1 00:00:00,240 --> 00:00:03,120 Speaker 1: This is the Fitting and Whip with Kate Richie podcast. 2 00:00:03,400 --> 00:00:06,960 Speaker 2: Elon Musk, I mean, even though he had that episode 3 00:00:07,000 --> 00:00:12,480 Speaker 2: there with Trump and I think I think even he 4 00:00:12,520 --> 00:00:16,279 Speaker 2: looks back and go what and it probably affected his 5 00:00:16,400 --> 00:00:20,880 Speaker 2: tesla who cares? The guy is like, we're talking multi 6 00:00:20,920 --> 00:00:24,120 Speaker 2: billionaire now, like where could he be the first trillion air? 7 00:00:24,200 --> 00:00:25,400 Speaker 2: He's close to it? Isn't he? 8 00:00:25,760 --> 00:00:28,080 Speaker 1: I don't know who was it the other day that 9 00:00:28,160 --> 00:00:29,120 Speaker 1: jumped up even. 10 00:00:28,960 --> 00:00:35,080 Speaker 2: More video the guy that the aim anyway? You know what, 11 00:00:35,120 --> 00:00:37,479 Speaker 2: Elon Musk, I'm not a big fan, but you do 12 00:00:37,560 --> 00:00:40,519 Speaker 2: have to listen to this man because he can foresee 13 00:00:40,680 --> 00:00:43,199 Speaker 2: what technology is going to do for us in the future. 14 00:00:43,680 --> 00:00:47,720 Speaker 2: It's unbelievable. He sat down with Joe Rogan again they're 15 00:00:47,800 --> 00:00:50,879 Speaker 2: very good friends, and he was talking about our phones 16 00:00:50,960 --> 00:00:54,680 Speaker 2: and AI and what freaked me out about this even 17 00:00:54,760 --> 00:00:58,560 Speaker 2: more is how quickly this could happen. But he thinks 18 00:00:58,680 --> 00:01:02,000 Speaker 2: that we won't have Now I'm trying to I was 19 00:01:02,000 --> 00:01:04,000 Speaker 2: trying to work out, I'm going to get you to 20 00:01:04,040 --> 00:01:07,520 Speaker 2: listen to this what will be using because there still 21 00:01:07,560 --> 00:01:11,080 Speaker 2: has to be a screen an audio that we listen 22 00:01:11,200 --> 00:01:15,120 Speaker 2: to whip, but have a listen to what he predicts 23 00:01:15,319 --> 00:01:16,800 Speaker 2: happens in the next few years. 24 00:01:17,000 --> 00:01:20,480 Speaker 3: There won't be operating systems. They won't be apps. In 25 00:01:20,520 --> 00:01:22,919 Speaker 3: the future, they will be operating systems or apps. It'll 26 00:01:22,959 --> 00:01:25,920 Speaker 3: just be You've got a device that is there for 27 00:01:26,040 --> 00:01:28,759 Speaker 3: the screen and audio and to put as much AI 28 00:01:28,959 --> 00:01:32,160 Speaker 3: on the device as possible so as to minimize the 29 00:01:32,160 --> 00:01:35,120 Speaker 3: amount of bandwidth that's needed between your edge. No device 30 00:01:35,600 --> 00:01:37,920 Speaker 3: fulling known as the phone and the servers. 31 00:01:38,280 --> 00:01:41,200 Speaker 2: There's no apps. What will people you like? 32 00:01:41,319 --> 00:01:45,679 Speaker 1: Will X still exist? Will there be email platforms? Or 33 00:01:45,720 --> 00:01:48,360 Speaker 1: will you get everything through AI? You'll get everything through 34 00:01:48,400 --> 00:01:50,320 Speaker 1: it will be the benefit of that as opposed to 35 00:01:50,440 --> 00:01:51,720 Speaker 1: having individual apps. 36 00:01:51,840 --> 00:01:54,120 Speaker 3: Whatever you can think of, or really whatever the air 37 00:01:54,200 --> 00:01:56,680 Speaker 3: can anticipate you might want, it'll show you. That's my 38 00:01:56,760 --> 00:01:58,120 Speaker 3: prediction for where things end up. 39 00:01:58,240 --> 00:02:00,080 Speaker 1: What kind of timeframe were we're talking about here, I 40 00:02:00,080 --> 00:02:00,360 Speaker 1: don't know. 41 00:02:00,400 --> 00:02:02,560 Speaker 3: That's probably five or six year or something like that. 42 00:02:02,560 --> 00:02:06,720 Speaker 2: That makes sense, so we don't even have to really 43 00:02:06,840 --> 00:02:07,480 Speaker 2: think in the. 44 00:02:07,520 --> 00:02:10,160 Speaker 1: End, Well, you do, but when you enter whatever you're 45 00:02:10,200 --> 00:02:12,760 Speaker 1: interested in, the AI will understand what you're attempting to do. 46 00:02:13,680 --> 00:02:16,959 Speaker 2: But then it'll be predicting stuff for you all the time, 47 00:02:17,400 --> 00:02:19,600 Speaker 2: so you're not using your brain as much. 48 00:02:19,760 --> 00:02:21,800 Speaker 1: This is the thing we were talking about this yesterday 49 00:02:21,840 --> 00:02:24,359 Speaker 1: with the new version of chutch ibt. Sometimes it dismisses 50 00:02:24,400 --> 00:02:26,040 Speaker 1: and doesn't give you what you want. But what it 51 00:02:26,120 --> 00:02:31,080 Speaker 1: does do is it prompts your thinking quite accurately and 52 00:02:31,160 --> 00:02:33,679 Speaker 1: even better than it did before, to suggest where you're 53 00:02:33,720 --> 00:02:36,160 Speaker 1: going or what it can offer next to help you. 54 00:02:36,720 --> 00:02:38,720 Speaker 2: See, Like, do you know what's freaking me out at 55 00:02:38,720 --> 00:02:40,240 Speaker 2: the moment? Uber? 56 00:02:40,360 --> 00:02:40,600 Speaker 3: Right? 57 00:02:41,440 --> 00:02:46,639 Speaker 2: When I fly into a airport around Australia. Uber, when 58 00:02:46,639 --> 00:02:50,080 Speaker 2: I go on to Uber, it knows where I've been 59 00:02:50,240 --> 00:02:52,880 Speaker 2: before at that airport, so it'll go, do you want 60 00:02:52,880 --> 00:02:53,960 Speaker 2: to go back to this hotel? 61 00:02:54,120 --> 00:02:54,400 Speaker 3: Yep? 62 00:02:54,800 --> 00:02:57,280 Speaker 2: That's what's starting to freak me out. So it's already 63 00:02:58,000 --> 00:03:01,919 Speaker 2: it's remembering everything that you've done, your schedule, and then 64 00:03:01,960 --> 00:03:04,000 Speaker 2: it just makes it easy for you when you get there, 65 00:03:04,040 --> 00:03:05,440 Speaker 2: it just goes, do you just want to go back 66 00:03:05,440 --> 00:03:05,919 Speaker 2: here again? 67 00:03:06,480 --> 00:03:09,160 Speaker 1: You're not going to believe it. Your brain might not 68 00:03:09,240 --> 00:03:10,320 Speaker 1: be needed in the future. 69 00:03:10,320 --> 00:03:14,480 Speaker 2: Fits what's shock this is, this is what scares me. 70 00:03:15,040 --> 00:03:16,880 Speaker 1: Like if I was if I was able to get 71 00:03:16,880 --> 00:03:19,799 Speaker 1: off a plane and it went and it was Uber going, oh, 72 00:03:20,080 --> 00:03:21,520 Speaker 1: I think you probably need to do a we and 73 00:03:21,520 --> 00:03:24,079 Speaker 1: then you're gone by a packet of mints and you'll 74 00:03:24,080 --> 00:03:27,280 Speaker 1: get an espresso and then I'll drop you home. 75 00:03:27,560 --> 00:03:31,400 Speaker 2: Yeah, but we'll get to the point where you've arrived 76 00:03:31,440 --> 00:03:35,720 Speaker 2: at Sydney Airport. I've already ordered you a latte one sugar, yep, 77 00:03:36,000 --> 00:03:38,960 Speaker 2: your favorite, right, so go pick that up first, then 78 00:03:39,040 --> 00:03:42,320 Speaker 2: go do a Wii and your uber arrives in five minutes. 79 00:03:42,400 --> 00:03:43,880 Speaker 1: Wow, you're told what to do? 80 00:03:44,280 --> 00:03:44,680 Speaker 3: Is that what? 81 00:03:44,920 --> 00:03:45,920 Speaker 2: That's what will be? 82 00:03:46,000 --> 00:03:48,240 Speaker 1: It's sent a radio idea and a funny meme to 83 00:03:48,240 --> 00:03:53,440 Speaker 1: Tommy already automatically, You've already sent a message saying just landed, 84 00:03:53,560 --> 00:03:56,000 Speaker 1: love you to your wife and can you please feed 85 00:03:56,040 --> 00:03:56,360 Speaker 1: the dog. 86 00:03:56,640 --> 00:04:00,320 Speaker 2: That's amazing, you know what? So then we that's amazing. 87 00:04:00,360 --> 00:04:03,480 Speaker 2: So you'll never need a personal assistant again who sits 88 00:04:03,520 --> 00:04:05,440 Speaker 2: down and takes your lunch order every day and go. 89 00:04:07,800 --> 00:04:10,520 Speaker 1: She was extremely efficient, poor thing. Well, she had an 90 00:04:10,520 --> 00:04:16,760 Speaker 1: accent overseas. She was colorI counting and helping at the temple. 91 00:04:18,000 --> 00:04:19,479 Speaker 3: She tried it at a couple of times. 92 00:04:19,480 --> 00:04:21,000 Speaker 2: Here ride a couple of bikes. 93 00:04:20,720 --> 00:04:25,359 Speaker 1: Into a wall of let's put too much cheese in 94 00:04:25,360 --> 00:04:27,960 Speaker 1: the slice. Its Whipper with Kate Ritchie is a Nova 95 00:04:28,000 --> 00:04:31,720 Speaker 1: podcast to walk great shows like this. Download the Nova Player, 96 00:04:31,880 --> 00:04:35,200 Speaker 1: find the app store or Google Play. 97 00:04:33,800 --> 00:04:33,960 Speaker 3: In the