WEBVTT 00:00:00.730 --> 00:00:02.940 My prediction is this. I'll go out on a limb. 00:00:03.090 --> 00:00:08.320 I'll say in five years I will not check my inbox anymore. 00:00:08.764 --> 00:00:13.924 Don't think of AI as an Einstein. Think of it as what would you do if you would 00:00:13.964 --> 00:00:15.614 have 100 assistants. 00:00:16.191 --> 00:00:17.921 Use the machine to test the hypothesis. 00:00:18.211 --> 00:00:20.741 Never allow the machine to give you the hypothesis. 00:00:26.700 --> 00:00:28.700 You are on mute! 00:00:28.800 --> 00:00:31.700 Where AI is taking us, and how to prepare. 00:00:32.700 --> 00:00:35.300 Episode 1: Think first. 00:00:36.480 --> 00:00:41.090 Hello everyone, and welcome to the first episode of You're On Mute. 00:00:41.800 --> 00:00:47.640 We're here together with Nicklas a former colleague from Google, and we have 00:00:47.680 --> 00:00:53.790 been discussing a lot lately where the world is heading and what we are seeing. 00:00:53.960 --> 00:00:57.560 And we get these questions all the time as well, is that so how should we be 00:00:57.600 --> 00:01:00.640 preparing? What- how should board work look like? 00:01:00.680 --> 00:01:05.290 How should education look like? How do you use these tools? 00:01:05.660 --> 00:01:10.070 And this is exactly the reason why we are here right now to discuss with you 00:01:10.220 --> 00:01:13.210 what we can do. Great to see you, Nicklas. 00:01:13.600 --> 00:01:14.060 And great to be here- 00:01:14.100 --> 00:01:14.760 How was your morning? 00:01:14.800 --> 00:01:18.480 Petri. My morning was really good. I'm on an island in the archipelago, and 00:01:18.520 --> 00:01:23.730 it's drizzling, but it's a beautiful autumn morning, so I really enjoyed it. 00:01:25.180 --> 00:01:27.310 What did AI do to you this morning? 00:01:27.880 --> 00:01:30.210 do for me, I hope. So- 00:01:30.880 --> 00:01:33.470 what it did, what it did do to me, I don't know. 00:01:33.620 --> 00:01:36.380 But no, so what it did for me this morning is several things, right? 00:01:36.420 --> 00:01:42.040 One is that I nowadays read the morning news through an, a news 00:01:42.080 --> 00:01:45.560 aggregator that I built myself. So the first thing I do in the morning, I go to 00:01:45.600 --> 00:01:49.380 this news aggregator. I check what the news is, what the top news is in the 00:01:49.420 --> 00:01:52.490 categories I care about, AI, politics, et cetera. 00:01:52.920 --> 00:01:57.170 so that's primarily how I encountered it this morning. 00:01:57.260 --> 00:02:02.780 And then I, and I also had it remind me what we had agreed we would discuss on 00:02:02.820 --> 00:02:07.420 this podcast. So there you go. which it which it happily did because it has 00:02:07.460 --> 00:02:10.560 access to my calendar and email and meeting notes and so on. 00:02:10.600 --> 00:02:13.920 so I s- I would say that's my morning AI. 00:02:13.960 --> 00:02:14.860 What about yours? 00:02:15.860 --> 00:02:22.160 Well, my morning AI routine has become to check out what it 00:02:22.200 --> 00:02:27.200 looked into my inbox and then decides on where, what to do a reply to, wh- what 00:02:27.240 --> 00:02:30.310 not to reply to, and also write drafts. 00:02:30.660 --> 00:02:34.070 I have not let it answer directly itself. 00:02:34.360 --> 00:02:39.270 So I use it as an assistant, as it should be, but it writes for me 00:02:40.060 --> 00:02:44.320 replies, and then I look through them and may might do some small changes, and 00:02:44.360 --> 00:02:49.690 then I'm ready to go. I also used as a news aggregator. 00:02:50.380 --> 00:02:54.380 work- been working in the, in the defense industry, so I have no clue of 00:02:54.420 --> 00:02:58.920 defense, so it's been f- amazing for us, for me to be able to have my own news 00:02:58.960 --> 00:03:02.070 aggregator to look at what's going on in that field. 00:03:02.560 --> 00:03:05.100 so tho- those are those things that really... 00:03:05.140 --> 00:03:11.180 Plus, I have to say that I used AI to optimize this beautiful setup that 00:03:11.220 --> 00:03:12.130 I have here with- 00:03:12.200 --> 00:03:12.480 It is- 00:03:12.680 --> 00:03:14.640 it is quite stunning. It's quite stunning. 00:03:14.680 --> 00:03:15.580 Very well done. 00:03:16.160 --> 00:03:20.600 I did, I did a few alterations, and it said, Oh, you know, you should use more 00:03:20.640 --> 00:03:24.140 light here and more light there, and don't let light come in through the window, 00:03:24.180 --> 00:03:28.600 and so on. again, it shows what all kind of stuff you can, you can do with this. 00:03:28.640 --> 00:03:31.620 I should probably learn from that. I feel worried about my background now. 00:03:31.660 --> 00:03:35.480 but I want to catch something you said that I think is really interesting. 00:03:35.520 --> 00:03:39.000 it's the email thing because I've started to do the same. 00:03:39.040 --> 00:03:44.710 And I, I've started to sort of ask myself a question, which is I wonder how much 00:03:44.840 --> 00:03:50.400 longer we will actually have email inboxes for humans, and when email 00:03:50.440 --> 00:03:55.040 inboxes should be for agents instead. Because the idea of looking into your 00:03:55.080 --> 00:03:58.880 email inbox with all of the noise and all of the different things that come in, 00:03:58.920 --> 00:04:03.240 some important, some not, and for me to take on that filtering cost and that 00:04:03.280 --> 00:04:05.670 filtering burden makes absolutely no sense. 00:04:05.960 --> 00:04:06.220 And I- 00:04:06.460 --> 00:04:11.640 and I really do believe, I mean, I hear you about only having a draft because 00:04:11.680 --> 00:04:15.840 you don't want it to send yet, but, I mean, for how much longer does it have to 00:04:15.880 --> 00:04:20.520 draft really well for you to say, Well, you know, I actually am quite fine with 00:04:20.560 --> 00:04:24.100 it responding for me as well? My prediction is this. 00:04:24.140 --> 00:04:25.190 I'll go out on a limb. 00:04:25.340 --> 00:04:30.570 I'll say in five years I will not check my inbox anymore. 00:04:30.680 --> 00:04:35.300 I won't open Gmail anymore. I will be doing all of my correspondence, whether 00:04:35.340 --> 00:04:39.830 it's, you know, email or any other correspondence that I do, through an agent. 00:04:39.880 --> 00:04:44.300 And I'm so looking forward to it. I think we might be closer to the end of email 00:04:44.340 --> 00:04:47.150 than we realize, and what a glorious thing that would be. 00:04:47.860 --> 00:04:53.219 that's a good prediction. And I have to say that also now I still go into my 00:04:53.259 --> 00:04:55.690 inbox then to glance through that was it correct. 00:04:56.540 --> 00:05:01.720 And until now the only mistakes that I have found was that it had obviously acc- 00:05:01.760 --> 00:05:06.040 access to my calendar too, and if I, if I put into calendar that there's an 00:05:06.080 --> 00:05:11.430 event that takes a full day, it thinks that day is free. 00:05:12.360 --> 00:05:16.090 so if someone comes in and said, Oh, could we have lunch during that day? 00:05:16.580 --> 00:05:19.760 it will tell, Oh, yeah, you have-- you don't have anything in, on that day, 00:05:19.800 --> 00:05:24.940 because I had put it into the event. So you need what I learned is that even if 00:05:24.980 --> 00:05:30.940 it's a day, a full day event, you need to block the full day in order for 00:05:30.980 --> 00:05:34.540 it to understand that yes you are actually busy. 00:05:34.580 --> 00:05:39.540 But I, I'm completely with you. I actually heard an interesting statistic a few 00:05:39.580 --> 00:05:44.560 days ago that said that already today two-thirds of internet traffic would be 00:05:44.600 --> 00:05:45.590 done by bots. 00:05:46.160 --> 00:05:46.500 Yeah. 00:05:46.540 --> 00:05:47.920 That makes total sense to me. And- 00:05:47.960 --> 00:05:52.310 So if you have a website today, who are you optimizing for? 00:05:52.580 --> 00:05:55.830 Are you optimizing for humans, or are you optimizing for bots? 00:05:56.260 --> 00:05:56.500 Oh, I would- 00:05:56.540 --> 00:05:56.980 And then if you go to Google's SEO- 00:05:57.020 --> 00:05:59.040 I would, I would certainly optimize for bots. 00:05:59.080 --> 00:05:59.340 Yes. 00:05:59.380 --> 00:06:03.580 Yeah. But if you go to Google's SEO rules they say, oh, you should own- or, you 00:06:03.620 --> 00:06:05.530 know, you should really optimize it for the humans. 00:06:05.760 --> 00:06:10.804 But if it's only a third of the traffic- I think that's a fascinating 00:06:10.844 --> 00:06:11.744 development. 00:06:11.904 --> 00:06:14.884 It is. And I, and I think there's more to that that's really interesting to dig 00:06:14.924 --> 00:06:19.184 into as well because as the web transitions into an agent web rather than a 00:06:19.224 --> 00:06:23.184 human web there is so much else that should happen as well with services. 00:06:23.224 --> 00:06:27.144 So if you're a service today and you don't have an API that agents can interact 00:06:27.184 --> 00:06:32.464 with or like a MCP server or something like that, I think that's a conscious 00:06:32.504 --> 00:06:36.164 choice because you're afraid of being out-competed by the agents or you're 00:06:36.204 --> 00:06:40.354 afraid of becoming just a resource under the agent layer. 00:06:40.783 --> 00:06:46.704 And I don't think that works because I think we, I know I want these services to 00:06:46.744 --> 00:06:47.644 just connect. 00:06:47.944 --> 00:06:51.344 The reason I, for example, have started to use Notion a lot more is that Notion 00:06:51.384 --> 00:06:54.514 has a really good set of agent integrations. 00:06:54.964 --> 00:07:00.974 So you know, I have- I do meeting transcripts, I do different kinds of updates, 00:07:01.224 --> 00:07:05.204 and Notion essentially works as an extended memory for all of the projects that 00:07:05.244 --> 00:07:08.334 I'm involved with. And my agents then just consult Notion. 00:07:08.704 --> 00:07:12.844 They update it. There's a work journal for every single project, so I can go in, 00:07:12.884 --> 00:07:18.064 see what has been done where. and that kind of structure really depends on the 00:07:18.104 --> 00:07:22.994 idea that we have services that are agent first. 00:07:23.544 --> 00:07:27.224 And I think if you're not agent first because you're a little bit afraid that 00:07:27.264 --> 00:07:30.444 the agents will come between you and the customer, you probably need to find 00:07:30.484 --> 00:07:33.094 another way to make sure the customers love what you're doing. 00:07:34.084 --> 00:07:34.984 I love it. 00:07:35.764 --> 00:07:38.194 Th- this really reminds me all the time is that 00:07:39.504 --> 00:07:43.604 well, I can tell our viewers now that also that you worked for DeepMind, and one 00:07:43.644 --> 00:07:48.944 of the DeepMind engineers once told me that, Petri, don't think of AI as an 00:07:48.984 --> 00:07:53.734 Einstein. Think of it as what would you do if you would have 100 assistants. 00:07:54.364 --> 00:07:58.504 And that has really stuck with me in the sense that, yes, if I would have those 00:07:58.544 --> 00:08:02.734 assistants, will I let them run immediately free? 00:08:02.824 --> 00:08:06.804 No. I would tell them exact- you need to tell them, You do this, and that, and 00:08:06.844 --> 00:08:09.394 when you've done this, you come and tell, show me what you've done. 00:08:09.804 --> 00:08:12.674 And then you correct and then say, Oh, can you do this, and that? 00:08:12.904 --> 00:08:14.254 And I think that, 00:08:15.644 --> 00:08:20.964 let's call it a metaphor I think is, has been s- stuck with me, and that's the 00:08:21.004 --> 00:08:24.644 way I've been looking into most of the stuff I'm doing is that. 00:08:24.684 --> 00:08:30.654 So what could my 100 assistants do for me while I'm 00:08:31.224 --> 00:08:32.124 you know, 00:08:32.704 --> 00:08:34.114 r- raking leaves in the garden? 00:08:34.684 --> 00:08:39.084 Yes. and reading and doing all those things that sort of make us smarter. 00:08:39.124 --> 00:08:42.464 But... And I think it's interesting because I agree with that although I think 00:08:42.504 --> 00:08:46.184 there's a, there's a twist to it, which is that if you had 100 assistants, you 00:08:46.224 --> 00:08:48.024 would appoint one of them head assistant. 00:08:48.064 --> 00:08:51.184 And then you would say to that person, Please take care of the rest so you can 00:08:51.224 --> 00:08:53.904 organize them. And that's essentially orchestration, right? 00:08:53.944 --> 00:08:55.034 Agent orchestration. 00:08:55.364 --> 00:08:55.984 Exactly. 00:08:56.024 --> 00:09:00.264 and I think we will see these orchestration patterns emerge that are super 00:09:00.304 --> 00:09:03.224 interesting, and people will adopt different orchestration patterns. 00:09:03.264 --> 00:09:06.984 You can have a main agent that you interact with and then delegates to 00:09:07.024 --> 00:09:10.724 sub-agents. You can have a main agent you interact with sub-agents, and then you 00:09:10.764 --> 00:09:15.004 can have a guy who checks it. Currently, you're the guy who checks the email 00:09:15.044 --> 00:09:16.574 inbox to see nothing was missed. 00:09:16.944 --> 00:09:18.274 You could have an agent do that. 00:09:18.564 --> 00:09:21.884 Or you're the one who reads the draft. But if you have one person drafting, one 00:09:21.924 --> 00:09:23.804 reading, and a third saying, Yeah, you're right. 00:09:23.844 --> 00:09:27.454 We should change this, then you start to sort of build these little teams. 00:09:27.504 --> 00:09:30.844 And I know Ethan Mollick, who writes about this beautifully and is a really 00:09:30.884 --> 00:09:35.464 smart professor of management, he said that the key skill in the future for AI 00:09:35.504 --> 00:09:38.654 is not going to be coding or computer science, it's going to be management. 00:09:39.124 --> 00:09:40.754 You have to be really good at management. 00:09:40.984 --> 00:09:42.784 How do you delegate? What do you not delegate? 00:09:42.844 --> 00:09:46.434 How do you set up teams? How do you make sure teams have clear goals? 00:09:46.704 --> 00:09:49.344 The kinds of things that you've been a manager for a long time, or the kinds of 00:09:49.384 --> 00:09:54.504 things that we, that we learned as managers are now actually the core skills for 00:09:54.544 --> 00:09:57.094 interacting with AI, which is kind of fascinating. 00:09:57.564 --> 00:10:02.934 It is. And if you take that argument or that thinking even further, 00:10:03.564 --> 00:10:08.394 traditionally in companies, even your salary bands have been more or less 00:10:08.504 --> 00:10:13.324 defined by how big is your team. And then the smartest one has realized that, 00:10:13.364 --> 00:10:17.994 oh, you know, I should, I should get the bigger team, and I get paid better and 00:10:18.504 --> 00:10:23.164 and so on. I might higher in, so to say, in the, in the hierarchy of these 00:10:23.204 --> 00:10:28.454 companies. So what if... And we will move into these hybrid teams. 00:10:28.883 --> 00:10:34.464 I will have those 100 assistants on my hybrid team, and I might have two other 00:10:34.504 --> 00:10:36.774 people there doing things. 00:10:37.944 --> 00:10:40.144 is that a big team or a small team going forward? 00:10:40.184 --> 00:10:40.444 Exactly. 00:10:40.484 --> 00:10:45.284 And the question is that maybe we should be really looking into that how can we 00:10:45.324 --> 00:10:48.234 build those hybrid teams in the future. 00:10:48.384 --> 00:10:49.084 And measure on outcomes. 00:10:49.124 --> 00:10:50.764 By the way, leadership will change also completely. 00:10:50.804 --> 00:10:53.884 Oh, it will. I- it certainly will. I mean, and measure on outcomes, I think, is 00:10:53.924 --> 00:10:57.804 the thing you have to do, and not look at, for example, you know, how many 00:10:57.844 --> 00:11:01.294 people do you have in your team, which I agree traditionally has been the case. 00:11:01.484 --> 00:11:06.344 Because now you know, a single person with a really good agent setup with 00:11:06.384 --> 00:11:11.314 excellent data can outproduce a 200, 300, 400 person team. 00:11:11.584 --> 00:11:14.664 And that's also why we're seeing the restructuring in many of the tech companies 00:11:14.704 --> 00:11:15.624 now where, you know- 00:11:15.744 --> 00:11:18.944 the vast restructuring that Microsoft is doing, et cetera. 00:11:18.984 --> 00:11:22.944 so coming back to this notion of what we do, I think one of the core things that 00:11:22.984 --> 00:11:27.594 we need to learn is that we need to learn how to think about this in a more 00:11:28.644 --> 00:11:29.614 traditional way. 00:11:32.664 --> 00:11:33.564 Meaning? 00:11:34.444 --> 00:11:35.894 Thinking a traditional way? What do you mean? 00:11:36.464 --> 00:11:40.164 So what I... Yeah, no, what I mean, we need to think about this in a way where 00:11:40.204 --> 00:11:42.214 we sort of go back to the basics- 00:11:42.484 --> 00:11:42.804 Mm-hmm 00:11:42.844 --> 00:11:47.704 and ask what do we do? What are the kinds of things that we produce? 00:11:47.744 --> 00:11:50.454 What are the kinds of services that we offer, for example? 00:11:50.784 --> 00:11:54.954 So that's largely what I was referring to. 00:11:55.364 --> 00:11:56.814 I have a question for you, Nicklas. 00:11:58.504 --> 00:12:04.504 Is AI a transformational technology, like for example digital 00:12:04.544 --> 00:12:06.774 was, or is it just a way to 00:12:08.664 --> 00:12:11.234 make us as individuals much more efficient? 00:12:13.512 --> 00:12:17.372 it's a good question because when we say AI, we typically take all of the 00:12:17.412 --> 00:12:21.152 different technologies that fall under that particular term, and we treat them 00:12:21.192 --> 00:12:25.712 the same. And I think there is some AI that is really good at sorting, for 00:12:25.752 --> 00:12:28.952 example. so you have spam, for example. 00:12:28.992 --> 00:12:31.852 Spam filters were a kind of AI, and they were really good at what they were 00:12:31.892 --> 00:12:35.912 doing. But if you think about AI as extended cognition, as us being able to 00:12:35.952 --> 00:12:40.512 think more differently, deeper, and m- you know, across more domains, then 00:12:40.552 --> 00:12:42.802 certainly it is transformational in a sense. 00:12:43.492 --> 00:12:49.452 for 'Cause to me, the technology that we are now building is adding cognition to 00:12:49.492 --> 00:12:52.792 the world, adding thinking to the world, and I think- that's something that's 00:12:52.832 --> 00:12:56.152 radically different from adding a new way of connecting or communicating or 00:12:56.192 --> 00:12:59.912 storing information. So you could, you could almost phrase this in saying that 00:12:59.952 --> 00:13:03.412 we're sort of, we have understood ourselves for the metaphor of the information 00:13:03.452 --> 00:13:08.292 society for a long time. Now, if you transition that into the new metaphor, the 00:13:08.332 --> 00:13:12.512 intelligence society, you suddenly realize that there's a huge difference 00:13:12.552 --> 00:13:15.912 between information and Intelligence is action. 00:13:15.952 --> 00:13:18.082 Intelligence is in different ways 00:13:19.152 --> 00:13:24.812 sort of reframing the world. And information is capturing the world and 00:13:24.852 --> 00:13:27.592 trying to describe or represent it in different ways. 00:13:27.632 --> 00:13:31.272 so I would, I would probably fall on the side of transformational when you look 00:13:31.312 --> 00:13:35.512 at the entire technological architecture we're building, because we're building 00:13:35.552 --> 00:13:39.362 something in the world that can think with us, and sometimes without us. 00:13:39.872 --> 00:13:40.412 What do you think? 00:13:40.452 --> 00:13:43.292 the reason why I'm asking this a little bit also is that obviously, you know, 00:13:43.332 --> 00:13:48.712 it's like we both remember the times when, so to say, in the, in the beginning 00:13:48.752 --> 00:13:53.502 of digital . and then s- suddenly we started seeing 00:13:54.312 --> 00:14:00.212 e-commerce, we started seeing digital banks that had no branches any longer, 00:14:00.252 --> 00:14:06.102 and so on and so forth. so it more or less built complete new ways of 00:14:07.372 --> 00:14:12.632 new ty- type of enterprises, new type of companies, new type new ways of serving 00:14:12.672 --> 00:14:17.942 your clients. and I don't know if we've seen an AI bank yet. 00:14:18.332 --> 00:14:24.432 We might have seen some insurance companies who can really automate the 00:14:24.472 --> 00:14:29.972 claims process and so on. but so the, so it really goes back to yes, I, I'm 00:14:30.012 --> 00:14:33.552 completely with you that it will, it's, and it's already transforming the way I 00:14:33.592 --> 00:14:37.922 work, and it transforming the way individuals are working. 00:14:38.712 --> 00:14:39.612 But is it 00:14:40.672 --> 00:14:46.542 is it transforming companies and the way companies work, and, 00:14:46.612 --> 00:14:49.662 or is it just so that we are so early in the development that we haven't- 00:14:50.092 --> 00:14:50.372 seen it yet? 00:14:50.412 --> 00:14:52.152 Yeah, no, I think, I mean, if you look at where it is- 00:14:52.192 --> 00:14:53.112 and the reason also I'm asking this a little bit- 00:14:53.232 --> 00:14:57.712 is that I see that those companies that in the early days of digital did not 00:14:57.752 --> 00:14:58.922 jump on the bandwagon, 00:15:00.112 --> 00:15:05.632 they got left behind. we look at some of those department stores who said, Oh, 00:15:05.672 --> 00:15:09.292 we will be waiting until, you know, I don't know what they were waiting for. 00:15:09.332 --> 00:15:13.272 They're still today waiting for it. and the Amazons and, of this world have 00:15:13.312 --> 00:15:18.732 passed them. and I see here the real, the same risk is that if this is truly 00:15:18.772 --> 00:15:23.602 transformational, if you don't jump on the bandwagon today, you'll be 00:15:24.832 --> 00:15:29.202 g- you know, you will be, not be able to catch the train any longer. 00:15:29.852 --> 00:15:33.552 and I actually think it's, I do think that it's the case. 00:15:33.592 --> 00:15:37.512 I think you're right. And I think the problem here is also that it's in a 00:15:37.552 --> 00:15:41.052 different way you will be left behind. Because in, if you look at the 00:15:41.092 --> 00:15:44.812 information society, if you look at the digital divide as we used to talk about, 00:15:44.852 --> 00:15:48.272 the digital divide you could bridge by connecting more and more people, or 00:15:48.312 --> 00:15:51.892 connecting companies, or connecting employees, and making sure they had access 00:15:51.932 --> 00:15:54.332 to the internet, and then starting to rethink the business model. 00:15:54.372 --> 00:15:58.252 So connection was the thing that you would do in order to bridge the digital 00:15:58.292 --> 00:16:01.512 divide. But if you now look at the kind of divide that we're building, it's a 00:16:01.552 --> 00:16:06.382 cognitive divide. It's sort of a divide that is based on how you learn. 00:16:06.872 --> 00:16:10.552 And learning is premised on organizing your data in the right way, asking the 00:16:10.592 --> 00:16:14.412 right kinds of questions, following up, compounding, making sure that every new 00:16:14.452 --> 00:16:17.202 learning is integrated into a new world model. 00:16:17.472 --> 00:16:20.382 And those things, they compound much faster. 00:16:20.532 --> 00:16:23.182 It's not just a question of giving somebody access to AI. 00:16:23.372 --> 00:16:27.012 You have to set up this learning infrastructure, and once you do that, it 00:16:27.052 --> 00:16:32.042 accelerates. So if you're left behind, you're left behind not a linear 00:16:32.511 --> 00:16:37.992 evolution of a field, but you're left behind somebody who is slowly going into 00:16:38.032 --> 00:16:43.412 an exponential learning curve. And that is, that is means that the cognitive 00:16:43.452 --> 00:16:47.292 divide is unlikely to just become smaller by its own. 00:16:47.332 --> 00:16:51.862 It's l- rather likely to grow. So between the companies that do or do not 00:16:52.052 --> 00:16:56.732 organize themselves for learning through AI or adapting through AI will probably 00:16:56.772 --> 00:17:02.632 be left even further behind, and their sort of gap will be growing if you 00:17:02.672 --> 00:17:06.402 compare to digital. So I think they're potentially in a worse situation. 00:17:07.652 --> 00:17:12.382 It's interesting you say about the exponential development. 00:17:13.172 --> 00:17:18.902 you also remember our ex-colleague Ray Kurzweil, who always argued m- 00:17:19.112 --> 00:17:23.582 his argument was clearly that yes, all these developments are exponential. 00:17:23.712 --> 00:17:26.892 And the interesting thing about exponential developments are obviously that in 00:17:26.932 --> 00:17:29.542 the beginning it looks like nothing happens. 00:17:29.952 --> 00:17:30.312 Yes. 00:17:30.352 --> 00:17:34.622 Because the beginning is, it looks slow, and then when the hockey stick hits, 00:17:35.032 --> 00:17:37.102 then that's when it's, so to say, late. 00:17:37.432 --> 00:17:42.932 Are we today in that phase now when... have we hit the hockey stick or yet, or 00:17:42.972 --> 00:17:45.742 are we still in the phase that it development looks slow? 00:17:46.100 --> 00:17:50.440 And there's a new term being thrown around in tech circles where they say we're 00:17:50.480 --> 00:17:54.580 in the foothills of the singularity. So the foothills is sort of this space 00:17:54.620 --> 00:17:58.790 between the ground and the mountain, the exponential. 00:17:59.100 --> 00:18:01.840 So this notion of being in the foothills of the singularity, I think is not 00:18:01.880 --> 00:18:04.580 completely wrong. I mean, I think singularity is a really... 00:18:04.620 --> 00:18:08.140 It's an interesting concept, and it can be contested because you can say there's 00:18:08.180 --> 00:18:11.880 been no technology in the history of mankind that has not turned out to be an S 00:18:11.920 --> 00:18:15.980 curve. So whatever we said was an exponential curve, electrification or 00:18:16.020 --> 00:18:21.520 computers or internet, et cetera, ultimately always turned out to flatten like 00:18:21.560 --> 00:18:24.530 this like an S curve, not an exponential curve. 00:18:24.860 --> 00:18:27.440 Now, the argument against that, though, from the people who believe in the 00:18:27.480 --> 00:18:30.700 singularity is really interesting because what they will say is that, yes, all 00:18:30.740 --> 00:18:35.240 individual technologies describe an S curve, but AI allows you to stack them on 00:18:35.280 --> 00:18:39.400 each other. So every time a technology flattens, a new technology will come 00:18:39.440 --> 00:18:42.280 along, and that will build the exponential over time. 00:18:42.320 --> 00:18:46.150 So compounding these S curves is what gives you the exponential. 00:18:46.520 --> 00:18:47.420 And so 00:18:48.660 --> 00:18:52.480 I mean, the jury's out on this one. You can or cannot believe in the singularity 00:18:52.520 --> 00:18:55.820 if you want to. But I think- one of the things that we should recognize is that 00:18:55.860 --> 00:18:59.630 the evolution, the development is now incredibly fast. 00:18:59.940 --> 00:19:00.200 And- 00:19:00.240 --> 00:19:00.600 Yeah 00:19:00.640 --> 00:19:04.900 we also seem to be at the cusp of this interesting moment where AI codes AI in a 00:19:04.940 --> 00:19:08.730 way that we don't quite understand, but we also believe will greatly 00:19:09.840 --> 00:19:12.810 will greatly improve the speed with which AI develops. 00:19:13.620 --> 00:19:17.770 Anthropic recently released a statement where they said that, you know, around 00:19:17.820 --> 00:19:21.220 90% of the improvements that we're doing right now in some of our models are 00:19:21.260 --> 00:19:24.900 actually done by models. checked by humans, they sort of added. 00:19:24.940 --> 00:19:26.250 It's like they're checked by humans. 00:19:27.400 --> 00:19:28.700 but that- 00:19:28.740 --> 00:19:30.410 It was an assistant. It wasn't me. 00:19:30.520 --> 00:19:35.860 Yes. but that sort of suggests, that suggests that we might be heading into the 00:19:35.900 --> 00:19:40.240 exponential to your point because I mean, I, and I do think this is interesting 00:19:40.280 --> 00:19:45.650 because y- when you can start to run different processes in computational speed, 00:19:46.080 --> 00:19:49.140 so you can run them at the speed of a computer, and you're no longer held back 00:19:49.180 --> 00:19:54.130 by biological speed, the speed of human beings, then things will go faster 00:19:54.300 --> 00:19:58.660 almost by default. there will be still some biological bottlenecks, but we're 00:19:58.700 --> 00:20:02.670 removing more and more of them across at least the field of coding. 00:20:06.280 --> 00:20:09.650 if I, if I... A little bit a- another, other question is like I think one of the 00:20:10.240 --> 00:20:14.880 advantages both you and I have right now is that we control, so to say, our own 00:20:14.920 --> 00:20:22.360 calendars, and we have the possibility to test, learn, take time to 00:20:22.400 --> 00:20:24.630 develop different things and so on. 00:20:25.940 --> 00:20:31.280 if I see the companies that I work together with on boards and also through 00:20:31.320 --> 00:20:36.580 different other means, they are completely overwhelmed and overheated by 00:20:36.620 --> 00:20:41.040 information, by tasks. Then they're saying, Oh, you know, we're cutting now 00:20:41.080 --> 00:20:45.540 people, but they don't know how to, how to you know, take advantage of these 00:20:45.580 --> 00:20:46.870 tools and so on. 00:20:48.060 --> 00:20:52.950 where do you think they should start? What would be-- What should they use their 00:20:53.480 --> 00:20:59.530 one free hour a day of in order to get over this 00:21:01.200 --> 00:21:07.170 how would I put it completely overwhelmed world as it seems like now in many 00:21:07.500 --> 00:21:08.450 cor- corporations? 00:21:09.260 --> 00:21:14.360 Well and it's such a good picture of reality as well because I do think that a 00:21:14.400 --> 00:21:17.180 lot of people feel overwhelmed. they feel they're working more than ever, and 00:21:17.220 --> 00:21:21.170 this notion that AI is taking their jobs, they're like, Yes, please, take it. 00:21:21.620 --> 00:21:23.950 Because it's like there's so much to do, right? 00:21:24.260 --> 00:21:25.900 but I but I think that if you, if you- 00:21:25.940 --> 00:21:27.790 by the way, that you s- you said that 00:21:28.880 --> 00:21:30.780 and partly as a little bit of a joke, but it interests me. 00:21:30.820 --> 00:21:31.040 yeah. 00:21:31.080 --> 00:21:36.880 I just saw in a survey where half of people in 00:21:36.920 --> 00:21:42.320 businesses did not dare to say what tools they are using because they're afraid 00:21:42.360 --> 00:21:46.600 of their jobs. So if someone sees that they're using a tool and that makes them 00:21:46.640 --> 00:21:49.310 more efficient, the question is, Oh, am I still needed? 00:21:50.140 --> 00:21:51.040 Half of the people- 00:21:51.140 --> 00:21:53.070 which I thought was scary. 00:21:53.480 --> 00:21:54.020 and it's crazy. 00:21:54.060 --> 00:21:57.300 So they'd rather, they'd rather keep it to themselves and say, Oh, yeah, I'm 00:21:57.340 --> 00:21:58.240 really busy. 00:21:58.320 --> 00:22:01.840 and that's, and that's crazy because what we really need are people who can use 00:22:01.880 --> 00:22:05.340 the tools and use them really well. But to your question then, what do you do if 00:22:05.380 --> 00:22:08.120 you have an hour a day and you want to develop and you want to grow and you want 00:22:08.160 --> 00:22:11.500 to understand how to deal with the information that is overwhelming you? 00:22:11.540 --> 00:22:14.990 I think the answer is surprisingly simple and slightly cheeky. 00:22:15.300 --> 00:22:20.630 It is you should ask the AI to teach you how to deal with information overload. 00:22:20.960 --> 00:22:24.940 Give it, you know, ask it to give you three tips a day and walk you through how 00:22:24.980 --> 00:22:28.960 to become more effective, and it will. At this point, we're in this unique 00:22:29.000 --> 00:22:32.210 situation where we have a technology that can teach you how to use it. 00:22:32.700 --> 00:22:36.700 And that's never been the case before. And so if you're really dead set on 00:22:36.740 --> 00:22:40.430 trying to figure out how things work, you can just start to ask it. 00:22:40.740 --> 00:22:43.800 That's when I realized that, which was when I was sort of playing around with 00:22:43.840 --> 00:22:49.100 chatbots, et cetera, that I can ask this thing to teach me it m- sort of made 00:22:49.140 --> 00:22:51.820 for a minor revolution in the way that I use technology. 00:22:51.860 --> 00:22:55.820 So I started coding. It taught me to use open source repos. 00:22:55.860 --> 00:22:59.760 I started to build my own skills, was the thing I started with, which is a 00:22:59.800 --> 00:23:04.220 simple way of telling the g- the AI to do the thing it's doing in the same way 00:23:04.260 --> 00:23:05.060 all the time. 00:23:05.120 --> 00:23:08.940 And then I went into using Claude code, and every time I ran into something that 00:23:08.980 --> 00:23:12.620 I didn't understand, I asked it to explain it to me as if I was a 12-year-old, 00:23:12.660 --> 00:23:14.550 and it happily did. And so- 00:23:14.760 --> 00:23:19.420 I would, I would I would, I would sort of constantly have the ability to learn 00:23:19.460 --> 00:23:25.220 more and more and more. my challenge now is that I need the AI to 00:23:25.260 --> 00:23:29.060 tell me where my ignorance is keeping me back because I think I learned 00:23:29.100 --> 00:23:33.190 something. I think I know how to do this thing, and so I do it the same way. 00:23:33.480 --> 00:23:37.440 And what I've learned to do is that I've learned to ask the AI, improve on my 00:23:37.480 --> 00:23:42.239 ideas and improve on my methods. Tell me what I could be doing to do this more 00:23:42.279 --> 00:23:43.179 effectively. 00:23:43.380 --> 00:23:46.800 Which means that I don't get stuck in thinking that I'm really good at this, 00:23:46.840 --> 00:23:50.240 which is like a very human error. I did that in the beginning. 00:23:50.280 --> 00:23:52.720 I was like, Oh, I'm really good at this and I'm doing this in the right way- ... 00:23:52.760 --> 00:23:55.980 et cetera, et cetera. And then when I ask the AI to sort of review what I had 00:23:56.020 --> 00:23:59.260 been doing, the project that I'd been working on, and give me a few insights 00:23:59.300 --> 00:24:03.080 into where I could be doing things more effectively it was slightly embarrassing 00:24:03.120 --> 00:24:05.440 because I was I was, yeah, using wrong technology. 00:24:05.480 --> 00:24:08.600 I was using wrong hosting. Too much of this, too little of that. 00:24:08.640 --> 00:24:11.830 Models that were much too expensive for what I was trying to do. 00:24:12.220 --> 00:24:15.940 And when we optimized it and my s- could continue to learn- 00:24:16.040 --> 00:24:22.040 the result was awesome. so this sort of i- two things: ask the 00:24:22.080 --> 00:24:27.830 technology and constantly be on guard against thinking that you know enough. 00:24:28.380 --> 00:24:30.340 I think those are the kinds of things I would advise. 00:24:30.380 --> 00:24:31.289 What would you advise? 00:24:32.520 --> 00:24:37.070 Well, yeah, I like that thing. As I wrote my first skills 00:24:38.120 --> 00:24:42.090 some time ago, and I also was thinking, So where do I start? 00:24:42.440 --> 00:24:45.790 And I started by saying, Tell me how to m- how to do this. 00:24:46.080 --> 00:24:46.380 Yes. 00:24:46.420 --> 00:24:51.060 so we're coming back to that. the other thing there I think also is fascinating 00:24:51.100 --> 00:24:54.890 really about asking those questions in order to learn. 00:24:55.880 --> 00:25:00.860 I have the chance to help the business school here in Helsinki around these 00:25:00.900 --> 00:25:05.100 topics. And one of the things that I always tend to ask them is that, so if I 00:25:05.140 --> 00:25:10.190 don't understand something, how many questions do I dare to ask the professor? 00:25:11.280 --> 00:25:12.410 Probably two. 00:25:13.620 --> 00:25:16.750 And if I still don't understand, I, I'll just say, Oh, okay. 00:25:16.880 --> 00:25:20.490 I and then I'll go home and trying to figure that out or I ask my friends. 00:25:21.320 --> 00:25:25.160 what's wonderful with these tools is that as you said, you know, you can, you 00:25:25.200 --> 00:25:29.280 can, you can continuously ask, So sorry, I still didn't understand. 00:25:29.320 --> 00:25:32.850 Can you please make this a more simple ways? 00:25:32.900 --> 00:25:33.800 or 00:25:34.560 --> 00:25:38.580 as you, as you said, I wouldn't dare saying that, just explain to me like I'm 12 00:25:38.620 --> 00:25:40.990 year old because I, I'm sure that those 12-year-olds- 00:25:41.340 --> 00:25:42.640 No, they're smarter than we are now- 00:25:42.760 --> 00:25:43.620 for sure. yeah 00:25:43.660 --> 00:25:44.590 how to use these- 00:25:44.680 --> 00:25:45.640 I completely agree with that 00:25:45.680 --> 00:25:45.900 these tools 00:25:45.940 --> 00:25:46.600 They're very smart. 00:25:46.640 --> 00:25:50.160 but I completely agree with you. I think that's one of those things that where 00:25:50.200 --> 00:25:55.550 you can really f- find amazing ad- advantages of... 00:25:56.240 --> 00:25:58.910 and also as you said what am I, what am I missing? 00:25:59.620 --> 00:26:05.580 I wrote a keynote a few days ago, and then one of the things I asked also 00:26:05.620 --> 00:26:09.670 was that tell me what areas of this keynote are dated. 00:26:10.500 --> 00:26:14.940 And it said, and it said, Oh yeah, you know, you, these examples are quite old. 00:26:14.980 --> 00:26:16.680 You know, you should, you should probably use this. 00:26:16.720 --> 00:26:21.690 I, I'll g- I'll find you a better example that is closer to today and so on. 00:26:22.080 --> 00:26:23.780 And I thought that was really good also. 00:26:23.820 --> 00:26:24.720 and 00:26:25.520 --> 00:26:30.790 it also added, said so you know, just don't talk about, you know in a way that 00:26:31.080 --> 00:26:35.860 using it as a chatbot or like a, like a instead of a of a, of a Google Search 00:26:35.900 --> 00:26:40.480 box, but really about how do you take that into agents and so on. 00:26:40.520 --> 00:26:40.960 And I- 00:26:41.060 --> 00:26:46.350 I thought it was it gave me good insights again in what I was missing. 00:26:46.660 --> 00:26:48.780 And I say, Oh yeah, you know, you, you're right. 00:26:48.820 --> 00:26:53.000 I am missing those things. so I think you know, keeping you alert all the, all 00:26:53.040 --> 00:26:57.550 the time also and say, you know, what am, what are areas did I not think of- 00:26:58.320 --> 00:27:00.400 I think are absolutely key also. 00:27:00.440 --> 00:27:04.340 And I think the really good part of that, what you're describing, is that you 00:27:04.380 --> 00:27:07.800 are also starting with your own thinking, which means that you're not handing 00:27:07.840 --> 00:27:10.000 over the thinking from the get-go to the machine. 00:27:10.040 --> 00:27:12.510 And I think we should also talk about the anti-patterns. 00:27:12.760 --> 00:27:15.800 When I talk to people about AI, one of the things I really try to say, there are 00:27:15.840 --> 00:27:17.490 ways in which you should not use it. 00:27:17.920 --> 00:27:21.080 So I there are a few simple tips that I always come back to. 00:27:21.120 --> 00:27:26.160 One is use more than one AI. Ask it to take the opposing stances. 00:27:26.200 --> 00:27:28.560 So one is pro something, one is con something. 00:27:28.600 --> 00:27:31.310 That's a really good way to make sure that you are in the driver's seat. 00:27:31.640 --> 00:27:35.140 It's a judgment-centric setup. The other thing that I think is really important 00:27:35.180 --> 00:27:40.520 is start with human thinking. I'm allergic to this notion that the AI can give 00:27:40.560 --> 00:27:42.360 you a draft and then you can expand on it. 00:27:42.400 --> 00:27:44.370 That's exactly the wrong way around. 00:27:44.879 --> 00:27:48.840 I sit down now, I write longhand when I do a talk or an, you know, an essay or 00:27:48.880 --> 00:27:52.740 something. I write longhand for a couple of hours sometimes, and then I take 00:27:52.780 --> 00:27:57.160 photos of my longhand writing. I digitize it, and then I ask for comments and 00:27:57.200 --> 00:28:00.510 ideas and, you know, things I missed to your point about the keynote. 00:28:00.940 --> 00:28:05.250 But if I would start with asking the AI, I'm giving a keynote on this. 00:28:05.380 --> 00:28:09.620 give me a few ideas, that's n- at that point I don't think I am necessary 00:28:09.660 --> 00:28:11.530 anymore. And then I think also- 00:28:11.860 --> 00:28:17.130 at that point we're missing human originality and human creativity, which still, 00:28:17.280 --> 00:28:20.330 I believe, is greater than that you can get from machines. 00:28:20.660 --> 00:28:24.540 Also because the creativity in the machines is derived from human creativity. 00:28:24.580 --> 00:28:29.080 We are c- we are capable of creating truly novel things, so we should start with 00:28:29.120 --> 00:28:34.120 the human. So judgment centric, always start with the human are things that I 00:28:34.160 --> 00:28:37.310 think are so important when it comes to the use of AI. 00:28:37.600 --> 00:28:41.400 Otherwise you end up in what's sort of now popularly called cognitive offloading 00:28:41.440 --> 00:28:44.940 or cognitive surrender where you're essentially saying, Oh, there's this 00:28:44.980 --> 00:28:50.340 thinking machine here. let's have it think for me because that seems like okay, 00:28:50.380 --> 00:28:52.990 and I don't have the energy for thinking right now. 00:28:53.400 --> 00:28:55.990 And that's a path we should absolutely avoid, I think. 00:28:57.180 --> 00:29:02.770 That I think is one of the key learnings from the last half hour- 00:29:03.260 --> 00:29:09.200 if I were to put it that way, is that always start by thinking 00:29:09.240 --> 00:29:10.210 yourself first. 00:29:11.260 --> 00:29:14.460 And I think that is something that it's like if there's nothing else you take 00:29:14.500 --> 00:29:15.320 out of this- 00:29:15.580 --> 00:29:19.270 I would say that. And this is something also that I have been very much 00:29:19.420 --> 00:29:25.280 emphasizing at the business school is that we need to start, always start 00:29:25.320 --> 00:29:29.890 thinking first as well as I think business schools need to teach thinking. 00:29:30.440 --> 00:29:30.880 Yes. 00:29:30.920 --> 00:29:36.830 they fa- teach concepts and teach thinking because through that we can then 00:29:37.040 --> 00:29:40.830 use these assistants in driving different things. 00:29:42.320 --> 00:29:45.250 what other things would you not hand over to AI today? 00:29:46.980 --> 00:29:50.760 So I... The most important thing I think is what we just talked about. 00:29:50.800 --> 00:29:55.010 I wouldn't hand over the first draft to an AI at all. 00:29:55.380 --> 00:29:59.790 I wouldn't, I also wouldn't hand over reading to an AI. 00:30:00.060 --> 00:30:03.700 So I actually tend to believe that reading is really important, and I like to 00:30:03.740 --> 00:30:08.900 read myself. I don't want just to have an AI sum up what an article says or sum 00:30:08.940 --> 00:30:12.920 up what a book says. Sometimes if it's in the periphery, it can be fine to just 00:30:12.960 --> 00:30:15.030 know what the main argument in a book is. 00:30:15.300 --> 00:30:18.860 But if I'm really working on something, then I want to really get into it 00:30:18.900 --> 00:30:22.510 myself, and the experience of reading a book changes you. 00:30:22.820 --> 00:30:26.960 And that means that next time you sit down and write, you have new things to 00:30:27.000 --> 00:30:29.810 write about. So I don't hand off reading. 00:30:29.920 --> 00:30:32.970 I don't hand off the first draft. I don't hand off judgment. 00:30:33.260 --> 00:30:37.400 Those are the key things that I try to make sure remain v- very solidly within 00:30:37.440 --> 00:30:39.090 my p- purview. 00:30:40.340 --> 00:30:43.010 and I think those are the key things. 00:30:44.220 --> 00:30:47.860 well, what I also have found is I need to be very clear when handing off 00:30:47.900 --> 00:30:51.440 scheduling because I was at some point scheduled to have 20 meetings in a day 00:30:51.480 --> 00:30:56.000 because the AI was going for efficiency and not necessarily for just human 00:30:56.040 --> 00:31:01.040 survival at this point. so there are a few things where, you know, you have to 00:31:01.080 --> 00:31:03.350 be very clear about your delegation as well. 00:31:04.080 --> 00:31:05.310 and I think that's important. 00:31:05.660 --> 00:31:11.520 And maybe to offer a more a more complex point, I think y- what you do 00:31:11.560 --> 00:31:16.810 not want to do is to hand over to the AI to decide your ontology for you. 00:31:17.260 --> 00:31:21.930 An ontology is like a very, it's like a fancy word of the stuff that exists. 00:31:22.360 --> 00:31:26.160 If you, if you sort of take your world description from your AI, then you will 00:31:26.200 --> 00:31:30.660 be limited in the way you think. You should own the way you describe the world, 00:31:30.700 --> 00:31:33.970 its ontology, the stuff that exists, how it interrelates. 00:31:34.440 --> 00:31:36.670 That is something that i- belongs to you. 00:31:36.900 --> 00:31:42.810 Being able to specify, describe, invent ontologies or world models, 00:31:43.160 --> 00:31:47.290 I think is a key to the long-term use of complex AI as well. 00:31:48.920 --> 00:31:50.730 What about you? What do you not hand over? 00:31:52.280 --> 00:31:58.320 Well, we mentioned already about the thinking and 00:31:58.360 --> 00:32:03.670 the beginning of that process. otherwise you'll get the averages of averages, 00:32:04.040 --> 00:32:07.050 and you don't get the thinking of, so to say 00:32:09.180 --> 00:32:13.050 an unorthodox thinking as well. so you're missing that. 00:32:14.800 --> 00:32:19.780 there are th- areas of data, for example financial data, that I'm very hesitant 00:32:19.820 --> 00:32:23.690 with. There are health data today where I'm very hesitant with. 00:32:23.740 --> 00:32:28.440 And so there are areas like this, and I don't know should I be that hesitant or 00:32:28.480 --> 00:32:30.410 not, but I am very hesitant with those. 00:32:30.840 --> 00:32:36.360 and the question always obviously is that do you trust this not to use your 00:32:36.400 --> 00:32:42.340 data in the, in the training? do you trust them not to leak your data and so 00:32:42.380 --> 00:32:47.300 on? And I don't have the answer to that right now and but it makes me a bit 00:32:47.340 --> 00:32:52.830 hesitant. And sometimes I feel like I could probably be more efficient 00:32:54.160 --> 00:32:59.740 if I would trust them more, so to say. The question is that do I dare to trust 00:32:59.780 --> 00:33:01.990 them more? Do you trust this? 00:33:02.220 --> 00:33:04.720 Well, no, I ma- I think this is a good point. 00:33:04.760 --> 00:33:07.240 I think it's not necessarily about the handing over the data. 00:33:07.280 --> 00:33:09.960 What sort of concerns me is the use and ownership of the data. 00:33:10.000 --> 00:33:13.690 But so to me, this is actually an area for massive innovation. 00:33:14.180 --> 00:33:17.600 I would- be happy to hand over my health data to a trust, and then have- 00:33:17.680 --> 00:33:21.460 that trust anonymize and aggregate the data in such a way that AI companies 00:33:21.500 --> 00:33:23.280 could do research on it. I would actually- 00:33:23.360 --> 00:33:26.580 quite I would love that because that would mean that I could be- have better 00:33:26.620 --> 00:33:28.180 health outcomes in different ways. 00:33:28.220 --> 00:33:28.640 Correct. 00:33:28.680 --> 00:33:32.790 So for me that would be good. But what we lack here is institutional innovation. 00:33:33.000 --> 00:33:36.260 And the kind of institutional innovation that's needed is essentially innovation 00:33:36.300 --> 00:33:40.770 that allows for individual trust and technological learning. 00:33:40.940 --> 00:33:45.280 so how do you enable the maximum amount of learning on the side of the AI 00:33:45.320 --> 00:33:48.850 companies and the maximum amount of trust on the side of the users? 00:33:48.900 --> 00:33:54.170 I think the, it's not inconceivable to me that there could be like a third-party 00:33:54.300 --> 00:33:58.970 institutional solution to that would be quite interesting- 00:33:59.260 --> 00:34:02.560 because I would love to, I would love to have an AI look at my health data and 00:34:02.600 --> 00:34:02.820 say- 00:34:02.860 --> 00:34:03.180 Agree 00:34:03.220 --> 00:34:06.710 You do this and this and this, and you'll be, you know, feeling much better. 00:34:07.080 --> 00:34:09.230 Agree. Finan- finance is the same thing. 00:34:09.560 --> 00:34:12.920 Yeah, totally. If, you know, if you could hand over your finances, you could 00:34:12.960 --> 00:34:16.600 hand over... I think finances is interesting because we're all trying to get an 00:34:16.640 --> 00:34:20.070 individual edge. There's like a really interesting risk being discussed by the, 00:34:20.160 --> 00:34:23.980 by the central banks right now, which is that may- people actually do hand over 00:34:24.020 --> 00:34:27.660 their finances to ChatGPT. So they will ask ChatGPT, What should my portfolio 00:34:27.700 --> 00:34:28.780 look like? And- 00:34:28.940 --> 00:34:30.880 then you get a portfolio recommendation. 00:34:30.920 --> 00:34:34.180 But then what happens if 100 million people get the same portfolio 00:34:34.220 --> 00:34:38.640 recommendation and ChatGPT one morning wakes up and says, You should sell 00:34:38.680 --> 00:34:41.180 Nvidia. And the 100 million people managing- 00:34:41.240 --> 00:34:43.330 the portfolios through ChatGPT does that. 00:34:43.440 --> 00:34:45.580 The volatility that then results. 00:34:45.620 --> 00:34:49.170 But now you outsource your thinking. 00:34:49.680 --> 00:34:49.900 Yes. 00:34:49.940 --> 00:34:53.410 And we said, we just said earlier that we should not outsource the thinking. 00:34:53.720 --> 00:34:57.840 What I would use it for more or less is that, for exam- sample say that what's 00:34:57.880 --> 00:35:00.950 my exposure to hyperscalers? 00:35:01.600 --> 00:35:06.200 Because like you have ETFs, funds. You might have even bonds from them. 00:35:06.240 --> 00:35:09.210 You might have, you know, stocks from them and so on. 00:35:10.140 --> 00:35:14.950 very rarely can anybody tell me today is that what's my w- and through that, 00:35:15.040 --> 00:35:18.350 what's my the, w- what's the risk that I'm taking? 00:35:19.080 --> 00:35:21.840 Because like probably these are all moving in the same direction. 00:35:21.880 --> 00:35:27.840 and so I would, I would use my 100 assistants to dig into 00:35:27.880 --> 00:35:33.160 these, to these instruments and then do calculations of how do they correlate 00:35:33.200 --> 00:35:36.440 with each other and how they don't correlate with each other and what's the risk 00:35:36.480 --> 00:35:39.100 there and is there a beta risk there and so on and so on. 00:35:39.140 --> 00:35:44.024 so I'm just saying that I think I would be willing to do that Which would help 00:35:44.064 --> 00:35:45.614 me to make better decisions. 00:35:46.044 --> 00:35:46.364 Yes. 00:35:46.404 --> 00:35:49.914 But I would not ask it to make that decision for me, so to say. 00:35:50.404 --> 00:35:50.704 Mm-hmm. 00:35:50.744 --> 00:35:54.454 And so that's, I think those are those areas where I would really be 00:35:56.544 --> 00:36:02.384 I would love it to work. I would also be probably willing to do it if, and I 00:36:02.424 --> 00:36:08.124 probably need to do some learning here, but so that I could run those locally on 00:36:08.164 --> 00:36:09.644 m- on my, on my own laptops. 00:36:09.684 --> 00:36:10.064 Yeah. 00:36:10.104 --> 00:36:14.994 And then I would be able to do those a- analysis. 00:36:15.284 --> 00:36:17.144 that's probably could be also one solution. 00:36:17.184 --> 00:36:20.924 And it's quite possible to do today. I mean, you can run some of the open weight 00:36:20.964 --> 00:36:23.264 models on your local MacBook if you want to. 00:36:23.304 --> 00:36:23.624 So it's- 00:36:23.664 --> 00:36:24.164 Correct. Yeah 00:36:24.204 --> 00:36:26.544 it is, it is probably going to more and more common. 00:36:26.584 --> 00:36:31.304 And you can imagine that kind of federated edge computing for AI being a thing 00:36:31.344 --> 00:36:35.144 for a lot of things that you want to do for, you know, photos, et cetera, et 00:36:35.184 --> 00:36:37.104 cetera, that you don't want to upload to the cloud. 00:36:37.144 --> 00:36:40.404 So I think that will probably come. But there's s- there's something important 00:36:40.444 --> 00:36:44.284 about what you said about finances and you can sort of sum that up as a method, 00:36:44.324 --> 00:36:48.734 which is that what you do with finances is that you start with a hypothesis. 00:36:48.864 --> 00:36:52.704 You have a hypothesis about what good finance m- portfolio management looks 00:36:52.744 --> 00:36:53.304 like. 00:36:53.364 --> 00:36:56.504 And then you ask the machine to test the hypothesis. 00:36:56.544 --> 00:37:00.064 And I think that's a, that's another way of framing think first, is saying you 00:37:00.104 --> 00:37:03.184 should have a hypothesis about what you think the world looks like or what you 00:37:03.224 --> 00:37:06.264 want to do or what you think the solution to the problem is, then use the 00:37:06.304 --> 00:37:09.804 machine to test the hypothesis. Never allow the machine to give you the 00:37:09.844 --> 00:37:13.864 hypothesis. I think that's a, that's another way of sort of casting the problem. 00:37:13.904 --> 00:37:16.964 I think you're hitting on a, on a, on a, on a really important note there, and I 00:37:17.004 --> 00:37:20.104 think this is one of those things that we need to cover in one of our podcasts 00:37:20.144 --> 00:37:20.544 later is- 00:37:20.584 --> 00:37:20.904 Yes. 00:37:20.944 --> 00:37:22.094 for example, board work. 00:37:22.784 --> 00:37:26.314 And how do you build strategies? How do you test strategies? 00:37:26.644 --> 00:37:31.204 How do you look at... 'Cause one of the most important w- jobs of a, of a, of a 00:37:31.244 --> 00:37:35.844 board is obviously oversight and see that everything goes well, but also is to 00:37:35.884 --> 00:37:37.374 evaluate strategies. 00:37:37.904 --> 00:37:41.444 And what you can do with these things are absolutely amazing. 00:37:41.484 --> 00:37:45.764 And for example, I've built my own supervisory boards in order to make those, 00:37:45.804 --> 00:37:50.584 some of those decisions. We'll get back to that in another episode. 00:37:50.644 --> 00:37:54.034 But I think that I think you're hitting one of the key things here. 00:37:54.384 --> 00:37:58.194 I have two quick questions for you, and then let's wrap up. 00:37:59.564 --> 00:38:04.964 one for me is that if there would be one habit for all the listeners to start 00:38:05.004 --> 00:38:06.974 with this week, and we're now 00:38:08.684 --> 00:38:11.454 middle of the week, so what would that be? 00:38:12.704 --> 00:38:17.424 Habit of asking the AI to teach you something about how you can use AI in order 00:38:17.464 --> 00:38:20.504 to become more, in order to learn faster. 00:38:20.544 --> 00:38:23.794 That's a habit that I think is really good to acquire quickly. 00:38:24.824 --> 00:38:25.974 What would your choice be? 00:38:26.664 --> 00:38:32.404 Oh, I like, I like that. I think one of the things really is to dig into 00:38:32.444 --> 00:38:33.754 these tools. 00:38:35.824 --> 00:38:41.524 I've been saying quite often that my imagination is the limit for what I can do 00:38:41.564 --> 00:38:42.464 with these things. 00:38:42.724 --> 00:38:46.524 So I think the first question I always should ask is that, so could this be 00:38:46.564 --> 00:38:47.464 automated? 00:38:47.764 --> 00:38:49.844 What I'm now doing, could it be automated? 00:38:49.884 --> 00:38:50.834 And if it could 00:38:52.864 --> 00:38:57.174 aut- automate it. I have one big question coming up. 00:38:57.584 --> 00:38:58.484 Uh-oh. 00:38:59.044 --> 00:39:01.194 What does the world look like a year from now? 00:39:03.104 --> 00:39:07.304 What does your crystal ball say? I know you have it in front of you, and you've 00:39:07.344 --> 00:39:09.764 been thinking a lot about this, and I know w- well, you have one of those 00:39:09.804 --> 00:39:14.264 companies that are also looking into more as forecasting, foresight, and so on. 00:39:14.324 --> 00:39:16.564 Yeah, we do foresight. We do forecasting, et cetera. 00:39:16.604 --> 00:39:21.664 I think, I think it's really interesting because to me I think the evolution of 00:39:21.704 --> 00:39:23.684 AI is going much faster than we recognize. 00:39:23.724 --> 00:39:27.374 So I think that the world might be very different in a year than it is now. 00:39:27.764 --> 00:39:31.664 So I think, for example, that we will see agents fully integrated with 00:39:31.704 --> 00:39:33.134 everything that you can do on a screen. 00:39:33.564 --> 00:39:35.704 I think that is going to be a difference. 00:39:35.744 --> 00:39:39.704 So you can ask an AI, and you can do it in voice mode or any other mode, to do 00:39:39.744 --> 00:39:41.694 anything that you can currently do on a screen. 00:39:41.904 --> 00:39:45.764 And if you think about what that means, it means that, you know, the screens and 00:39:45.804 --> 00:39:48.424 the keyboards might no longer actually be necessary. 00:39:48.464 --> 00:39:53.244 So one of my sort of soft predictions would be that we probably will see new 00:39:53.284 --> 00:39:57.984 form factors for AI within the year because nobody has cracked what the device 00:39:58.024 --> 00:40:00.704 looks like that encapsulates AI in a great way. 00:40:00.744 --> 00:40:02.843 We're still using phones. We're still using computers. 00:40:02.883 --> 00:40:06.254 We're still using keyboards, and I think that might change. 00:40:06.324 --> 00:40:09.904 So I will be really interested to see what the form factor is, and I do think 00:40:09.944 --> 00:40:15.194 that we will be delegating a whole lot more to our collection of agents. 00:40:15.424 --> 00:40:21.384 And then I think that within a year we will also have experienced a lot more in 00:40:21.424 --> 00:40:24.544 terms of security incidents, and that has just started. 00:40:24.584 --> 00:40:25.084 Mm-hmm. 00:40:25.124 --> 00:40:27.434 So our systems will become less connected. 00:40:27.904 --> 00:40:32.044 I predict, and this is not going out on a limb, that freezers will not be 00:40:32.084 --> 00:40:34.194 connected to the internet in a year from now. 00:40:34.504 --> 00:40:37.534 Yes. Yeah. I think that's 00:40:38.964 --> 00:40:42.424 I, I'd love to come back on that in a year's time to see what people- 00:40:42.464 --> 00:40:45.834 yes. You should hold me accountable. You should hold me accountable 00:40:46.284 --> 00:40:47.934 what happened. 00:40:49.024 --> 00:40:54.044 topics we want to cover in this going forward, I mentioned already we need to be 00:40:54.084 --> 00:40:59.964 looking into how should AI sit on the boards table- board table, and how should 00:41:00.004 --> 00:41:04.244 actually every single board member in the future and already today have, so to 00:41:04.284 --> 00:41:06.784 say, their own agents to do the, to do research. 00:41:06.824 --> 00:41:12.344 I think that is a fundamental change that we will see in my view, how 00:41:12.384 --> 00:41:14.174 companies are managed. 00:41:15.464 --> 00:41:16.364 data centers. 00:41:16.764 --> 00:41:17.664 Data centers. 00:41:18.064 --> 00:41:22.934 Well, I think we should absolutely look into that topic. 00:41:24.344 --> 00:41:28.994 you mentioned the data security and all of this area. 00:41:29.744 --> 00:41:31.874 I think that should be one of those areas. 00:41:32.204 --> 00:41:34.114 I would love to also for us to discuss 00:41:35.184 --> 00:41:36.084 a little bit 00:41:37.004 --> 00:41:41.774 how do we trust those tools, and can those tools be trusted, and can we... 00:41:41.864 --> 00:41:45.264 what should companies... Like I see so many companies today, they say, Okay, you 00:41:45.304 --> 00:41:48.474 know what? We have this license with Microsoft Copilot. 00:41:49.044 --> 00:41:50.804 you are not allowed to use anything else. 00:41:50.844 --> 00:41:55.944 And then the employees or the students, they use all kind of other tools, so to 00:41:55.984 --> 00:41:56.644 say, widely. 00:41:56.684 --> 00:41:58.844 Oh, there's huge shadow use. I think you're right. 00:41:58.884 --> 00:41:59.184 Exactly. 00:41:59.404 --> 00:42:04.104 Exactly. and what we can do with that. Any other topics you think we should be 00:42:04.144 --> 00:42:04.964 covering? 00:42:05.004 --> 00:42:07.044 Yeah, I think, well, I think we talked about this before. 00:42:07.084 --> 00:42:09.664 One, there are a couple of things that I think we should add to your excellent 00:42:09.704 --> 00:42:12.204 list, and one of them is we should talk about AI in the labor market. 00:42:12.244 --> 00:42:12.984 What will actually happen- 00:42:13.164 --> 00:42:13.784 to your job? 00:42:13.824 --> 00:42:14.184 Yes. 00:42:14.224 --> 00:42:18.314 We should also talk about AI and universities and higher education. 00:42:18.604 --> 00:42:21.954 How do you think about AI when everyone can write an excellent essay- 00:42:22.284 --> 00:42:22.624 Yes 00:42:22.664 --> 00:42:26.804 with, you know, pushing a few buttons? How do you reorganize higher education 00:42:26.844 --> 00:42:31.674 and research around that? And then I think there is, there is there is, there is 00:42:31.744 --> 00:42:36.334 also I think at some point we should just tackle the geopolitics of the thing. 00:42:36.424 --> 00:42:39.054 The US, China, Europe sovereignty. 00:42:39.124 --> 00:42:39.424 Absolutely. 00:42:39.464 --> 00:42:42.584 Who does what, who, and, you know, and what do we need to be able to do in 00:42:42.624 --> 00:42:48.534 Europe, and how should we put some clout behind European regulation and demands? 00:42:48.984 --> 00:42:51.364 And should we, or do we risk sliding behind? 00:42:51.404 --> 00:42:53.944 So I think those are things I would add to your list, and I would be- I'm 00:42:53.984 --> 00:42:55.334 looking forward to discussing them. 00:42:55.824 --> 00:42:58.734 Fantastic. So am I. Thank you very much, Nicklas. 00:42:58.824 --> 00:43:00.564 It was great catching up with you as always. 00:43:00.604 --> 00:43:02.284 Likewise, Jussi. 00:43:02.324 --> 00:43:05.194 Enjoy the bright fall in the archipelago- 00:43:05.364 --> 00:43:06.444 I definitely will 00:43:06.484 --> 00:43:09.774 in Sweden, and we will be catching up very soon. 00:43:10.064 --> 00:43:11.174 We will. Thank you. 00:43:13.900 --> 00:43:16.400 You've been listening to You are on mute! 00:43:16.500 --> 00:43:19.800 Follow the show so you don't miss the next episode.