1 00:00:10,800 --> 00:00:12,440 Speaker 1: On the cutting room floor today. 2 00:00:12,680 --> 00:00:18,200 Speaker 2: A Greek woman has filed for divorce after chat GPT. 3 00:00:17,280 --> 00:00:20,200 Speaker 1: Reads husband's affair in a coffee cup. 4 00:00:20,280 --> 00:00:20,919 Speaker 3: What's happened? 5 00:00:21,000 --> 00:00:23,720 Speaker 2: So in a bizarre mix of old traditions in cutting 6 00:00:23,800 --> 00:00:26,360 Speaker 2: edge tech, you know, the Greeks, I like, you get 7 00:00:26,400 --> 00:00:28,840 Speaker 2: your coffee in the bottom that reads your future. 8 00:00:30,160 --> 00:00:31,960 Speaker 3: She's future as you'll be going to toilet in half 9 00:00:31,960 --> 00:00:32,240 Speaker 3: an hour. 10 00:00:33,000 --> 00:00:38,480 Speaker 2: So the chat GPT has read her husband's coffee cup 11 00:00:39,440 --> 00:00:46,280 Speaker 2: that she's been married for twelve years, and she got the. 12 00:00:44,640 --> 00:00:50,600 Speaker 4: Coffee ground sort of favorite to chet GPT. And what 13 00:00:50,640 --> 00:00:51,840 Speaker 4: did chet GPT say? 14 00:00:51,960 --> 00:00:52,519 Speaker 1: The result? 15 00:00:52,760 --> 00:00:56,000 Speaker 2: Chat GPT told her that her husband was having an 16 00:00:56,040 --> 00:00:59,360 Speaker 2: affair with a younger woman who was determined to tear 17 00:00:59,400 --> 00:01:00,440 Speaker 2: their family part. 18 00:01:00,760 --> 00:01:03,040 Speaker 3: This from the coffee grinds. This is from the coffee Grinds, 19 00:01:03,040 --> 00:01:05,200 Speaker 3: not from the other photo she uploaded as well. 20 00:01:05,360 --> 00:01:08,920 Speaker 2: No so, but chat GPT, if he was a French guy, 21 00:01:08,959 --> 00:01:09,760 Speaker 2: you just go, we'll do her. 22 00:01:09,840 --> 00:01:11,279 Speaker 1: That's that was going to happen. 23 00:01:11,600 --> 00:01:16,040 Speaker 2: But the Greeks, she's just looked into that and thought, well, boom, 24 00:01:16,160 --> 00:01:17,200 Speaker 2: that's pretty much. 25 00:01:17,400 --> 00:01:18,920 Speaker 3: So she took that as gospel. 26 00:01:19,040 --> 00:01:20,560 Speaker 2: That is gospel. A lot of people do take it 27 00:01:20,600 --> 00:01:23,480 Speaker 2: as gospel. One of my son's mates works for a council. 28 00:01:23,520 --> 00:01:27,800 Speaker 2: I won't say which one, but he had a blinding hangover, 29 00:01:28,040 --> 00:01:30,920 Speaker 2: been out night the night before on the piss and 30 00:01:31,280 --> 00:01:33,600 Speaker 2: knew that he had to do this presentation about local 31 00:01:33,640 --> 00:01:39,840 Speaker 2: infrastructure around the council, and this particular infrastructure pertaining to 32 00:01:39,959 --> 00:01:42,720 Speaker 2: drains and things like that concrete colvert's. 33 00:01:42,560 --> 00:01:43,840 Speaker 1: Very boring sort of stuff. 34 00:01:44,240 --> 00:01:47,960 Speaker 2: Anyway, he used chat gpt to come up with it, 35 00:01:48,480 --> 00:01:51,440 Speaker 2: and he did this presentations just reading Forbadeim what chat 36 00:01:51,520 --> 00:01:54,840 Speaker 2: gpt had written, and the council was so impressed. 37 00:01:54,880 --> 00:01:56,320 Speaker 1: I actually promoted. 38 00:01:55,920 --> 00:02:00,880 Speaker 2: Him, wow to the next level in the untsel, working 39 00:02:00,920 --> 00:02:03,760 Speaker 2: as a public servant. And then he started to feel 40 00:02:03,800 --> 00:02:07,400 Speaker 2: a bit suspicious that people maybe twigged to what had happened, 41 00:02:07,520 --> 00:02:08,960 Speaker 2: were in an actual fact, they hadn't. 42 00:02:09,000 --> 00:02:10,080 Speaker 1: They just thought it was fantastic. 43 00:02:10,120 --> 00:02:12,840 Speaker 2: They thought this young man so insightful that came up 44 00:02:12,960 --> 00:02:15,919 Speaker 2: and knew so much about concrete covids And I have. 45 00:02:15,880 --> 00:02:17,520 Speaker 3: Never even heard the expression before. 46 00:02:17,680 --> 00:02:19,360 Speaker 1: He's got no idea his coffee cup. 47 00:02:19,960 --> 00:02:22,160 Speaker 4: Well, you know what, my friend Anita McGregor is a 48 00:02:22,280 --> 00:02:26,640 Speaker 4: university lecturer and she they have software to detect plagiarism 49 00:02:26,880 --> 00:02:32,160 Speaker 4: and other have software to check chat GPT. And it's 50 00:02:32,200 --> 00:02:34,000 Speaker 4: interesting I read an article about this, might have been 51 00:02:34,040 --> 00:02:36,320 Speaker 4: in Vanity Fair or something, whether these top students were 52 00:02:36,360 --> 00:02:38,359 Speaker 4: saying whether they'd use it or not, and it's there 53 00:02:38,400 --> 00:02:40,520 Speaker 4: for them to use, would they? And some of them 54 00:02:40,520 --> 00:02:43,600 Speaker 4: were saying that, considering you go to university to learn 55 00:02:43,639 --> 00:02:46,440 Speaker 4: a lot of critical thinking, yep, is it a waste 56 00:02:46,520 --> 00:02:48,680 Speaker 4: then to give all your stuff to chat GPT. But 57 00:02:48,680 --> 00:02:52,760 Speaker 4: they're saying that even within a course, there are some 58 00:02:53,639 --> 00:02:54,760 Speaker 4: of the subjects that you. 59 00:02:54,800 --> 00:02:56,079 Speaker 3: Don't really need to be across. 60 00:02:56,120 --> 00:02:58,520 Speaker 4: You have to pass them, but they're not ones that 61 00:02:58,600 --> 00:03:01,400 Speaker 4: matter to you, so they use it for that. So 62 00:03:01,800 --> 00:03:04,160 Speaker 4: they don't fail because of a subject they don't care about, 63 00:03:04,200 --> 00:03:06,440 Speaker 4: but the ones they do care about or use their 64 00:03:06,440 --> 00:03:07,240 Speaker 4: actual brains. 65 00:03:07,360 --> 00:03:09,960 Speaker 1: My youngest is doing AI at university. 66 00:03:10,240 --> 00:03:10,960 Speaker 3: See he's one of. 67 00:03:10,880 --> 00:03:12,480 Speaker 4: The few, not one of the few, but he will 68 00:03:12,480 --> 00:03:15,360 Speaker 4: benefit from it. In our industry, in the creative industry 69 00:03:15,400 --> 00:03:18,680 Speaker 4: where creative writing and advertising, my youngest son wants to 70 00:03:18,720 --> 00:03:21,240 Speaker 4: go into radio, those jobs are all going to disappear. 71 00:03:21,960 --> 00:03:23,919 Speaker 3: You can you know you can get a chat GPT 72 00:03:24,200 --> 00:03:25,880 Speaker 3: to do a podcast at a radio show. 73 00:03:26,040 --> 00:03:29,480 Speaker 1: Yeah, you could do. Yeah, be careful for what you 74 00:03:29,520 --> 00:03:29,920 Speaker 1: wish for. 75 00:03:30,520 --> 00:03:32,679 Speaker 2: How do we even know that we're initially we could 76 00:03:32,720 --> 00:03:35,080 Speaker 2: be chat GPT right now, we'd be better than We've 77 00:03:35,080 --> 00:03:37,880 Speaker 2: said so many words on the radio, some more than other. 78 00:03:39,480 --> 00:03:41,560 Speaker 3: Looking at you, how many stories on your own? 79 00:03:41,600 --> 00:03:41,680 Speaker 1: Is? 80 00:03:41,720 --> 00:03:42,040 Speaker 3: Can you do? 81 00:03:42,840 --> 00:03:44,680 Speaker 2: They could just get all our words, break them up, 82 00:03:44,720 --> 00:03:46,360 Speaker 2: and you've got the AI version of Jones. 83 00:03:46,400 --> 00:03:49,880 Speaker 4: Because initially all of that technology was supposed to take 84 00:03:49,920 --> 00:03:51,920 Speaker 4: the drudgery out of things, but still it's taking the 85 00:03:51,960 --> 00:03:52,920 Speaker 4: creativity out of things. 86 00:03:53,800 --> 00:03:54,680 Speaker 3: Or do my own laundry? 87 00:03:54,720 --> 00:03:59,040 Speaker 2: You want chat GPT writing about concrete covids and not 88 00:03:59,120 --> 00:04:03,360 Speaker 2: doing works. But if we can harness that years ago, 89 00:04:03,440 --> 00:04:07,240 Speaker 2: the Luodites they didn't like the loom, the weaving loom 90 00:04:07,600 --> 00:04:10,640 Speaker 2: in industrial England, and they were against the weaving loom. 91 00:04:10,480 --> 00:04:13,520 Speaker 4: Because because it mechanized, the mechanized the business. 92 00:04:13,520 --> 00:04:16,839 Speaker 2: And the industrial revolution in the seventeen hundreds, which we 93 00:04:16,920 --> 00:04:19,440 Speaker 2: ended up getting made all these textiles all of a sudden, 94 00:04:19,480 --> 00:04:22,800 Speaker 2: all these people that used to like make individual garments 95 00:04:23,040 --> 00:04:24,800 Speaker 2: forever to make all of a sudden, you know, this 96 00:04:24,880 --> 00:04:27,720 Speaker 2: machine that wiped out a whole industry. Chat GPT. I 97 00:04:27,720 --> 00:04:29,479 Speaker 2: don't think it's going to do that I think it'll 98 00:04:29,520 --> 00:04:30,000 Speaker 2: be okay. 99 00:04:30,839 --> 00:04:33,520 Speaker 3: Well tell that to the people who were doing handmade 100 00:04:33,560 --> 00:04:35,800 Speaker 3: rugs they got wiped out. 101 00:04:35,920 --> 00:04:39,800 Speaker 1: Yeah, but someone's still making handmade rugs right now. And 102 00:04:40,000 --> 00:04:42,000 Speaker 1: then you see all those rug places, they're all going 103 00:04:42,040 --> 00:04:42,640 Speaker 1: out of business. 104 00:04:42,880 --> 00:04:43,880 Speaker 3: Well, they're all on sale. 105 00:04:44,480 --> 00:04:46,760 Speaker 4: It's like, what about those Christmas shops that have a 106 00:04:46,800 --> 00:04:48,719 Speaker 4: sale every single day. 107 00:04:48,600 --> 00:04:51,240 Speaker 1: And at Christmas time they go fifty percent off. 108 00:04:51,279 --> 00:04:54,400 Speaker 4: Why wouldn't you pop it up for your big days? 109 00:04:54,839 --> 00:04:56,760 Speaker 3: Make it that's when you're going to get your profit. 110 00:04:56,839 --> 00:05:00,320 Speaker 2: I'd be charging money hand over fist at Christmas East. 111 00:05:01,360 --> 00:05:03,440 Speaker 4: Yeah, but when you in the middle of the year, 112 00:05:03,680 --> 00:05:06,720 Speaker 4: Christmas in July, give it another spy Christmas. But then 113 00:05:06,839 --> 00:05:11,240 Speaker 4: say around you know August, you're just you know, you're 114 00:05:11,279 --> 00:05:13,000 Speaker 4: not going to sell anything then and have your specials 115 00:05:13,000 --> 00:05:15,480 Speaker 4: then Christmas July. 116 00:05:15,760 --> 00:05:16,600 Speaker 3: Prop it right up. 117 00:05:17,040 --> 00:05:19,000 Speaker 2: Look at this chat that we just had, there's no 118 00:05:19,120 --> 00:05:21,240 Speaker 2: way chat GPT could come up with. 119 00:05:21,279 --> 00:05:23,680 Speaker 3: I haven't been in here for a year. I'm completely fake. 120 00:05:24,400 --> 00:05:26,760 Speaker 2: Well, why is there a puddle on the seat that 121 00:05:26,880 --> 00:05:30,960 Speaker 2: you're on To me, you're leaking some cooland hey, hey, hey, okay, 122 00:05:32,720 --> 00:05:38,000 Speaker 2: come back to