1 00:00:00,240 --> 00:00:03,120 Speaker 1: This is the Fitty and Whipper with Kate Richie podcast. 2 00:00:03,360 --> 00:00:05,920 Speaker 1: I feel like we're talking about AI quite a bit 3 00:00:05,960 --> 00:00:07,600 Speaker 1: on the show at the moment, but it is, I mean, 4 00:00:07,600 --> 00:00:09,639 Speaker 1: it's that they're saying that this is just as big. 5 00:00:09,760 --> 00:00:13,360 Speaker 1: The introduction of AI is like the it's like the 6 00:00:13,360 --> 00:00:15,079 Speaker 1: new Industrial Revolution. It is. 7 00:00:15,120 --> 00:00:17,279 Speaker 2: It is believe it's taken over my world and I 8 00:00:17,320 --> 00:00:18,960 Speaker 2: am loving every bit of it. 9 00:00:19,239 --> 00:00:21,159 Speaker 1: Oh it is. And I am reading this off a 10 00:00:21,200 --> 00:00:23,440 Speaker 1: sheet that I've got off Chat GPT at the moment. 11 00:00:23,480 --> 00:00:24,640 Speaker 1: So this is worse. 12 00:00:24,720 --> 00:00:29,240 Speaker 2: This is actually your voice or from guys. It's AI 13 00:00:29,400 --> 00:00:32,360 Speaker 2: generated voice. It's live and it's real. 14 00:00:32,960 --> 00:00:36,000 Speaker 1: But there are so many different sort of apps and 15 00:00:36,040 --> 00:00:39,280 Speaker 1: also software companies that are opening up at the moment 16 00:00:39,280 --> 00:00:43,760 Speaker 1: that are involved with AI. One that goes by the 17 00:00:43,840 --> 00:00:47,479 Speaker 1: name of Natasha. It was an AI app building service 18 00:00:47,479 --> 00:00:51,560 Speaker 1: from a London based company called builder Dot ai Whip. 19 00:00:51,920 --> 00:00:54,440 Speaker 1: It was getting so big it was valid at one 20 00:00:54,440 --> 00:00:58,080 Speaker 1: point five billion dollars and Microsoft got involved Whip, so 21 00:00:58,120 --> 00:01:02,440 Speaker 1: they invested four hundred fifty five million dollars into the 22 00:01:02,480 --> 00:01:04,160 Speaker 1: business and said we want to get on board. You 23 00:01:04,160 --> 00:01:08,639 Speaker 1: guys are on fire. The thing was, though, it turns 24 00:01:08,680 --> 00:01:11,440 Speaker 1: out that all the cash was going towards a workforce 25 00:01:11,600 --> 00:01:16,440 Speaker 1: of over seven hundred Indian engineers in a call center 26 00:01:16,880 --> 00:01:17,840 Speaker 1: rather than AI. 27 00:01:18,360 --> 00:01:20,600 Speaker 2: Okay, so they were doing the work and they didn't 28 00:01:20,640 --> 00:01:22,039 Speaker 2: actually have the AI tech. 29 00:01:22,480 --> 00:01:26,000 Speaker 1: Yes, so not funny they were finding out. So you 30 00:01:26,040 --> 00:01:28,039 Speaker 1: would go on there and this would help you with 31 00:01:28,160 --> 00:01:31,440 Speaker 1: your business and APT building service for your business. So 32 00:01:31,480 --> 00:01:33,560 Speaker 1: you would go on there and I need this, I 33 00:01:33,600 --> 00:01:36,720 Speaker 1: want this is my marketing. I need a logo, and 34 00:01:36,760 --> 00:01:38,800 Speaker 1: they would this is the thing. You're not going to 35 00:01:38,840 --> 00:01:40,920 Speaker 1: be as quick as AI. Now if you've got seven 36 00:01:41,000 --> 00:01:44,440 Speaker 1: hundred people working in one warehouse, these guys are only 37 00:01:44,480 --> 00:01:47,000 Speaker 1: getting eight to fifteen dollars per hour as well. 38 00:01:48,720 --> 00:01:51,000 Speaker 2: The thing you turn it around and make it believable, 39 00:01:51,000 --> 00:01:53,280 Speaker 2: like if you type in I need a logo on 40 00:01:53,320 --> 00:01:56,080 Speaker 2: it with a moose that has a hat on. Yeah, 41 00:01:56,200 --> 00:01:58,280 Speaker 2: how do they turn that around within seconds? 42 00:01:58,440 --> 00:01:58,600 Speaker 1: Well? 43 00:01:58,640 --> 00:01:58,920 Speaker 2: What that? 44 00:01:59,040 --> 00:02:02,240 Speaker 1: No? They were they were delaying code delivery by twelve 45 00:02:02,240 --> 00:02:06,320 Speaker 1: to forty eight hours by saying Natasha is optimizing your request. 46 00:02:07,080 --> 00:02:09,480 Speaker 1: Then they would go away and sit in the room together. 47 00:02:10,400 --> 00:02:13,600 Speaker 2: Up they'd ring another bell. We need another moose with 48 00:02:13,639 --> 00:02:14,040 Speaker 2: a hat on. 49 00:02:15,000 --> 00:02:16,760 Speaker 1: Quick? What are you doing? 50 00:02:17,120 --> 00:02:19,680 Speaker 2: I'm doing a donkey with a bucket on its head. 51 00:02:19,919 --> 00:02:22,760 Speaker 1: You're just there with all your fellow employees going I 52 00:02:22,800 --> 00:02:26,200 Speaker 1: think AI was quick. Why is it taking two days? 53 00:02:26,480 --> 00:02:27,040 Speaker 2: It must be good. 54 00:02:27,080 --> 00:02:28,000 Speaker 1: That must be really good. 55 00:02:28,040 --> 00:02:28,760 Speaker 2: When they come. 56 00:02:28,600 --> 00:02:32,960 Speaker 1: Back, Natasha, you're still there. So but these poor workers, 57 00:02:33,000 --> 00:02:35,320 Speaker 1: this is the thing now, these poor workers that they've 58 00:02:35,600 --> 00:02:39,200 Speaker 1: they faced their visas being taken away from the blacklisting. 59 00:02:40,200 --> 00:02:43,919 Speaker 1: They were forced to use fake Western names in client emails. 60 00:02:44,600 --> 00:02:46,680 Speaker 1: So they were all just sitting there, all at their 61 00:02:46,720 --> 00:02:50,040 Speaker 1: computer going, guys, I got another one. 62 00:02:50,440 --> 00:02:54,280 Speaker 2: Yeah, we need a gorilla eating a birthday cake sitting 63 00:02:54,280 --> 00:02:55,320 Speaker 2: on top of a tower. 64 00:02:55,919 --> 00:02:59,480 Speaker 1: It's a fishing chip shop in London. They need a logo. 65 00:03:00,080 --> 00:03:02,799 Speaker 2: I want to see the fish swimming through the shop. 66 00:03:03,639 --> 00:03:05,720 Speaker 1: Make it happen, Oh theo. 67 00:03:06,280 --> 00:03:07,400 Speaker 2: Do you know what? Can I tell you what I 68 00:03:07,440 --> 00:03:09,160 Speaker 2: did the other day? And it was a tip that 69 00:03:09,200 --> 00:03:12,480 Speaker 2: we got on this show and it actually worked. I 70 00:03:12,480 --> 00:03:15,240 Speaker 2: felt like a bit of a scammer. I was buying 71 00:03:15,240 --> 00:03:17,680 Speaker 2: something online and I was at the checkout stage ready 72 00:03:17,680 --> 00:03:18,920 Speaker 2: to pay, and it said coupon. 73 00:03:19,040 --> 00:03:20,880 Speaker 1: You know when you put in your coupon, Yeah, you 74 00:03:20,880 --> 00:03:22,120 Speaker 1: don't have a coupon code. 75 00:03:22,360 --> 00:03:24,600 Speaker 2: No. But then I went to touch GPT because we 76 00:03:24,680 --> 00:03:26,840 Speaker 2: got that tip off on the show, and I said, 77 00:03:26,880 --> 00:03:30,240 Speaker 2: please search this website copy paste for any coupons that 78 00:03:30,280 --> 00:03:33,160 Speaker 2: could be attached to the website. They filed back about 79 00:03:33,240 --> 00:03:33,959 Speaker 2: five of them. 80 00:03:34,400 --> 00:03:34,480 Speaker 1: What. 81 00:03:35,040 --> 00:03:37,920 Speaker 2: Yeah, there's always a welcome work, there's always a welcome 82 00:03:38,040 --> 00:03:41,560 Speaker 2: ten to take ten percent off, there's always a thanks 83 00:03:41,600 --> 00:03:44,680 Speaker 2: fifteen or something like that. Yeah, and I got fifteen 84 00:03:44,720 --> 00:03:48,400 Speaker 2: percent off me la boo boot Oh you know what 85 00:03:48,480 --> 00:03:52,520 Speaker 2: I mean. That is unbelievable easey savings. Guys, you got 86 00:03:52,560 --> 00:03:53,800 Speaker 2: to take them where you can find um. 87 00:03:54,000 --> 00:03:57,240 Speaker 1: It's Whipper with Kate Ritchie is a Nova podcast walk 88 00:03:57,280 --> 00:03:58,280 Speaker 1: great shows like this. 89 00:03:58,600 --> 00:04:02,040 Speaker 2: Download the Nova Player via the App Store or Google Play. 90 00:04:02,200 --> 00:04:03,120 Speaker 1: The Ova player