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The following video transcript is generated automatically by a computer algorithm that learns and gets better on a daily basis. Please accept our apologies if some content below doesn’t make sense:

[00:00:00] Hi, everyone. Welcome to the Daily Dose podcast. This is the podcast where we pick out things that we spotted in the news and social media that’s interesting to us as entrepreneurs and as real mostly lives, semi functioning human beings. I’m James and I’m joined by my co-host, Marseillais Miserly, when it kicks off with the first topic I made. [00:00:19][19.5]

[00:00:20] Thanks for the intro. Yeah, sure. So begin from Twitter on other media outlets. So Harvard is going to charge a full tuition of 50 K for doing classes remotely from next year. [00:00:30][10.5]

[00:00:31] I mean, my first reaction will be this is nonsense, but we can talk about economics on what’s going on with the education system, especially in the US, but partly in the Western countries. So we see it even worth going to university or what can you do, like start your business, be an entrepreneur like us? Let’s try to look at this from a nonbiased point of view. So I’m strongly biased, so I will try. Well, it’s. The thing is, Will. Forget some respect to Harvard. We’ll need to know more specifics on how they plan to build up that content or if it’s for all courses. So what will be the value that they try to deliver on that board? Certainly looks like pretty steep. And yeah, as many people are taking that to get to that 50 K as well. So which will make it worse. So this is a huge burden. I mean, one of the reasons we started networkers was to tackle these problems specifically on how universities in general are not or are struggling to catch up with technological progress. And they’re not really preparing people for the jobs of they’re not not the present leave a. Let alone the future. So, look, I’ve been through university. I’m not the classic dropout entrepreneur. I started online businesses, very, very young age. Are you and trading online at twelve on first businesses at seventeen. But but then I went through all university post graduate and. Yeah. Well my personal impression was that what took like five, six years could have been done in one to have two broadly sided international business. Probably. It’s not like I’m like a science career that you can shrink or or go to a point. But certainly the incentives are not aligned on on. Yeah. What people are expecting when they get out of university. I mean, it is still an industrial age education system. You need to go to class or take certain modules which build up over modules and then you call a lot of fluff there. So I would think definitely not value for money or you should at least break it down, make it more modular. [00:03:25][173.4]

[00:03:27] Yeah. [00:03:27][0.0]

[00:03:28] And I’m not so sure how they will be able to justify this over time. I’m sure still many people would like to go to Harvard. This by inertia. It will be difficult to change behaviour of the masses. And also these universities, and especially if they do it remotely, they can. They have a huge audience. I mean, worldwide. Whereas before students need to get visas on this and that if it’s globally, broadly there, they can cut her out. What a wider audience. And they’re just trying to take advantage of that, basically. So. So it’s not they want to make as much money as possible rather than yet deliver transformational change, which is much needed. I mean, they should be leading innovation and discoveries. And I’ve not seen that many groundbreaking discoveries coming from universities for quite a while. I mean. Yeah, compared to last century for some. [00:04:39][70.9]

[00:04:40] Yeah, for sure. I think what it does do is it it I think it really shines a very strong light on the reasons for people attending those particularly Ivy League universities, because essentially, you know, a university is ostensibly a place to learn and that the the top you know, the Ivy Leagues and the Oxford views of the world are the best places to learn because they have the best teachers and the best coursework and the best research opportunities and all this kind of stuff. But in essence, what many people actually use their Ivy League education for is a golden ticket to the job market. And that’s what Harvard and the rest of universities are getting away with, is not. Is the value proposition of that is not so much the quality of the education, but the fact that it’s highly selective in order to get into it and that you get given at the end of it, a golden ticket to go out into the market and sort of have your pick of the best plum jobs. And so now this is really the case of that. It’s got to be very hard for them to argue. For Harvard to argue, hey, look, you know, you’re getting a load of other intangible benefits by attending Harvard. Now it’s purely down to, you know, either you’re going to go out into the job market with a Harvard degree or you aren’t. And how much is that worth? It is. You know, if they’re charging 50 grand a year for tuition, then, you know, are you willing to spend two hundred grand on the golden ticket to go out into the market? You know, how much extra money can you earn in the market with a Harvard degree versus not having a Harvard degree and putting the opportunity cost of four years of education? You know, you could put towards something else. And I think it’s especially interesting and and sort of highlights some of the issues that are there because. For example, M.I.T. for years have had a thing called Open Courseware, which is basically any M.I.T. lecture. You can go online and register for free on the M.I.T. platform and view all of the lectures on any of the topics, you know, that M.I.T. teaches. So you can get an entire MASC education without actually having to spend the money. You don’t get an M.I.T. degree at the end of it, but you can take all of the education portion of that and you can do that online for free anyway. So essentially what Harvard are offering here is the equivalent of what you can already get for free from M.I.T., but. With a, you know, a Harvard degree at the end of it. And so I think a lot of people are saying, right, well. Why? You know, even if you do want to go through with a Harvard degree, why? Why do it this year? There’s no point. You may as well take a gap year or whatever these sort of international equivalent to that is. And, you know, try and learn different things, do different things, like have a stab at something entrepreneurial in that year and then go back go to Harvard next year when hopefully, you know, if things improve, then people will be upset. Go back to in-person education. But you’ll go with a whole New Year’s worth of extra sort of skill set there. I’ve seen a lot of people on Twitter, a lot of entrepreneurs actually sort of, you know, science people like don’t bother going to Harvard, come work for me in turn for me. Like, learn a skill, do a thing. And it’s a very you know, it’s it’s quite compelling. Why would you drop that kind of money? [00:08:10][209.8]

[00:08:11] You know, like, I agree. Hundred percent. But that’s bias because we are entrepreneurs. So many people, they just don’t think. Like that, just people, they are taking one year off or they’re just following instructions on it through the system since they were like like a kid. So then it’s not even an option for them to challenge that. So it’s very rare that people would challenge that. The young people that drop out. Many of them have problems on many of them, like they couldn’t get into universities who wanted to study what they wanted or maybe found promised help or whatever economic problems. I mean, there are so many. So they need to start working earlier. So they do go cheque other experiences before getting to university. But for these selective, let’s say, Ivy League or higher class or whatever, people can afford that. Definitely. Especially Natia like huge crowds on that. So, yeah, they they just they go through the system and they don’t even think about they don’t bother other cash. Many of them, then they don’t think about options. I also think it’s important. Leaving aside which university you go on, how much it will cost you and also leave it. Leaving aside the fact that when you go to university, that network effect is important from the people you meet, there are build companies with university classmates. So I have that personal example. But many companies started as well from university dropouts or colleagues or whatever. So. So you have that colonisation. So but which online you want or you are less likely to bond and explore ideas in depth or go to bars. So, so is less value for sure. So it’s about our. I’ll be careful. Not only which university you pick, but most importantly, which areas are you planning to educate yourself on. So that’s critical. I mean, what used to be and then cheque on what’s a good paint job, well-paid job or or cost good prospects because it may say so. So you really need to do research on that whilst you are doing your research. Also, consider the option that is never told to you about being an entrepreneur. So or being a business owner or what? What does that mean? So this is actually. More straightforward to start a business on. You think especially nowadays, you have plenty of resources. So, yeah, certainly I would recommend that at least to start something. Even if you start a business or a book or something else that is not straight. Go to university and. Yeah, to what you thought three years ago, because also you are kind of funnelled into what you will end up end up staying at college. Earlier on two, three years ahead at least. So, yes, I would challenge that for sure. Living the economics aside is more about you on on what do you think it will be great to do and add value and then think about the other way around from the bottom up. Okay, so this looks interesting or that it has prospects or it looks interesting to me because of this and that. So then what. What? How can I educate myself on that and then think if it works, it makes sense for you. On which university are or the options, as you say, some great resources out there from top universities as well. So our take that approach. [00:12:21][250.2]

[00:12:23] Absolutely. So my bias has definitely been. I enjoyed my time at university from a social perspective. I don’t think I’ve ever used in anger any of the knowledge that I gained from university. But, yeah, I did enjoy myself. And it wasn’t so expensive when back in the day when when when I went to university. So it would definitely cause me to pause and think for sure. So moving on to the next topic, something which I came across the other day on Twitter that was absolutely blew me away. [00:12:56][32.9]

[00:12:56] I’ll be honest. So there is this artificial intelligence language model which has been doing the rounds in recent months called g.P T-3. [00:13:08][12.1]

[00:13:09] I’m not sure what GPE Stansel to be on it. [00:13:12][2.5]

[00:13:14] But in essence, it’s created by an organisation called Open Eye, which is a non a non-profit organisation doing research into AI and machine learning and things like that. [00:13:28][14.6]

[00:13:29] And essentially, it was a giant language corpus created from a huge amount of stuff on the Web. So basically they pointed loads and loads of sort of machine learning, computing power at a whole load of content that they scraped from the web. And they basically set it the job of sort of learning English or learning language by using the input of all of this sort of written word that they found on the Web. But not just written word, just like how gob of stuff that they found from the Web. And. [00:14:01][32.0]

[00:14:02] The reason why this was originally interesting was because they use 10 times as much input data as they had done on previous models, with the idea being that the more data you throw something, the more in machine learning, the more interesting stuff, kind of like floats to the top. So this has been around for a while now and it’s it’s been used in some interesting ways. So you may well have seen on line there are a few these sites which do I storytelling. And basically you can go along to these sites and you can just type in the start of a story. [00:14:40][37.9]

[00:14:41] And then this language model, this GPE three language model will hallucinate the next section of the story, which is something, you know, that’s been around a computer game since the very early days of taxpayers computer games. I’m not sure if people are old enough to remember any of that be used against us or type in. Go left. Go right. Pick up the thing. Do whatever. And it was used to really frustrate you because the computer always come back saying, up, down and stand up, stand down, stand up. Whereas these ones just completely hallucinate this very compelling sort of scenario that it feels like you’re talking to another human or that there’s an author on the other end is producing this output. Anyway, that’s all very interesting. But what was really interesting on Twitter the other day, we’ll put the link to it on the show notes. But a guide basically took that giant. [00:15:30][48.6]

[00:15:32] Model. And on top of it. [00:15:34][2.0]

[00:15:35] Created a little bit of a UI and the question he also it was basically what did it learn from the Web? Because we they chucked a whole load of data through the stuff that they just pulled off the web. So with a little bit of extra tweaking. What else does it inherently know? Just by the fact that it’s crunch through all this kind of like information and. What he sort of pieced together was that he piece about this amazing little demonstration where essentially you you have a little textbooks and you type into the textbooks. Your description of a Web page or of you are a user interface. So you and he’s got a great little video and his on his tweet showing and doing this. And it’s he’s doing things like typing in create a page with a giant red headline that says X, Y, Z and a blue subscribe button. And this language model basically creates code in a in a language called J.S. X, which is kind of like a a layout code, similar in style to a female or something like that. And then just creates this output code, which then actually just shows you, you know, this code actually is well formed. It’s not buggy or broken in any way. And it actually shows like what this. Language model has created just from a single textual description of what it is that you want to display. And he sits there and he just types in various things. And pretty quickly, on the order of five to 10 seconds. This thing is output’s new versions of a UI just entirely based on just a few was of description. Now, the reason why this sort of jumped out at me was I that was like, wow, wow. Because it was never taught to do that. It’s just something it picks up. Bye bye. Getting all this information off of the web. But the second thing that was, well, you know, this is just some guy who has just tried a little experiment now with the bit of extra elbow grease and a little bit of extra effort, you could really see like a whole variety of different business opportunities falling out. So there’s already quite a big movement in sort of programming or app creation in general called the no code movement, which essentially is people coming out with a whole suite of different tools and apps which allow our non programmers to create sort of fairly sophisticated apps. So you can put together things like so for example, there’s things like Air Table, which is kind of a cross between a spreadsheet and a database, which allows you to sort of create and plumbed together some quite complicated sort of database type things without having to know a line of ASCII well or do any sort of database programming of any sort. There are plenty of other sort of companies things out there doing that. And this feels like the next step on from that, which is like. You have this sort of little II co-pilot who’s sitting there in the in the cockpit next year while you are maybe you’re a designer and trying to so, like, design an interface for an app or something like that. And you could be there and, you know, in figure or sketch your Adobe illustrator or any of these programmes, and you can have this little sort of I co-pilot that kids will plug in, which would essentially hallucinate whole well-formed, well-thought-out, kind of like you eyes from very little input from someone who doesn’t, you know, I can’t design worth a fake. So if I can go to an AI co-pilot and say, hey. I want this thing and describe it in very sort of general terms, and this thing pumps out version one of this thing, and you can then yourself like tweak it, you know, just move things around, change the colours a bit and away you go. Then that just speeds up a whole section of sort of asset creation. You know, you could imagine it doing the same thing for like Facebook ads. So a classic thing. With online advertising is you want to try lots of lots of different creative to see what sticks. And I’ll be tested against each other. And what are the bottlenecks there apart from the cash to do? It is actually coming up with all these variations in the first place. So having something like this applied to it, you could say, OK, here’s the raw materials. Here are a few photos. Here’s a few bits, a copy of whatever. And this thing like Kelly Sunnites, thousand different variations of have created from nothing. So I think there’s loads and loads of options here. And it’s the first time we’re really where something sort of A.I. has sort of, you know, demonstrated any form of actual intelligence. Excuse me. As far as I could tell, I. Now, you’ve looked at this briefly, Marseillais. What what did you think? [00:20:19][283.9]

[00:20:20] Yeah, what’s chicken, actually. So our recent comments. So the counterargument will be, from my technical point of view, that they just threw a lot of computer computing power to that two to a problem or to that project. [00:20:39][18.8]

[00:20:41] They argue, let’s say on here, VentureBeat, that the computer they team up with Microsoft on the computer to process this kind of information, which had one hundred and seventy five billion parameters. So is Uruguay a system with a word through kind of 50 joyed of memory and untaught which cost? Or I mean, millions, tens of millions. And they say 12 million in compute credits, which these guys have opened. I can do with Microsoft what they said is done. So the underlying technology is the same. So a neural nets that were used before, even for lightning, probably Google Translate or other platforms, they just did it bigger. So it’s more impressive, the results, but it’s not moving the world forward. They need in the research of how to. I would say probably there is a race towards general A.I. or jow artificial intelligence. So and and so there was a leap forward with then your net deep mind. [00:21:57][76.9]

[00:21:59] We’d go out to go on, son. So but since then there have been all these incremental advances. And I think I, I agree with you and you probably you feel it more closely because you are a programmer. So it will make it easier for you. And also give give gifts Europe. [00:22:23][24.2]

[00:22:24] It’ll put me out of a job. [00:22:24][0.8]

[00:22:25] Yes. Yeah. So by your intrapreneur. So you may try to find a way to get into that lather. But yeah, ultimately, if it builds tools and what they’re trying to achieve now is with the eye as well, these two to up code that codes for itself basically. So. So that programming could be outdated, which makes sense anyway. If it’s sameem to make it as you said, it will speed up a lot the efforts to get to the next generation of tools which are more advanced and all that combined go going towards an ultimate solution that that’s more powerful. [00:23:08][43.0]

[00:23:09] So, yeah, I’m I’m impressed on the progress of A.I.. I’m I’m usually I’m a bit more reserved on the claims. Many others are putting forward for their singularity. And, you know, I’m personally a big fan of Elon Musk as well. I don’t take what he says for granted or not. Nothing like that. I think he’s perceptional one of a kind. But, yes, he’s still a person that can say silly things or could be wrong. So. [00:23:49][39.5]

[00:23:51] So but he has a point on on that this trend will keep growing up to a singularity. I’m not so sure that is going to be in 20 years, 30 years. But at some point, if you allow enough time. Yeah. This artificial intelligence or machine intelligence will surpass human intelligence. So, of course, you need to find what’s intelligence on and in which sense it supposes. But if. Yeah, essentially it I would say if if if you if in any domain that you can imagine a computer or that computer competing with a human, it’s a puzzle as a human. I’m vastly southerlies that passes by. Bye bye. But by an age it’s got to be a material or six like exponential. So. [00:24:44][53.0]

[00:24:46] Yeah. [00:24:46][0.0]

[00:24:49] Yeah we will. We’ll get there. But it’s it’s going to take time. Probably way more time than people think. Probably hundreds of years. Well we we could be all done by then. Yeah. Yeah. On Pandemic. Sound like I gave it to an authority. Yeah. That climate change. Whatever the shit that hits us next. So yeah, I’m more reserved. I was, I would love, you know, to merge with machines and I loved all of them. I’m, I’m, I’m not that technical like you on like from front for my programming point of view. But I built the companies. I’m early adopter of technology as well. So eLong was targeting Joe Rogan on the symbiosis with machines, I think. Yeah. Yeah. That’s that’s that’s great. I think I would definitely go for it. Yeah. Yeah. Ford without hesitating too much. But again, even with that, I think we are many years away from it. And also we will know when it’s coming. So that is going to happen overnight. This is looking more like an incremental improvement of things. I don’t think it’s exponential as its claim. [00:26:09][80.4]

[00:26:11] Yeah. [00:26:11][0.0]

[00:26:12] Certainly there has been progress, but usually we are. Yeah, we are not that good at thinking long term. Yeah. When it’s gone it’s gonna happen. [00:26:25][12.5]

[00:26:27] Yeah. Bit like nuclear fusion. It’s always been 20, 30 years away. [00:26:30][3.3]

[00:26:30] But what was it. Yeah. I can go like other examples as well. Like it is so different but. Well Peter Thiel, you know this well known investor entrepreneur from the PayPal mafia, they call them the founders of PayPal. They went on then to build great things. He was early investor in Facebook. Now he’s listing volunteer and so on, which is very controversial, but good for him. And he’s always this contrarian guy putting forward like different ideas. So, again, I’m not saying he’s right, but it’s good to come out like contriving opinion because on this, because everyone you will always hear almost inevitably everyone, all media outlets as well, saying, oh, my God, technologies like growing exponentially. And he puts the example that actually probably is not. [00:27:30][59.4]

[00:27:30] And we are stagnated so that that only on them on the field of bits like computers, that the growth has been exponential. And he attributes that mainly because of their business model love like software companies, you have an incremental cost to build a larger audience. So usually if you sell cars, you come out cost by cost of producing that car. So if you sell more cars, then you will grow. But it’s not exponential because your costs would grow attached. To do that, you can improve profit margins. So it’s not. [00:28:08][38.2]

[00:28:09] But and then whereas in software you if you have a cost of hundred for one hundred customers, but then you can have a cost of hundred fifty for 10 million maybe. So that is like extreme example. But the point is that with little incremental cost you can deliver to a wider audience, increase sales. And that’s why they became so popular and lots of investments went there and developed a lot. But in their world of atoms, as he put it off like things, we actually went backwards in many, many of them. Like he puts some of the examples from top of mind may say. So he said in the 60s, we. Went to moon. We were sending rockets everywhere. And then, yeah, we thought, OK, then we’ll go to Mars. But instead, NASA had their space shuttle orbiting the Earth. So not very exciting. And in 2011, they just landed. So, so, so. So now they they were. Now, which Space X is sending some some some astronauts to a space station in U.S. soil? But until since 2011, NASA was hiring rocket launches from Russia. So they didn’t even have the capability to send a rocket despite our people to space station. So so it clearly went backwards and then other examples. So you are saying as well. They promised that in the year 2000 we will have flying cars and instead we got 140 characters. Originally we did on the bottle some day. The human genome. So it was discovered in 2000 and it was, you know, the holy grail of the next wave of many scene discoveries in biotech, nanotech and so on for curing cancer. All sorts of other diseases. But 20 years since then and there has been very little progress in the cure of cancer or any major other disease, really. So. Yes. So it’s I don’t know, I think with a A.I., there is hype still in their world of bits. But we should be careful long where we think this will go, especially linking to a previous topic we’re talking about on the education system. So don’t just think this will keep growing forever, exponentially. I think eLong would say as well that don’t assume things will. Things won’t improve by their own or on their own. I just need people doing a lot of effort and committing resources over a long period of time to really make it happen. So, yeah, things won’t improve on their own. So, yeah, that the the fallacy on the exponential technological progress. I mean, there is progress. I’m not sure if it’s exponential and maybe in some fields even just this is something very basic example. But like the iPhone. I mean, one what one was the first one lunch like. 2007, May 2007. Yes, seven. So 13 years since then. And is pretty much the same piece of hardware, I mean. Yeah. A little more memory and camera here and there, but. He has not improved much. Of course. Yeah. I would like to see those companies doing what they can do. Definitely way more. And if they are not, I mean, they’re driven by profits, though, quarterly, short term profits. So for them that day, for the cash cow, they just keep producing the same marginal increments. Just more people would buy it because too many people don’t have it. All right. Well. [00:32:21][252.7]

[00:32:24] But they yeah, they could be doing more. I would say I’m Kudo’s for open A.I. is great. I know as well. [00:32:33][9.4]

[00:32:34] Elon Musk was involved at the beginning and he just step step down or just left. [00:32:41][7.0]

[00:32:42] He was not part of the team, but was kind of invest or some direct or something like that. So he argued that the insurance and vision. [00:32:52][10.5]

[00:32:53] I wonder what that meant. But yeah, I’m still to be more impressed on them on the path towards artificial intelligence. I think broadly, for example, the approach on your link. I think it’s it’s way different and more like a radical way of thinking. And probably that could be a light, certainly a shortcut to Janet. I or at least on paper, makes more sense to me. I don’t know if it’s gonna work at all. But if it if it does work to some extent, like increase the bandwidth where humans or the human brain can connect to a computer, that then that’s a completely different story. So probably. Yeah. More research. So neural nets are you know, they are one thing you can grow the potential of neural nets exponentially beyond throwing. [00:33:52][58.8]

[00:33:54] Or doing the bigger data sample. So with more like machine power and this and that. But rather it’s the path to a I would rather be more like a combination of stuff. Yeah. So, yeah, I agree to some extent with a counter argument, but I’m still impressed you get plaids here. [00:34:17][23.5]

[00:34:17] So to summarise, kids think twice before you sign up for the Grand. Zankel. And secondly, sex robots. They’re coming. I can feel it. Thanks, everyone, for listening. We’ll be back next week with some more nuggets of knowledge. In the meantime, please do cheque out our YouTube channel. That’s where we post this and our other podcasts. You can go to YouTube and search for networkers or you can find the link in the show notes. If you’re interested in a deep dive in all things entrepreneurial, including more detailed information. Help mentorship courses. Cheque out our Web site. And that is a networkers dot code. Right. See you next hour, guys. [00:34:56][38.1]

[00:34:56] Thank you to. [00:34:56][0.0]

[2050.8]

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