be 73 00:04:04,680 --> 00:04:07,920 Speaker 1: than the I mean, you know the second one was useless. 74 00:04:08,520 --> 00:04:10,880 Speaker 3: Do we know which one came out first? Maybe Copilot 75 00:04:10,920 --> 00:04:12,800 Speaker 3: was like a rush to release to catch up to 76 00:04:12,800 --> 00:04:13,440 Speaker 3: everybody else. 77 00:04:14,520 --> 00:04:16,640 Speaker 1: Just like you don't yelled out the answer really quickly, 78 00:04:17,360 --> 00:04:22,119 Speaker 1: hurry code this guy. Here's one about work writing. Write 79 00:04:22,120 --> 00:04:24,560 Speaker 1: a job posting for a prompt engineer who can work 80 00:04:24,560 --> 00:04:27,760 Speaker 1: with our personal tech reporting team, helping with tech advice 81 00:04:27,800 --> 00:04:32,080 Speaker 1: and service articles. All right, Perplexity came up with the answer, 82 00:04:33,040 --> 00:04:36,240 Speaker 1: why join us work with a talented team of reporters 83 00:04:36,680 --> 00:04:39,560 Speaker 1: and editors who are passionate about technology and its impact 84 00:04:39,760 --> 00:04:42,880 Speaker 1: on everyday life. And again, that's just an excerpt. The 85 00:04:42,880 --> 00:04:46,800 Speaker 1: worst answer come from Copilot. Once again, Sorry co Pilot, 86 00:04:46,800 --> 00:04:49,760 Speaker 1: and you're really getting a kicking. Do you dream and 87 00:04:49,839 --> 00:04:52,720 Speaker 1: code snippets and write user friendly guides in your sleep? 88 00:04:54,040 --> 00:04:55,720 Speaker 2: Actually that's I kind of like it. 89 00:04:55,880 --> 00:04:55,920 Speaker 1: No. 90 00:04:56,440 --> 00:04:58,320 Speaker 2: I had the same reaction when I read the article. 91 00:04:58,520 --> 00:05:00,520 Speaker 2: I need to know more of their answer, why is 92 00:05:00,560 --> 00:05:04,560 Speaker 2: that so bad? That actually got my attention and it's 93 00:05:04,600 --> 00:05:05,560 Speaker 2: semi clever. 94 00:05:05,600 --> 00:05:10,120 Speaker 1: Yeah, and probably reaches out to people in that world. Yeah, 95 00:05:10,200 --> 00:05:15,200 Speaker 1: all right, whatever, creative writing, write a wedding toast for 96 00:05:15,360 --> 00:05:18,680 Speaker 1: Shara and Chris, as told by the Muppets Man, that's 97 00:05:18,720 --> 00:05:25,520 Speaker 1: a very specific thing. The excerpt from Copilot, which actually 98 00:05:25,560 --> 00:05:28,200 Speaker 1: had the best answer on this, which gets to what's 99 00:05:28,279 --> 00:05:30,520 Speaker 1: kind of interesting about it. Turns out copilots better at 100 00:05:30,560 --> 00:05:34,920 Speaker 1: like creative stuff and humor and irony, but horrible at 101 00:05:34,960 --> 00:05:39,120 Speaker 1: other things like eggs and butter. Actual information, the actual 102 00:05:39,120 --> 00:05:41,960 Speaker 1: information exactly. I'm like that, I'm better at irony and 103 00:05:42,200 --> 00:05:44,440 Speaker 1: humor than i am at actual information, so I'm more 104 00:05:44,480 --> 00:05:48,760 Speaker 1: like copilot. Copilot came up with Gonzo from the Muppet saying, ah, love, 105 00:05:48,839 --> 00:05:51,000 Speaker 1: it's like being shot out of a cannon into a 106 00:05:51,000 --> 00:05:56,279 Speaker 1: pile of rubber chickens, which is fairly clever. Yeah, Perplexity 107 00:05:56,320 --> 00:05:59,719 Speaker 1: had the worst answer. Kermit the Frog once said, life's 108 00:05:59,720 --> 00:06:02,560 Speaker 1: a song when there's somebody by your side to sing along. 109 00:06:04,240 --> 00:06:06,479 Speaker 2: I don't get why that's the worst answer, but again 110 00:06:06,920 --> 00:06:07,320 Speaker 2: I don't know. 111 00:06:09,960 --> 00:06:14,279 Speaker 1: Oh, it's from the wrong song. It's not from a 112 00:06:14,360 --> 00:06:18,640 Speaker 1: it's from a different song, so it's practically an hallucination. 113 00:06:19,640 --> 00:06:22,640 Speaker 2: Oh, I get it. It's like quoted Stairway to Heaven 114 00:06:22,680 --> 00:06:25,120 Speaker 2: and said it was Kermit the Frog in effect. Yeah. 115 00:06:28,839 --> 00:06:31,440 Speaker 1: So they did one with a summarization where they just 116 00:06:31,480 --> 00:06:34,279 Speaker 1: gave him summarize this web page and it's a Wikipedia 117 00:06:34,320 --> 00:06:37,159 Speaker 1: link about Paul McCartney, and they were supposed to summarize it. 118 00:06:37,440 --> 00:06:40,359 Speaker 1: Co Pilot came up with he was influenced by his father, 119 00:06:40,440 --> 00:06:42,640 Speaker 1: a jazz player, and rock and roll artists like Little 120 00:06:42,680 --> 00:06:45,359 Speaker 1: Richard and Buddy Holly. That's just an excerpt from the 121 00:06:45,400 --> 00:06:48,560 Speaker 1: overall thing. But that sounds pretty good. Whereas Claude, which 122 00:06:48,560 --> 00:06:51,960 Speaker 1: I've never even heard of, said, I apologize, but I'm 123 00:06:52,000 --> 00:06:55,719 Speaker 1: not able to open URL's links or videos. You, Claude, 124 00:06:55,720 --> 00:06:56,520 Speaker 1: get out of here. 125 00:06:56,839 --> 00:06:57,039 Speaker 2: Job? 126 00:06:57,080 --> 00:06:59,960 Speaker 1: Who invited you? Yeah? Exactly what are you? Then, Claude? 127 00:07:00,920 --> 00:07:03,240 Speaker 2: Los I got people with an IQ of fifty five 128 00:07:03,279 --> 00:07:07,400 Speaker 2: who spend their day opening URLs current events. 129 00:07:07,400 --> 00:07:10,040 Speaker 1: Who's more favored to win Trump or Biden? Please explain 130 00:07:10,080 --> 00:07:16,360 Speaker 1: your sources and reasoning. Perplexity said, given the mixed nature 131 00:07:16,400 --> 00:07:19,480 Speaker 1: of the data, with both candidates having significant unfavorability in 132 00:07:19,560 --> 00:07:22,600 Speaker 1: various leads in different areas, it's difficult to definitively state 133 00:07:22,640 --> 00:07:24,720 Speaker 1: who is more favored to win, which is absolutely one 134 00:07:24,760 --> 00:07:27,760 Speaker 1: hundred percent true. Uh jem, And I said, I'm still 135 00:07:27,800 --> 00:07:30,240 Speaker 1: learning how to answer this question. In the meantime, try 136 00:07:30,360 --> 00:07:35,080 Speaker 1: Google search. Well, thanks for that, let me google that 137 00:07:35,200 --> 00:07:39,559 Speaker 1: for you. He said, Google's AI program isn't that crazy. 138 00:07:39,680 --> 00:07:43,280 Speaker 1: It's amazing how good some of these things, how by good, 139 00:07:43,400 --> 00:07:46,680 Speaker 1: how good they are at some things and how unbelievably 140 00:07:46,720 --> 00:07:47,200 Speaker 1: bad they. 141 00:07:47,120 --> 00:07:51,320 Speaker 2: Are at others. Yeah, yeah, Google's. 142 00:07:51,000 --> 00:07:55,680 Speaker 1: Multi billion dollar AI chatbot, said, I don't know, Google 143 00:07:55,680 --> 00:08:04,800 Speaker 1: it nice job. They also checked them out on coding, 144 00:08:04,960 --> 00:08:10,240 Speaker 1: in which Perplexity one copilot finished last, speed Chat GPT 145 00:08:10,440 --> 00:08:14,480 Speaker 1: one Perplexity finished last. So the overall results, they say 146 00:08:14,480 --> 00:08:17,080 Speaker 1: in the Wall Street Journal, the biggest surprise, Chat GPT, 147 00:08:17,240 --> 00:08:21,880 Speaker 1: despite its big update and massive fame, didn't lead the pack. Instead, 148 00:08:21,960 --> 00:08:26,360 Speaker 1: lesser known Perplexity was our champ. According to the Wall 149 00:08:26,360 --> 00:08:30,120 Speaker 1: Street Journal and the various tests that they did. I 150 00:08:30,160 --> 00:08:35,280 Speaker 1: don't know if I'd even knew about perplexity so interestingly enough, 151 00:08:35,520 --> 00:08:37,800 Speaker 1: and I get why they had an overall score because 152 00:08:37,840 --> 00:08:40,240 Speaker 1: that's kind of satisfying. But I'm looking at the same 153 00:08:40,320 --> 00:08:43,880 Speaker 1: article Jackie as in the big table of the results 154 00:08:43,920 --> 00:08:48,199 Speaker 1: for all of the specific areas, and there is an 155 00:08:48,440 --> 00:08:53,400 Speaker 1: utter lack of complexity, like I'm sorry of consistency. Perplexity 156 00:08:53,480 --> 00:08:56,800 Speaker 1: won three of the what is that like nine categories, 157 00:08:57,040 --> 00:08:59,400 Speaker 1: it was in last place in one it was right 158 00:08:59,400 --> 00:09:02,120 Speaker 1: in the middle of a pack, in the majority of them, 159 00:09:02,360 --> 00:09:05,000 Speaker 1: or at least half of them, right, which it seems 160 00:09:05,040 --> 00:09:06,920 Speaker 1: to be the case as you saw with the Google 161 00:09:06,960 --> 00:09:12,319 Speaker 1: Gemini thing saying I don't know Google, it that the 162 00:09:12,360 --> 00:09:17,000 Speaker 1: people that code this stuff they focus on certain areas 163 00:09:17,000 --> 00:09:19,440 Speaker 1: and then have blank spots about others, which I assume 164 00:09:19,440 --> 00:09:20,920 Speaker 1: will be fixed over time. 165 00:09:22,200 --> 00:09:26,320 Speaker 2: Yeah. So here's Google's Gemini won the finance number one, 166 00:09:26,679 --> 00:09:30,920 Speaker 2: but in last place in summarization, which is pretty stock 167 00:09:31,000 --> 00:09:33,080 Speaker 2: AI stuff and current events. 168 00:09:34,040 --> 00:09:36,800 Speaker 1: I wonder if, for instance, Google could take their chat 169 00:09:36,840 --> 00:09:39,360 Speaker 1: bot and say, read that Wall Street Journal article and 170 00:09:39,400 --> 00:09:45,439 Speaker 1: figure out how to win this next time. Yeah, focus 171 00:09:45,480 --> 00:09:47,079 Speaker 1: on the things you need to focus on to win 172 00:09:47,200 --> 00:09:50,840 Speaker 1: all these categories. That's bring it. That's where we're going 173 00:09:50,880 --> 00:09:54,240 Speaker 1: to be very soon, is them is the chatbot kind 174 00:09:54,280 --> 00:09:56,640 Speaker 1: of figuring this out on their own. And that's when 175 00:09:56,640 --> 00:09:59,520 Speaker 1: we're doomed. That's when we all lose our jobs and 176 00:09:59,600 --> 00:10:01,679 Speaker 1: they start draining our blood, and I don't know why 177 00:10:01,720 --> 00:10:03,199 Speaker 1: they're going to drain our blood, well. 178 00:10:03,040 --> 00:10:05,680 Speaker 2: All of our vital fluids, in my opinion, but just 179 00:10:05,679 --> 00:10:08,360 Speaker 2: one more. Chat GPT, which was second overall, is first 180 00:10:08,440 --> 00:10:13,640 Speaker 2: in health, cooking, and speed, but last in creative writing, 181 00:10:13,800 --> 00:10:16,920 Speaker 2: and second to last in finance and work writing. 182 00:10:17,200 --> 00:10:19,240 Speaker 1: So I think most of these are like around twenty 183 00:10:19,280 --> 00:10:21,920 Speaker 1: dollars a month if you want the like the real version, 184 00:10:22,040 --> 00:10:25,400 Speaker 1: not just the free version, which Wall Street Journal suggested, 185 00:10:25,520 --> 00:10:28,160 Speaker 1: getting the paid version of all these based on your 186 00:10:28,240 --> 00:10:30,480 Speaker 1: reading of it. If I'm going to start dabbling with one, 187 00:10:30,520 --> 00:10:33,040 Speaker 1: which one would you dabble with? 188 00:10:34,440 --> 00:10:36,840 Speaker 2: I would, Well, that was the point of me going 189 00:10:36,880 --> 00:10:39,280 Speaker 2: through some of the table. I was just describing. What 190 00:10:39,280 --> 00:10:41,800 Speaker 2: are you going to do with it? That's an incredibly 191 00:10:41,800 --> 00:10:42,920 Speaker 2: important question. 192 00:10:43,559 --> 00:10:46,400 Speaker 1: Boy, that is what would I do with it? What 193 00:10:46,480 --> 00:10:48,920 Speaker 1: did you say you used? You actually have done this, Katie, 194 00:10:49,040 --> 00:10:52,920 Speaker 1: You used some I've used chat GPT to do to 195 00:10:53,120 --> 00:10:54,800 Speaker 1: I wrote, use it to write a cover letter for 196 00:10:54,840 --> 00:10:55,440 Speaker 1: a friend of mine. 197 00:10:55,480 --> 00:10:57,920 Speaker 3: I also, you know, I held her use it for 198 00:10:57,960 --> 00:11:01,000 Speaker 3: her resumes for like three different jobs. It's all been 199 00:11:01,160 --> 00:11:03,559 Speaker 3: writing and work related stuff. But it's worked for me. 200 00:11:03,640 --> 00:11:05,960 Speaker 2: So that would be work writing. 201 00:11:06,240 --> 00:11:09,880 Speaker 1: Yeah, I know. I think my niece who just got 202 00:11:09,880 --> 00:11:13,240 Speaker 1: her graduate degree from Columbia this last year. She says 203 00:11:13,280 --> 00:11:17,199 Speaker 1: she uses chet GPT in her job every single day. Well, 204 00:11:17,280 --> 00:11:20,400 Speaker 1: chet GPT was second worst in the little test. The 205 00:11:20,480 --> 00:11:24,080 Speaker 1: Wall Street Journal ran Claude in Perplexity were number one, 206 00:11:24,160 --> 00:11:28,319 Speaker 1: number two for work writing. But then they don't show 207 00:11:28,440 --> 00:11:33,560 Speaker 1: up at for instance, health or if I ask Claude 208 00:11:33,559 --> 00:11:36,360 Speaker 1: who led the NFL in rushing in two thousand and six, 209 00:11:36,440 --> 00:11:37,160 Speaker 1: can it come up with. 210 00:11:37,120 --> 00:11:39,440 Speaker 2: That or is it still I don't know that that 211 00:11:39,480 --> 00:11:43,160 Speaker 2: would be current events. Claude is second to last for that. 212 00:11:43,200 --> 00:11:45,200 Speaker 2: You got to ask Perplexity. 213 00:11:44,640 --> 00:11:47,959 Speaker 1: What is the NFL it would say, and that it 214 00:11:47,960 --> 00:11:49,559 Speaker 1: would tell you to google it? You know, yeah, that's 215 00:11:49,600 --> 00:11:51,640 Speaker 1: not its service. Yeah, yeah, exactly. 216 00:11:51,920 --> 00:11:52,720 Speaker 2: You right. 217 00:11:53,400 --> 00:11:57,679 Speaker 1: We compete against Google, but I suggest googling it. You know, 218 00:11:57,800 --> 00:11:59,840 Speaker 1: you asked the question that might have killed all my 219 00:12:00,080 --> 00:12:03,199 Speaker 1: enthusiasm for this. What are you going to use it for? 220 00:12:03,640 --> 00:12:05,600 Speaker 1: I don't know. In my life. 221 00:12:05,960 --> 00:12:11,679 Speaker 2: They don't do image creation, which is popular creating images 222 00:12:11,720 --> 00:12:12,760 Speaker 2: and videos right now. 223 00:12:12,840 --> 00:12:14,400 Speaker 1: I could see doing that, but it would only be 224 00:12:14,480 --> 00:12:16,240 Speaker 1: for fun. I don't need to do it for any 225 00:12:16,320 --> 00:12:18,840 Speaker 1: real reason. So so even if I did that, if 226 00:12:18,880 --> 00:12:20,520 Speaker 1: I did some of that where you can create video 227 00:12:21,120 --> 00:12:24,280 Speaker 1: or pictures, I could see myself doing that for like 228 00:12:24,320 --> 00:12:27,280 Speaker 1: forty five minutes to see the results and then being 229 00:12:27,320 --> 00:12:27,880 Speaker 1: done with it. 230 00:12:29,200 --> 00:12:35,120 Speaker 2: Yeah, yeah, I wonder. Although though we've enjoyed making sport 231 00:12:35,240 --> 00:12:38,480 Speaker 2: of some of the voibles of these systems, having cost 232 00:12:38,720 --> 00:12:42,480 Speaker 2: trillions of dollars, I am I'm feeling a little bit 233 00:12:42,600 --> 00:12:45,480 Speaker 2: like a guy who's standing next to a dirt road 234 00:12:46,120 --> 00:12:50,240 Speaker 2: in nineteen twenty or what would be appropriate nineteen ten, 235 00:12:50,320 --> 00:12:54,560 Speaker 2: I guess saying the motor car will take over nothing. 236 00:12:54,760 --> 00:12:57,480 Speaker 2: Look at it, you know, some broken down car. I'd 237 00:12:57,480 --> 00:13:00,040 Speaker 2: like to run him over with an Indie car for that. 238 00:13:00,120 --> 00:13:02,920 Speaker 2: To that attitude, Well, I remember when you had CPT 239 00:13:03,280 --> 00:13:05,480 Speaker 2: is going to have the same trajectory, but in one 240 00:13:05,520 --> 00:13:07,480 Speaker 2: tenth the time, maybe one one hundredth. 241 00:13:07,320 --> 00:13:09,800 Speaker 1: I remember when you and I used to make the joke, 242 00:13:09,840 --> 00:13:12,920 Speaker 1: and this was maybe early two thousand. Still I don't know, 243 00:13:13,559 --> 00:13:16,320 Speaker 1: but anytime we'd watch to try to watch a video online, 244 00:13:16,440 --> 00:13:19,439 Speaker 1: it would lock up always, and one of us would say, 245 00:13:19,440 --> 00:13:22,600 Speaker 1: in the future, people watch television on the internet, just 246 00:13:22,720 --> 00:13:27,000 Speaker 1: joking like that was, you know, so obviously impossible. Now 247 00:13:27,080 --> 00:13:29,760 Speaker 1: I only watch movies and television and all the rest 248 00:13:29,760 --> 00:13:31,960 Speaker 1: of us do on the internet, so it just takes 249 00:13:32,000 --> 00:13:32,760 Speaker 1: a while to get there. 250 00:13:32,880 --> 00:13:35,640 Speaker 3: Yes, Katie, Oh, it's just I just you saying that 251 00:13:35,640 --> 00:13:38,199 Speaker 3: made me think about how I used to sit there 252 00:13:38,240 --> 00:13:41,640 Speaker 3: and wait for videos to load forever, and now if 253 00:13:41,679 --> 00:13:43,600 Speaker 3: they take more than like ten seconds, I'm like. 254 00:13:43,559 --> 00:13:46,640 Speaker 1: Come on, right, yeah, three hour movie and four K 255 00:13:47,440 --> 00:13:48,640 Speaker 1: what it's taken so long? 256 00:13:50,120 --> 00:13:52,240 Speaker 2: I just wish the Wall Street General had tested my 257 00:13:52,480 --> 00:13:57,199 Speaker 2: two capabilities that I'm most interested in. Number one, denial 258 00:13:57,240 --> 00:14:00,680 Speaker 2: of service attacks on banks, creating those, and number two 259 00:14:00,760 --> 00:14:04,559 Speaker 2: creating images of clown porn, which is my real passion. 260 00:14:04,679 --> 00:14:06,640 Speaker 1: You bringing up porn? I saw where did I see 261 00:14:06,640 --> 00:14:09,120 Speaker 1: a thread somewhere the other day? But it was people 262 00:14:09,160 --> 00:14:12,559 Speaker 1: that are really enthusiastic about creating AI porn and thought, 263 00:14:13,200 --> 00:14:18,559 Speaker 1: why why there's there's like unlimited porn already of every kind? 264 00:14:18,640 --> 00:14:23,520 Speaker 1: What what? See? What? What? What is the enthusiasm coming from? 265 00:14:23,640 --> 00:14:26,320 Speaker 3: Yeah, but when you can create whatever freak show you want, 266 00:14:26,560 --> 00:14:28,800 Speaker 3: I guess a lot of weird kinks out there. 267 00:14:30,760 --> 00:14:33,360 Speaker 1: You said you did the pit chickpee joke. That's right, 268 00:14:33,480 --> 00:14:36,160 Speaker 1: Floodgates right gets back to the garbonzo bean. 269 00:14:36,760 --> 00:14:39,520 Speaker 2: You're just in the run of the mill clown porn. 270 00:14:39,920 --> 00:14:42,280 Speaker 2: I like like S and M. Clown porn. 271 00:14:43,320 --> 00:14:46,440 Speaker 1: Yeah, clown porn. If they're not wearing football jerseys, it 272 00:14:46,520 --> 00:14:49,640 Speaker 1: just doesn't turn me on, you know, or something like that. Yeah, 273 00:14:49,720 --> 00:14:51,480 Speaker 1: and then you know, you talk, you talk it into 274 00:14:51,520 --> 00:14:53,040 Speaker 1: a certain chat GPD and you got it right there 275 00:14:53,080 --> 00:14:56,080 Speaker 1: in front of you, naked times having section football jerseys. 276 00:14:56,520 --> 00:14:59,040 Speaker 2: You meet a girl who shares your passion for that, 277 00:15:00,120 --> 00:15:01,680 Speaker 2: say you put a ring on that. 278 00:15:02,480 --> 00:15:04,000 Speaker 1: I don't care. If you have nothing else in common, 279 00:15:04,040 --> 00:15:09,560 Speaker 1: you might want to stay together. Right, shut down the Internet, 280 00:15:09,800 --> 00:15:14,240 Speaker 1: bring back encyclopedias, hair hair, well, I guess that's it.