Episode Transcript
[00:00:08] Speaker A: Welcome to Examining a technology focused podcast that dives deep. I'm Eric Christiansen.
[00:00:16] Speaker B: And I'm Chris Hans.
[00:00:22] Speaker A: Welcome to another episode of Examining the podcast where we take a deep dive into technology and kind of productivity focused topics. How are you doing today, Chris?
[00:00:37] Speaker B: I'm doing well.
You know, you're a little bit still under the weather, but it seems like the voice is better.
[00:00:44] Speaker A: Yeah, like, it's. It's tolerable. I've had. I've been sick for actually, like, over two weeks.
I had laryngitis with this terrible cold. My daughter was sick because she's in daycare and she had an ear infection, unfortunately, and we all caught a cold. So it's just kind of just what happens.
[00:01:03] Speaker B: But, yeah, definitely something going around. There's. It's been like, I know people who have been sick for, you know, several weeks, so.
[00:01:12] Speaker A: But that's life. I mean, that's not the end of the world. I mean, I. I survived. You and I were talking about. Well, you were talking about something we both watched recently on Netflix. It was the Buy now documentary.
[00:01:25] Speaker B: Yeah, yeah, exactly.
[00:01:26] Speaker A: And you were saying that. I mean, basically it talks about, you know, the consumer culture. The minimalist documentary is also very good. I would recommend people watch either or both of the minimalist documentaries. The message is very much the same. But you were saying that kind of the big takeaway that you took from that documentary was just, don't buy this stuff.
[00:01:48] Speaker B: Well, it's just like, again, we kind of, you know, buy into the narrative that you just need more stuff. And with that stuff, like, you know, for whatever reason, I mean, I. I look at it, I. I think we're all kind of guilty of it. I mean, even, let's say, like, phones. I mean, there was a time we talked about this when we first started the. The podcast. Like, every year I would get, like, a new phone, or it would be every two years. Then I just stopped. And then, you know, I had the iPhone 6. Or no, wait, yeah, I think it was the 6. Or is it the 8? I can't remember. It was a. I think it was the six. I had the iPhone six for, like, several years, and then I upgraded to the iPhone 11. And the only reason why I did was because my wife said that it was embarrassing. I don't know who looks at my phone and thinks, hey, oh, this. This person, I can't be seen with him because he has this old phone or whatever. But I. I just looked at it as peer pressure. Yeah, maybe it's peer pressure, but like, literally, I mean, nobody cares. They all look the same. I mean, I even went into like staples the other day and I'm like, hey, is that. Is that the new iPhone? And then I looked at it closer as I get to it, and it was a Samsung Galaxy, which had the same bezel. And I'm like, they're all looking the same now. It's like, it's like, you know that you might have seen that meme where all the SUVs, like white SUVs, they all literally look the same. And so I don't know how we get by, get in, caught up into this thing. And again, it's where society, I don't know if it's even society. It's some of these publicly traded companies where shareholders need to go and see returns, so they got to keep pushing out product. And I mean, I look at, you know, this laptop, for instance, that I got. I mean, prior to this, I had my MacBook Pro from 2012 for over a decade I kept it because they didn't. I didn't want to have dongles. And, and so I, you know, at the end of the day, it works. But some people, they like to show off that they have the latest and greatest. And I'm, as I get older, I'm thinking like, who does anybody actually look at that stuff?
[00:03:57] Speaker A: I don't know that people look at it. I mean, I'm sure there's a certain class of people that look in, you know, social comparison, there's a whole science about that. Certain. I think I'm trying to think of the book that talks about that.
It'll come to me at some point about consumer psychology, but I mean, you're right, I think it's partly a spotlight effect. I don't think people look as closely as we think unless something is really obviously old. You mentioned old phones like the iPhone 6. It's interesting how we upgrade things and why. And thinking about some of the technological advances, I have to say there's certain design trends that I find they're advancements on paper, but they're not quality of life advancements for me personally. So to give you an example, I had my old iPhone 8 plus for many years until I bought the this the 15 or whatever. One of the things I really miss and what I actually preferred is I don't really get a lot out of a bezel less all screen device. And we've kind of moved to, you know, maximizing the screen surface on all our electronics devices. And I actually preferred some of the More tactile buttons. I really liked the home button. I like the design. Same thing with Android phones. I'm not going to pick on Apple where you could always get home.
Tactile buttons don't have to dominate a device. Kind of like the BlackBerry. That was one extreme where you have a built in. What was the famous quote from Steve Jobs was there's a built in keyboard whether you need it or not. And that was. He made a fair observation. But there was still some advantage to having some tactility. You see this in vehicles too. I was in a Tesla not that long ago and it's just very few knobs or buttons. You have to kind of navigate through a display to do the simplest of tasks. Um, and, and it's just not very ergonomic. It's, it's difficult to map your mind to kind of a.
From an information architecture perspective. It's very difficult to map a physical, something that you're expecting to be physical to kind of a software interface. And I, I do wonder sometimes if the design trends to kind of make everything software focused is a bit regressive. One of the reasons why, to your point about the documentary, I've been hesitant to move on because there's certain things that I buy that are valuable tools and they me and they continue to work. And so the marginal utility that I get by upgrading is minimal. It's funny that the, do the, the podcasters and the bloggers, the minimalists have kind of. You can download it from their website. It's really quite interesting. It's kind of like the 16 rules of minimalism. The top rules and what. And one of them is the don't upgrade rule.
So you know, don't upgrade just to upgrade. Now their argument isn't that upgrading is bad, but you know, upgrading should happen when you know, something no longer works or it no longer works for you and then it no longer provides the value that you need.
[00:07:17] Speaker B: Yeah, yeah, exactly. Like, I mean I look at it like there was that one YouTuber, that Marquis Brownlee that, you know, he had this video that he did of the honest Apple salesperson and literally everything that, you know, the new iPhones that are out right now, the six, the, the cheaper one.
[00:07:38] Speaker A: Right?
[00:07:38] Speaker B: Yeah, well, and even the other ones, I don't know if it's like marginal, you know, difference in terms of like the computing power and the camera and that kind of thing, but for sure the basic version, you would be better off getting the 15 Pro versus getting the, the, the 16e which they've increased the price on or even just even the basic 16. And so again like they're, they, if you think about it, they're, they need to go and push phones. They have to create some reason for you to push the phones. And, and even I look at it like most people can't even tell the difference. Like literally it's the, the difference in terms of the, the aesthetics. There's like one button that's the only difference. And if you had the different color and so, and I don't know if there's going to be much difference even in terms of performance. But again we keep getting into this. I mean even, I think we would be better off. Just the only major issue that comes up with these phones is your battery. You could go to Apple and go and pay the hundred bucks, get them to go and replace it. And even in that documentary it mentioned like you know, having the right to go and repair your own devices or your, any kind of electronics. I mean that, that makes sense to have that. I mean they did it on purpose. But that again this is where like you know, Apple obviously has been one of the most successful companies. Every company has kind of followed suit with that approach where you don't let you know, customers fiddle with their stuff and then you have this kind of planned obsolescence. And but the issue is, I don't know how sustainable that is. You know, you have these rare earth minerals and things that are, we're just going and pushing it onto other countries to go and dismantle or try to do something with it. But it's, it's just causing a lot of waste. And again, I mean that's just the electronic side. I mean I, I look at even I thought it was funny on the fashion side there was, they mentioned in there, there's this one factory, let's say if it was a white dress shirt. In that same factory, the Chinese laborers, they're going and manufacturing for like you know, gap to even high end luxury brands. It's basically, it's like oh okay, shift time has changed. Now I can go and slap on you know, the, the more like the thousand dollar shirt label as opposed to the other one. And so it's, it's just kind of interesting even how like there's so they mentioned this in the documentary. They are producing so much in terms of clothing that there isn't enough people in the world. Like you could clothe people, you know, 10 times over and instead what they do because they gotta go and you know, keep control over supply and Demand and stuff. Like they'd rather just burn the clothing.
[00:10:31] Speaker A: Well, that was brought up in the minimalist documentary. They, I think it was forever 21. It was one of the companies that they highlighted. I'm not suggesting that they're an offender because I don't know, I mean, what's on the screen and the examples they're talking about in a documentary are sometimes blurred. But they talked about. Yeah, instead of having four seasons, there's kind of in the fashion industry, probably similar to tech too, there's like 52 seasons. So this fast fashion. So this idea that you can cut up old clothes rather than donate them because again, the goal is to keep that momentum of purchasing going. And of course you could make that case for all sorts of industries. Clothing is probably the worst example. But the.
[00:11:21] Speaker B: Offender.
[00:11:23] Speaker A: Yeah, offender. Thank you. That's the word I'm looking for. But I think technology is quickly following suit. But I think the issue with tech is that the implications for recycling are much greater than cotton and polyester. Well, I guess not polyester because I guess that turns into microplastics. But there's a lot of rare earth minerals. There's a lot of problems with kind of having a society where everybody has multiple screens and multiple displays, especially if the devices don't last as long as they used to. I mean, thankfully I will say that at least the things that I've purchased, whether they be from Apple or even if it's a work assigned computer, this stuff is well supported and it does actually last. Electronics tend to last a lot longer than they used to. Computers used to be obsolete material, quicker, but now the difference is that everybody has multiple. Right. So I remember talking to, I was at a family event and I was introduced to a friend of a family member and I was talking about just generational quality of life, economic opportunities or just having a general discussion. And I remember one of the things that he said that really stuck with me was that, well, there used to be one television and then if you had a computer, it was like the shared family computer. But now everybody has their own television and everybody has their own computer and everybody has their own iPad and they have a phone and they have a video game console. And so if you think about how many things everybody has, it's quite remarkable.
[00:12:58] Speaker B: Yeah, it's crazy. Like, remember, I don't know, I'm a little bit older than you, but I remember even just like having portable TVs like that was going to be like some like big innovation or something. And now. Yeah, like you're right. I looked at. I think I have six TVs in my house, and there's only four of us in the whole house.
[00:13:16] Speaker A: You have six televisions. That's incredible.
[00:13:18] Speaker B: I have six televisions that, you know, and. Yeah, I haven't even thought about, like. Yeah, you're right. Like, you know, we have the Nintendo Switch, which we just leave it there, but that's a screen. You know, we have iPads. You got. You got all these computers and stuff. Like, it's just. Yeah, it's. It does get a little bit too much and.
[00:13:39] Speaker A: Yeah.
[00:13:40] Speaker B: And I don't know, again, like, I. The more I look at it, like, even things that I buy now, I. I'm trying not to buy anything if I. If I don't need it.
[00:13:50] Speaker A: Yeah.
[00:13:50] Speaker B: So. And that would, that would be like one of the big takeaways is don't buy. But if you do need something, I mean, I. And I kind of. I remember my dad would always mention this. He's like, yeah, you know, if you need something, get it. And even, in fact, you should get something that's high quality that will last you a lot longer. And so that's what I'm kind of looking at is, you know, buying something that. Even if it's like, let's say it's a shirt, buying something that will last hopefully longer. And the other thing that I, I do myself anyways, as I've gotten older, is I. So I don't have to kind of ride this wave of the fast fashion or whatever. I'm sticking to. I'm being like, you know, I guess you're like minimalist people, but just like basic colors. Like, get a white shirt, get a black shirt, you know, just. You don't need anything on there. Just keep it very simple and basic. I don't know if that'll ever go out of style.
[00:14:45] Speaker A: Yeah, I, I don't. I mean, I don't tend to dress up and wear a white shirt as much, partly because I'm worried that now someone like my daughter will spill something all over it. So it's a little bit different. But I tend to have a pretty minimal wardrobe. I mean, you've seen me at work. We work in a pretty casual environment. So I often have a button up, sometimes it's plaid, sometime it's solid. And I usually wear that with some slacks, sometimes jeans. And then I'm not really too worried about it if it's casual or dressy, but more that it's well fitted.
You know, I still wear dress shoes to work every day. But again, like the dress shoes I bought, I've had, I purchased those in 2017.
[00:15:22] Speaker B: Yeah.
[00:15:23] Speaker A: Now I've had them resold at least once on the bottoms.
[00:15:29] Speaker B: Okay. Yeah.
[00:15:30] Speaker A: Not because they're not, they're not leather soles, but they're the rubberized. So like, I've had to. I've had to. I've worn them down just because of the pattern of my walking. So I've had to have them redone. But they're quite comfortable. I've never been able to. Maybe Rockport still makes them, but they're. They're good. So there's no reason for me to. To get rid of them. But one of the other things too, I find is that, you know, over the last year, I think we. I don't know if I mentioned this, I've been slowly kind of decluttering in my house, getting rid of stuff. And the easiest way to do that, other than getting rid of things, is just to not accumulate them in the first place.
You know, shopping takes up a lot of time. You have to make decisions. You have to go get something, you have to order it. Plus there's a financial cost rather than an opportunity cost. And so for me, it's reducing the number of decisions I have to make.
You know, I'm not using it to start a new business that time, but just to have that kind of quiet time, the stillness.
I want more time just to enjoy. I'm not trying to get more time to do something with. And I found that reducing my purchases and kind of just working with what I have and kind of getting good at using the things that I have. And we're going to talk about this a bit more later.
It's kind of a huge advantage versus going for the shiny thing.
[00:16:45] Speaker B: Yeah, yeah, exactly.
[00:16:47] Speaker A: Perhaps we can segue into some. And this is related to Apple.
Excuse me. There was a couple of more high profile articles that were written about Apple recently. One of them was on Jon Gruber's daring Fireball and the other one was David Heinemeiner Hanson. This is a post that was actually taken down from LinkedIn because it violated their policy, I think, on ageism and discrimination. But essentially Jon Gruber talks about how there's something seriously wrong going in on Apple. And then Heinemeier Hansen talks about the age perhaps being an issue in terms of the leadership team because there seems to be a multiple kind of high profile misses that Apple has taken recently. So I'll just lay them out for people who are listening. So for instance, all the advertised Siri AI features have been delayed and I think there are actually a lawsuit now for false advertising because those were prominently advertised in commercials with Bella Ramsey. About all the new Siri features, Jon Gruber argues that they kind of missed some of the warning signs. So he acknowledges his oversight, not recognizing kind of the earlier indications of potential delays. Him being kind of an Apple advocate, he even admits that, which is a big deal.
He also had some concerns over vaporware. So things that are not ready but that they say are going to be released. That's an example of vaporware meaning that it doesn't ever really materialize.
You know, the kind of. The opposite. It's kind of the tangentially related to abandonware, which of course be the kind of Google strategy where you roll things out and then you just don't support them anymore. And so this vaporware is a problem. And he says that this is a big issue because it's kind of eroded the credibility. Right. So then people have purchased phones that are AI enabled, are supposed to be enabled for a technology that's coming in the future that actually isn't going to ship and probably won't ship even on the hardware that's out.
[00:19:10] Speaker B: Yeah, no, for sure.
Should we get into the other comments as well from David Heinemeyer Hansen?
[00:19:19] Speaker A: Yeah. So what did he talk about?
[00:19:21] Speaker B: Yeah, so you know, he was talking about the, the problem could be the age. And so there, right now, the leadership itself, the average board member's age is 68. And you know, if half of them are 70, the youngest is 63, then you look at their executive team, their average age is 60 as well.
And so he's saying that this age could be what's impacting their innovation. And the lack of age diversity is contributing to some of their recent missteps, particularly in this realm of AI. He's suggesting that also this leadership may be out of touch with the current technological trends.
They need some diverse intelligence. And he's advocating, Hanson is advocating for a blend of fluid and crystallized intelligence within the leadership team. Yeah, implying that there's a, a mix of youthful innovation and seasoned experience that could better navigate the, the world's advancements. And if you compare that to other tech giants, so he noted, like Meta, their board members average ages 55, with three of them in their 40s. So suggesting that the, the younger leadership could be beneficial for staying abreast of the technological shifts and trends.
[00:20:47] Speaker A: I don't know that Meta is like the best comparison given their track record. And they're losing user base on Facebook.
[00:20:52] Speaker B: But yeah, but at the same time, I think again, that acquisition of Instagram and so on, they got people like locked in for certain platforms. But I mean, one of the things that he did mention when I was reading through like this Gen Moji, like who came up with this thing? Do they actually think that this is what people want? And I look at the, the one that you, you know, found or came across this Jon Gruber stuff. Like even I like that one story where it talks about like this mobile me. And I, I'll tell you, like, I. I actually had a mobile Me account back in the day when I first.
[00:21:30] Speaker A: What was mobile me again? I forget.
[00:21:32] Speaker B: And so mobile me was their version of email.
[00:21:36] Speaker A: Okay, right. You can still do email with icloud now.
[00:21:39] Speaker B: Yeah, it's. It was, it was basically the same thing, but it was the precursor to iCloud. It was the, what they created. I mean they actually. And I still have my, the, the, you know, @me.com but you had to pay a subscription and that was the only way that you could go and get push emails to your phone, your iPhone. So that was, that was kind of like the big seller and everything would kind of synchronize or what have you. But in this article that from Gruber, he actually put in how the whole process and now Steve Jobs and keep in mind, like Steve Jobs, even later on he was only, what, like 53. And so again, he was like younger and. But he berated the whole team and told them that, you know, you're tarnishing the Apple's reputation and so on. And so the, you know, again, these are, these are things where I think he was notorious for.
[00:22:33] Speaker A: Right.
[00:22:34] Speaker B: Like he wanted before you ship out anything like you would make sure that it works 100%. It's not going to impact the.
[00:22:40] Speaker A: And how the company addresses errors is also a big deal in returning and maintaining goodwill. Right. So there hasn't been a lot of public acknowledgment from Apple regarding the missed AI features that it has yet to ship. And the features that it's already shipped, which are pretty simple like email summary, text summary, have had some hilarious consequences, just like silly summaries missing the understanding. And so even that has been a bit of a boon or a bonanza for them because it's not working as advertised.
[00:23:14] Speaker B: Yeah.
[00:23:15] Speaker A: And so they haven't officially walked it back in the same way. It's not like Apple Maps, where it was kind of a disaster. Tim Cook wrote a public letter so you Kind of see mistakes are inevitable, but there seems to be some sort of inability to kind of face the music.
[00:23:33] Speaker B: Yeah, yeah, for sure. And who knows? I mean, this is. If you look through history, there always is this kind of issue that once you're like the dominant company, maybe like you, you know, there's, as Clayton Christensen talked about in terms of disruption and so on. Right. Like there's. Maybe they're kind of stagnating and I, I still feel like, I don't know, maybe I could be wrong. I feel like the, even though they aren't the first to this whole AI side of things, I, I feel they could probably still do a better job if they can get their act together because at the end of the day this AI, like it's, it's just a matter of making the average person's life easier without knowing it's AI.
[00:24:23] Speaker A: Well, and I think too, it kind of touches on. I'll just send you a link because it's one thing that I think we could talk about.
There seems to be with these tech companies an issue where there's, It's. Their products are becoming increasingly complex to the point where I don't think that they can be well maintained.
So to give you an example, mobile phones like desktop computers like the Mac and Windows, they change their interfaces, they get design updates which are fine, but you know, there's core fundamental operating functions, you know, how the File Explorer works, gestures, they, they haven't really changed that much and they still sell very well and they're very valuable products. So when I want to buy a new Mac or if I was to buy a Windows Ultrabook, I'd probably prioritize based on the quality of the hardware, battery life and how much support I'm going to get. So I can keep these things for a long time. And it doesn't seem to be a problem that they.
The number of additional features or the refinement of features on that particular platform is slow. And I think we're kind of getting to that point on the mobile side. So the number of features that you can realistically introduce into a post PC device like a tablet or a phone is kind of reaching that limit. And it's kind of to the point now where it seems like they're starting to prioritize features like you said, that nobody really wants and nobody really asked for to differentiate. So the genmoji image generator, which I can't really get to work that well, to be perfectly honest, is a software example. But what about, what about these rumors of folding phones. I haven't, I haven't seen the sales on folding phones, but I don't know about you, but it's never been interesting to me. I have no desire to have a really thick device that folds up.
It sounds like so many points of failure.
I don't need a larger screen. I guess the idea is that you would have device consolidation potentially, but it's not a super appealing factor for me.
[00:26:37] Speaker B: Yeah, yeah, no, absolutely.
I mean even like I'll tell you Eric, like this past week I had a, a meeting with a client. And that client, it's actually in the healthcare space. So he's a doctor and he got a new Mac Mini because everything else is like PC based because of, you know, their software and the EMR and all that kind of stuff. So anyways, the new Mac Mini because again he decided I want to have Mac. And then you know, he has a monitor but he didn't get a webcam. And then I'm like, hey, did you know that you have, because he has an iPhone, like you have this continuity camera, right? And which should have worked. It didn't. We were having like a zoom meeting and stuff. It didn't work in the past, something like that. It should have just somehow worked out. And I, I don't know, like usually it just has like NFC or like some sort of just being on the same WI fi just somehow the devices connect to one another and figure it out. And so again, like I, I think that would be, it is a kind of a cool feature and stuff. But yeah, like I'm even getting to the point. Like I've told you before, like I, in some ways we've chatted about this in past episodes, but I don't know if I even really like having a smartphone that much. I, I, I think that it's again, it's just comes down to their sales and everything that they want. I think I could be perfectly happy just having an Apple watch just for like phone calls and stuff and maybe not worry about. And you know, again, I kind of envy like one of our colleagues has an iPhone, never uses it, touches it like twice a day just to see if there's anybody who's called them. I wish I could be like that. And then I just, you know, have to go in front of my computer to look at like emails or whatever because emailing is not real work. It really is a distraction that takes you away from other things. And even the, from a phone perspective, there's only a few people that actually call me that I need to talk to. And they're usually family members. Right. So again, I, I don't know, I mean there's things that we could kind of simplify our lives quite a bit. But it's this whole, I mean, going back to like that documentary because these companies have to push products to go and make money, to go and increase their shareholder return and you know, deliver their earnings per share and so on and so forth. So they have to find some way of pushing product on us. And in the long run, I mean, even the one thing that they could easily do that Apple doesn't want to do, and none of those tech companies in that documentary talked about or like had a solution for was that end of life thing. I mean, wouldn't it be great if you could just go and literally like take your iPhone to Apple, get a new iPhone from them and then they could take that, dismantle it and recycle the whole thing and put it back into like new iPhones. But they won't, they'll ship it off to some, you know, other country to have their labor to go and you know, deal with without like property kind of gear and stuff and who knows the safety repercussions on their bodies and stuff. But whoever comes up with that and I, I see like even Ikea's talked about it for a while, like where you can, let's say you, you buy a piece of furniture, we know it's not going to last forever, but you take it back to them. If they can go and sell it, they can put it in that, you know, the, the, what is it, the pre owned stuff or whatever, that one section at the front of the store and, and otherwise they'll just somehow recycle it and then, and they'll give you a gift card, right, that you can use towards buying more stuff or whatever. Like there should be more of this like circular kind of economy thought process, but there isn't, for whatever reason, and I think especially for electronics there should be because those rare earth minerals, you could, I would think, I don't know. Again, I'm not a scientist and I don't know anything about this stuff, but I would imagine there should be some way to go and reuse it or we should maybe think a little bit better in terms of how we design this stuff so that we could go and repurpose.
[00:30:43] Speaker A: I mean, you make a good point. It probably comes down to something like motivation, like the cost of selling another one is so much greater than the cost investment for figuring out how to properly dismantle and do all that stuff. I'm sure there's an economic incentive to not do that since that's how companies work. You mentioned end of life. I think about that when I purchased an Apple Watch. In fact, one of the things I'll say is that the Apple Watch is my favorite of the Apple devices because I can't really do anything too complicated on it. I can get some of my messages and someone texts me. I can make a phone call from it. That's actually fairly good.
I mean, it has to use my iPhone, but it does do speakerphone relatively well.
And it's a very simple device that sits on my wrist passively. It's a great health monitor, but one of the concerns I have is that it's relatively delicate. Mine has quite a few scratches on it. You know, how long is it going to last? The battery life is fine. You get about a day, day and a half out of it. But, you know, I would also be willing to trade a lot of the high contrast display, the features for a battery life that lasted a really long time. That just did a few things really well. You know, the basic heart monitor and activity tracker is all I need. I don't really care if they add more workouts. I don't need an ecg, I don't need more apps on it. I don't need to play games on it. There is rumors that they want to bring Apple intelligence to the Apple Watch and I have zero interest in that whatsoever. I never use Siri or an assistant on it. And in fact, one thing I just sent you, I forgot to bring this up with you earlier. Is that. So you remember the Pebble Watch was kind of the first open, was the first smartwatch platform. It actually started on a Kickstarter campaign. This is about, I think almost 10 years ago now.
[00:32:33] Speaker B: Yeah.
[00:32:34] Speaker A: And it was an E Ink display. The battery life was about seven days and it was a Kickstarter.
Excuse me. And it was. Eventually the company was acquired by Fitbit.
Excuse me, one more time here.
[00:32:52] Speaker B: It's kind of cool too, because the founder of pebble, he's also Canadian born. And so then he went down to Palo Alto and, you know, did this, this whole thing.
[00:33:04] Speaker A: But they were acquired by Fitbit. Google acquired Fitbit and then of course they rolled Fitbit into. So all these acquisitions have happened, but pebble was kind of lost by the wayside. There's still people who use the original Pebble Watch. I think it works better on Android because people have been able to kind of keep it alive. But what Google did is they took that operating system that that smartwatch platform was designed under and they actually recently open sourced it. And we can put this in the show, not because they open sourced the os. You can't go and create a Pebble Watch with that name because of course the trademark for that product is still owned by Google though maybe they'll give that up at some point. But now the original founder of Pebble Watch has actually gone and created a new company.
I'm trying to remember what the company is called. It's called Repebble is the store and then he's created the two options, the Core 2 Duo and then the Core Time 2. The Core 2 Duo is kind of like the non touchscreen black and white E Ink smartwatch and the core time 2 is a slightly larger basic touchscreen color E Ink display. And you know these are metal frames, heart rate monitors, barometers, compasses.
They have a very simple kind of interface where you can make your own watch face. Of course because it's E Ink like an E reader, it works really well. They have a 30 day battery life, water resistance. But one of the and theoretically any company can now go along and make hardware that will work with that now open sourced pebble os.
Awesome. So this is much more sustainable from a lack of a lock in.
[00:34:42] Speaker B: Yeah, well even like I mean that's amazing if it has 30 like you know I have my Apple Watch 5 and Eric like I have to charge it like twice a day now. I mean I could probably.
[00:34:53] Speaker A: So when was that released?
[00:34:55] Speaker B: I would say it's been a while.
[00:34:57] Speaker A: 2017 or something.
[00:34:59] Speaker B: Yeah, something like that. And yeah, I'm sure I could probably replace the battery but guess what, it'll probably be cheaper and like you know you to go and just get. I mean. Well I guess a new Apple Watch is still going to be like 4 or 500 bucks and then we I get tied back into the overall buying crap.
[00:35:19] Speaker A: Well I mean I think the idea though that buying something that's you know, hit its end of life, let's say you've had it for seven or eight years, isn't necessarily the end of the world. I think if you said you know, I'm going to wear an Apple Watch on both wrists and you know, you took it to some extreme, that would be different.
[00:35:34] Speaker B: Yeah, exactly.
So it looks like it was released in 2019.
[00:35:41] Speaker A: Okay, 2019 I have the se, the second generation.
So I don't have the always on display and things like that.
[00:35:49] Speaker B: Yeah, even That I turn it off. I mean, I could do it, but then it drains the battery. So I just, I don't know if it's any. Even the. Actually even on my iPhone, I turned it off. I don't know if having the screen on all the time really helps.
[00:36:01] Speaker A: Yeah, I don't know.
[00:36:03] Speaker B: I don't know. But see, these are things that like I again, like you say, and I think it goes back to the core of what we're talking about with Apple. Like they come up with these ideas. I don't know if just basic thing is you should talk to your customers whether they want the screen on or not. Like, do I really care to have my screen on 24 7? Probably not time, right? Like, I mean, I even, I kind of find it freeing a little bit now. Like Eric, I would have my watch on all the time now because the battery is dying. I just go and you know, charge it like before it hits the, like the, the red, like the 20 or lower. And then I forget about it. Sometimes I forget that I even had the watch or whatever. And I'm doing my thing. I don't know if it really, for whatever reason in my head, like I thought, okay, well, I'm keeping track of all my, the steps and all these kind of things and my heart rate and all this. I don't know if that data is ever going to be helpful for any purpose whatsoever. And so I'm kind of walking away from it. But who knows? Now I might go, maybe when Black Friday comes around, I might go and get the cellular version that they'll probably release it later in the year anyways.
[00:37:19] Speaker A: So to have my battery on my Apple watch replace is $135, which is now a disincentive for me to do it because it used to be, you know, for the phones, it used to be like 60, 70 bucks. And so now if you can buy a brand new watch for, you know, 300 or 280 or something, is it really worth it?
[00:37:41] Speaker B: Yeah, well, and that's the problem, right? Like, I mean, you look at the cost benefit, you have old technology and most people, they see it as a disposable. And again that's, I mean, I wish if Apple and this is the other thing, like sometimes I don't know what the recycling program is or what have you, if they actually do anything with their devices or if it just goes to Thailand or something and they started getting some, you know, cheap labor to go and dismantle this stuff without the proper gear and stuff. But I mean if they just gave some decent amount because it's your own product, I would probably give it to them before anybody else. I mean even Eric, I have like old iPhones that I would give it to them even for free, but they won't even accept it.
Right? Like so, like, although I haven't looked in a while, maybe they've changed, but this is where like I think it's, it goes back to their core kind of credibility. And if you recall, there was even that one interview or not this interview, but it was a stupid like commercial video that they created with where Mother Nature, this one, you know, actor came in and is like, oh, Mother Nature's coming. And Tim Cook presented to Mother Nature and all this like crap about sustainability and stuff like that. But like, I don't know, again, looking at that, the documentary, whether we like it or not, I mean the one thing that going back to like from a takeaway is that not only Apple probably paved the way for everybody to go and take that mentality and they were very successful at it. And to the point where like all electronics companies are basically looking at their devices as disposable.
[00:39:32] Speaker A: Well, and I don't really understand how they measure like net zero or carbon neutral products. So does the company use more recycled goods or can they get away with that by just buying carbon credits? Like, I don't really understand the mechanism. I'm sure that there's multiple. Just like a company can either grow by increasing their revenue or increase costs by, or sorry, by increasing their bottom line by cutting costs. That's a ratio. So I'm sure that there's multiple ways to get to some sort of carbon neutral product. But it's not, not very clear to me how that, how that happens.
[00:40:12] Speaker B: Yeah, who knows? This is where again, it comes down to transparency. And I think a lot of these companies, it's, they just, they go and communicate what we want to hear so that we keep buying crap.
[00:40:27] Speaker A: Well, speaking about carbon neutral and things that eat up all our electricity and electrical grid, I thought maybe we should pivot back to our favorite discussion about AI. So I, I've been trying to read about AI trends on higher education. Many of the articles that have been posted are largely what we have already discussed here. So the Times of Higher Education, the Chronicle of Higher Education, they talk about AI trends, they more or less say the same thing, which is that academic integrity training, how to be efficient, teach students how to interpret the information critically. I don't see a lot, lot of movement on trends since generative AI tools kind of became more ubiquitous in an education context. So I thought maybe what we could do instead is give users some, or give an update about some of the ways that we're using these tools and maybe provide some tips for what people can do next.
So is there anything that you're doing differently when using these tools? I mean, you and I were talking about prompting earlier.
[00:41:32] Speaker B: Yeah.
[00:41:33] Speaker A: What are some ways? I mean, prompting is a good question that I get A lot of the time. I think that I feel like I'm becoming better and better at prompting, but perhaps that's an area where people are not confident.
[00:41:45] Speaker B: Well, and, you know, and when we were chatting about this before we started, like, one of the things, I feel like the industry, this whole, like, you know, with generative AI, things are moving so fast that it's, it's hard to kind of keep up. And it may even get to the point where maybe like, prompting isn't even a thing. Like, it's not even a, a big deal. Because basically the, the technology, I mean, as you see, like I, I look at certain platforms, it actually suggests the prompts to you, but again, that's where I think you got to go and use your brains and so on. But I feel a lot of it, it just comes down to going and experimenting with the tool and it's, it's a bit of trial and error.
People do need to. Some of the general principles, I feel is you, you gotta understand how this technology, this large language model technology works and how it functions.
The fact of the matter is that the people who are designing it, they don't even understand. Right. Like, they, they, I recall that one.
You know, There was a 60 Minutes episode with all the top Google people and somehow like their AI large language model learned Hindi even though it was trained in English. And, you know, they had no explanation for it. But at the end of it, I think what you do need to go and understand is that it may sound really smart, but it comes down to like, it's taking whatever we put in there and converts it into those tokens and then, you know, tries to figure out based on probability. And so again, I feel that you need to go and understand like the, the engineering, I mean, they keep, they call it prompt engineering, but you have to understand how the engineering works. But then you got to think about just in terms of when you're crafting, because it doesn't understand English. So you got to go and put together that prompt in a way that it'll go and generate what you have Envisioned. And there's different tactics that people are doing, like taking Personas.
You know, I, I think sometimes I feel, I don't know, I. And I, who knows, maybe I could be wrong about this. But I, I feel that you should be concise in terms of your, your prompts. Like, you could throw in tons of stuff. I mean, I, I did this just as an experiment.
Just this past week, we had a library session and I thought, let's, let's just see ahead. You know, the librarian come in and let's use deep research. I threw in my instructions and stuff, and for 20 minutes it just came, Kept going and came back, spit out this report. It looked halfway decent. I think if I had to go and grade it, I'd probably maybe give it like a C for satisfactory to maybe even, you know, like a B.
That's just at face value. But then you, you gotta go and check the data. Like, it had 168 sources. Of those sources, I started going through. And this is where you got to think critically about it. But like, much of that stuff was just, it was total garbage. And so I, I feel that it goes back to, you know, you got to go and experiment. You gotta, you know, go back and forth. It's a bit of a dialogue. And what I've been telling my students is you want to get it to a point where it's something workable.
You get it to a point where it's workable, and then you massage it, put your own voice and, and, and so on to it. And especially I think where, where it has the most right now, especially like most of the, Where I'm going and delivering the business communication courses.
That's probably the best application for this technology where it sounds right now. I've even had some students, they were doing some big, like, as part of the business or not. The Bachelor of Computer Information Systems, they had some coding projects. And what I found, like, the most of the students were stressing out about it, and it was going to take them like basically the whole weekend to complete this one project. And then I, I don't know, somehow it came in conversation. And then this one student told me, hey, yeah, you know, I completed in like 20 minutes. And what he used was Claude, because Claude's large language model is much better suited for coding. I don't know if they're allowed or not. I mean, it's not my course. But, you know, again, at the end of the day, does it really matter? This is a tool just like any other tool. And so as Long as you understand and you gotta, you're responsible for making sure that things are correct. But if it does the job and it makes your life a lot easier, then it's probably a good thing.
[00:46:38] Speaker A: I, I also think too that when people are developing prompts, they're much more likely to come back with accurate information if the prompts are very specific, right? So like if I, I had an example in one of my library guides, so if I upload a document and I, I have this listed somewhere, is that if you upload a document to that you want summarized or that you want to help. I think the example I use is that here's a document that I've uploaded. You know, I want you to help me generate additional kind of educational content based on what I've given you. So it's kind of like an example prompt could be super long, right? So I think I had something like, based on the content provided in, you know, and then blank could be whatever it is that you've uploaded, please. And then I actually listed out, one at a time, the things that I wanted the AI to bring back. So, like summarize the key points focusing on this, this and this. You know, identifying, identify potential gaps or controversies within the, and pay attention to these particular areas.
Summarize or create a list of reflection questions based on this chapter and this chapter, particularly these sections. And then when it brings back content, it's much more likely to be accurate. Another thing that I've done in the past, especially when it comes to summarizing documents, and I did this recently because I created a custom GPT, I was working with a colleague and he said, could we use the provincial budget in Alberta dropped recently? And he's like, do you think we could use ChatGPT to do an analysis based on all the documents that are released by the government? I said, well, it's public information, so we could do that. So I made a custom GPT on the Alberta budget, but one of the things that I asked it to do in the instructions for the GPT was a only reference the budget documents, unless prompted otherwise to find ancillary information on the Internet. And then it was pretty good at following that. And one of the things that I asked it to do in the initial instructions, but for whatever reason it doesn't stick to, but it does it if I ask it on a prompt by prompt basis, is to provide page numbers for the information that it finds from the documentation that I've uploaded to it. And then that I find is really quite helpful because then I can spot check a handful of them and in general, when I ask it to do that, it's quite correct.
[00:49:13] Speaker B: Yeah, that's a good idea. Yeah. I mean again, you have to kind of understand how the technology works and how can we create these constraints to get the best outcome.
[00:49:25] Speaker A: And so I think this idea, it kind of speaks to this idea that you talked about recently and we were talking about this earlier. A piece of advice that we give people is that, you know, these, these tools come out all the time. You know, AI is kind of being infused into all sorts of tools. I often use it within notion. But I think something that's important to remind people about is, and that you mentioned this is to kind of master the tools in front of you rather than kind of jump around all the time.
[00:49:51] Speaker B: Yeah, I mean again there's, there's thousands of AI tools out there. Right. And I, I find like there's some people that I know, they, they hear of the, the new shiny kind of object or what have you and then they start going in that direction. But really at the end of it, like this prompting side, I think when you go and experiment, chances are right now in the near term many of these large language models are acting the same. And so as they roll out features, those skills are probably going to be transferable. But at the same time, you know, stick to what you know. Why do you need to go and you know, have to be doing like using a, dozens of different large language models unless you have specific applications for it? As far as I'm concerned, I'd look at it and we were chatting about this too, like literally, I think you only need to focus in on like maybe one or two, maybe three at the most right now. And right now if I was to rank it probably the best one still compared to everybody else. And it's probably because the, you know, they keep using the argument that if we don't do it, China is going to do it or what have you. But it's OpenAI and their chat GPT is probably the, the strongest one for most of our day to day applications. And then as we were discussing like this, the CLAUDE one is on par.
And then for certain things like, like that example that I gave you, like from a coding perspective, the, the Claude one is better than ChatGPT. So I mean if that was your application that you're doing, I mean you mentioned that maybe you might even switch to claude.
[00:51:32] Speaker A: Yeah. So my understanding is that claude's data set is a little bit more ethical. One thing I'll point out about Anthropics, Claude is that Google owns like 13% of that company.
I don't think, I don't know if as an outside investor or if they just bought stock. No, it's not publicly listed, so it must be some sort of private equity deal. But I've heard that Claude's model doesn't incorporate like everything that's been scraped from the Internet. It tends to include things like Reddit, I think a bunch of, you know, maybe the more extreme forums on the Internet. So it tends to be a little bit more railed, but in a way that doesn't give kind of the wild hallucinations, but it still gives very thorough answers.
I've done some research, you know, just reading on, I mean, I go to Reddit to see there's a subreddit about AI that's really helpful because people could kind of provide their experiences comparing the different tools.
So some people say that the Claude has a huge context window and actually uses it.
So you'll notice kind of, they say that one person says you'll notice a degradation of the replies when you reach the limit of a context window. So Claude tends to give more consistent answers, I guess longer maybe as you get closer to your token limit.
I have read from people's experiences that the reasoning models, those are the models where it kind of double checks its work as it's providing you the answer are significantly better.
So they're kind of just more consistent, more reliable in that way. I've read that some people have said that Claude is allowed to explore more philosophical themes, so it has a lot more freedom.
So it'll be more likely to say it doesn't know if it can't answer something or just be a little bit more upfront if something falls outside of the corpus of knowledge that it was trained on.
But then I've also read that it has a much higher refusal rate, which is kind of frustrating. So it just won't do certain things compared to OpenAI. I think it only recently got the ability to do live Internet searching and scraping. And of course if you go to Claude, you don't get any of the video or images, image generation tools with it if you have a paid account or things like that. I haven't worked too much. I don't know, I mean, I don't understand. I feel like there's some missing information I have about how the models work. I mean I have had, I heard that people do criticize like ChatGPT 4O versus 4 I really like O1 as a reasoning model.
But then I've heard that 4.5 is a bit of a bust because it's focusing on kind of phrasing and empathy rather than accuracy and quality. So they're kind of. I, I don't.
[00:54:33] Speaker B: I'm not.
[00:54:33] Speaker A: I'm more interested in an AI tool that, that focuses on quality and accuracy rather than coming across as a real person. I'm not looking to pass the Turing test. I'm thinking about it in terms of productivity and how it could help me synthesize information so I can make come to my own conclusions. So I haven't decided, but those are some things that I have read about Claude. What I really need to do is go and use it and, and test it. The, the, you know, it's. It's not that I'm afraid to switch because I think the switching costs between these models are still pretty, pretty easy. I don't lose a lot by going to another. It's more that, you know, there is just a financial cost. And I already know how to use ChatGPT and how to voice things to it in a way that I get the responses that are the most helpful for my own productivity. So it's hard to kind of. If something uses a very different approach or has it is trained on a different model, it might, it might require a huge learning curve for me, which means there. It might not be productive for a while while I'm getting used to it. I guess that's possible.
[00:55:36] Speaker B: Yeah, no, for sure. Actually, you know, one for coding, I've.
[00:55:40] Speaker A: Heard Claude is better, but I don't really use it for clothing. I'm really using just text, so.
[00:55:44] Speaker B: Yeah, yeah, no, exactly. I'm just using it for text for the more most part too. One thing that I found kind of, that was kind of cool and again there's like these thousands of apps that are out there. But I had a meeting about, I would say maybe about three weeks ago or so and at that meeting, this. One of the people that was attending attends a lot of meetings and he mentioned, hey, do you mind if we go and get AI to record this whole meeting and then transcribe it? Right, okay, sure.
And the tool that they used, it was called Firefly.
Firefly AI. And so it was kind of cool because it actually took the audio, took a, you know, transcribed everything and then if, let's say the AI did not make out the transcription was incorrect, you could go and double click on it and then go back to the audio and actually listen to it. And so you know, I thought that was actually a good application and in fact I needed to go back because we were writing some, some stories right now and just some, we're looking at doing some press releases and that kind of thing. So I had to go back to some of the points because there was some really good things that we could use for, from quote, perspective and so on. So again, you know, there's, it just comes down to, you know, what are you using that tool for in the application? Right. And so I wouldn't, I wouldn't just go and get subscriptions to every single thing out there. And I guess that's the other barrier too, right? Like, how much money do you want to be spending on this stuff? I mean, I, I look at like, you're right, that, the analytical one. And again, I, I wish that these people would actually talk to their customers and what they want. Like, I don't know, it seems like a common trend with these companies. But I'd rather have quality versus anything else as well. And I, I do find that reasoning model is much better in terms of the performance. And you are right. Like if you keep going in that conversation. I've mentioned this to people before, people have this assumption because they just think, oh, okay, well I'm, I'm going and having this conversation and it's going to keep referring back to the, you know, that dialogue and so on that it'll remember the, the original, let's say documents that you uploaded or what have you, you. But it doesn't, at some point it craps out. And so you do have to be kind of aware of the, that And I guess it just depends on what you're, you're trying to do, what your goals are.
[00:58:21] Speaker A: I don't, I haven't. So I agree with you that the reasoning models are. One of the reasons I like them is they kind of provide a, they show their work like what it's doing and it kind of shows a little transcript of how it's answering your question and how it's thinking about it as it's working. So I, I often just watch that because sometimes I go, oh, I see where I can see where it's going wrong. Maybe my prompt needs to be improved. So, because sometimes the problem isn't the AI, it's me. I haven't, I, you know, I've made a description that you would understand but is actually nebulous without, you know, inferring something about the person that it doesn't know. So sometimes the user is the problem and so I like that about it. One of the things I don't, haven't tested a lot is this O3 mini. So you can use the O3 mini and O3 high is.01 still the better of the reasoning models over O3, the mini?
[00:59:20] Speaker B: I, I would say so, but I guess it depends on what you're trying to achieve. Right? So I mean if, if it was something basic, I think, think maybe like the mini might be okay. Like let's say it was like an email or something or some sort of basic correspondence. I think it would be more than sufficient. But yeah, for the most part a lot of the things that I'm kind of looking at is like I'm looking for some sort of trends or some ideas and, and if I have a large text that I, I'm going through like what are some of the general points or the takeaways that I can, you know, use.
I mean again, it's not a hundred percent right. Like I think I mentioned to you, like even I, I tried to create a case study using that, the analytical model, the, the O1 and I used the deep research and instead of, you know, I provided the instructions. I was pretty clear in my prompt. I'm like hey, I need a case study that's two pages long because they won't have the attention span. I don't want to answer the questions. These are just for your background purposes. The, the instructions and so on. Instead of doing what I asked it to do. And this was the last time we were recording, it actually produced a full on report and answered the questions. And so I was not really happy with that. I mean we were recording so I just thought let's do it as an experiment. And ultimately I ended up writing everything from SCRAT on my own. But again it, it, this is where I think the, if, if anybody takes anything from this is that you got to experiment, you got to go and try this. I, I do agree with you Eric. Like, you know, the one thing I do like is seeing how the AI, you can see the whole log of what it's doing, what it kind of information it's pulling. And I feel from that I'm learning how the, these large language models are functioning and I can do better in terms of putting together those prompts.
[01:01:24] Speaker A: Yeah, I think 01 is still the most advanced reasoning in general.
I think if they released a full O3 it would be better. But O3 mini is faster but less accurate. O3 mini high is more accurate, but I think still O is the most thorough reasoning model. And so again I think those are probably best suited just for people listening when you're doing math computational questions, I think the reasoning models are best. But even for generating just general answers and text summarizing documents, I did find that the outputs for O1 tended to be a little bit shorter but better, more accurate.
I don't know. It would be interesting to know what, when you make a custom GPT, what model is being used?
That is a good question because I don't believe you can go in and select it.
[01:02:25] Speaker B: Yeah, if I was to guess I would probably think it's just the regular, like what is it? The 4 point?
[01:02:33] Speaker A: I feel like it's 4o maybe the default but so that's one thing to check out. I will say though that as I, like you said, as I get more confident using these tools and becoming more expert at using individual tools, I'm less interested in kind of moving on to a new one because I feel like if another model is way better at coding but slightly worse at something else, I mean they're all going to work to some degree if you invest enough time and understand how they function. I think what I'm most interested in in the future is figuring out how I can run these locally and I'm excited about models that will run locally without like a huge GPU that I have to attach to my Mac.
[01:03:15] Speaker B: Yeah, yeah, exactly. I mean I just wish like that's the thing, like you know, Apple has the potential there, you know, and that was kind of like what they're pitching just to run these local GPUs with the privacy and all that kind of stuff. I, you know, like we have the ability if we want, I'm just not going to do it. Like we've talked about like with Chat GPT, I'm not going to go and give it access to my drive and all my documents. I'm just not going to do that. I don't trust them. I mean if they took everybody's writing out there and you know, without their permission, what do you think? Even if I pay for this thing, are they gonna go and not, you know, take advantage of everything that's on there? That's the same reason that I, I look at even like Deep Deep Seek, the Chinese large language model which apparently they have built for much cheaper and it's producing sim somewhat similar results when compared to like Chat GPT or even Claude. It's, it's still not as good, but it's not bad if they are actually truthful in terms of the, the processors that they're using and the money that they've invested. But again, I, I don't know if I trust them with my kind of information and I'm not dealing with anything secretive. But again, it is something to be mindful of. And so again, it goes back to.
I would be very cautious of what you input to any of these large language models. You know, when in doubt, always remember, just because this stuff is digital doesn't mean that it's, it gets erased or something. If you should treat it like it's actually worse than having physical documents because hypothetically it could be in existence forever. It could be on somebody's servers. Right.
[01:05:12] Speaker A: I turn Apple intelligence off on all my devices, so because I don't find it very helpful, I find the Siri is worse.
So setting timers and doing stuff. I actually prefer the old version. So I just turn it off.
[01:05:26] Speaker B: Yeah, I actually haven't turned it off. Well, I turned it off and then I turned it back on my phone actually. I don't know if I have it on my Mac, but I actually still. I like that little feature that they had for summarizing, like the summarizing the emails that come in.
[01:05:47] Speaker A: I found it. Okay. It didn't really help me a whole lot. Yeah, I found, I found that it.
Yeah, for whatever reason, it just, it didn't, it didn't really work for me that well. It didn't summarize things very accurately. So for that reason I just turned it off.
[01:06:03] Speaker B: Yeah, like, I mean, I'm not looking for accuracy per se, but at a quick glance, like if I'm in between meetings or classes, I, I see an email. It summarizes in one line what that email's about.
It's not bad. It's, you know, I think there could be worse kind of applications, but I think that is not a bad kind of option. And so again, they need to go and they got to figure their crap out and hopefully their changes in leadership or what have you. I mean, it was supposed to happen before, but yeah, it's definitely going to impact them. Hopefully they can turn things around. But if not, again, they're like the best of the worst from the big tech companies. So they're all equally have some issues.
[01:06:52] Speaker A: Well, that sounds like a good place to end it for now. So we'll tell people, be careful what you wish for and be careful what you use.
Focus on mastery over collecting tools. Yeah, okay. Well that sounds like a great place to end and I guess I'll catch you next time.
[01:07:10] Speaker B: Yeah, for sure.
[01:07:11] Speaker A: Take care that.
[01:07:13] Speaker B: You, too.
