I Failed My First Two Years Of University - TDBS 21 April 2017

Guess what day it is? It's day 80. That's an 8 and a 0. Can you believe it? It's the 21st of April, 2017. Back once again with another episode of the Daniel Bourke Show. Thank you all for tuning in, whether you're on YouTube or podcast. Hope whatever you're up to today, you're having an awesome day. And if not, hopefully I can bring you some value and make that day a little bit better. And if I don't, well then let me know and let me know how I can get better. But what have I been up to today? This morning I woke up and did some studying, made some tea, went for a walk actually. That was really good. It's hard to remember, it's like 9:38 PM and as you can— if you're watching on YouTube, you can probably see I've got a bit of a red eye. I've been rubbing my eye because I was— been looking at a computer screen for way too long today. Doing a lot of study, trying to get ahead, uh, well, back up to scratch on this deep learning course that I'm doing. If you've never heard of deep learning, it's a subset of machine learning. Machine learning is essentially taking over the world of software, and all the big tech companies are getting right involved in it. If you just Google machine learning, you'll get a whole bunch of things. I've actually done a few podcasts on machine learning, but essentially it's, it's getting computers to do more and more tasks for us, which we've been doing since the 1940s, but recently it's been scaling up. The jobs in tech have grown exponentially over the past few years, and with that growth, so many new technological advancements have happened. I don't know if you had a chance to check it out, but Facebook's recent developers conference, I think it's called F8, they announced some incredible stuff. So they're no longer just a website or an app that you go on to and fill in your details and chat to your friends. Facebook announced Building 8, which is a research facility to look into new products and new frontiers in, in the tech world. One of them is a Neural Link, so you put it— I'm assuming you put it on your head or you put it on your hand or something like that, and it can sense the words you're about to type. and it believes that it can get you typing on a phone at 100 words per minute by just sensing the words that are in your head. Whereas, right now, you can only type on a phone as fast as you can with two thumbs, about 20 words per minute. So, imagine, I don't know, the communication possibilities you could have through a phone if you could— if it could sense that you're going to type. And that's, I haven't dug into it deep enough, but that's just one thing. It's not even, then the typing is not even the ground level. Well, actually, sorry, the typing is the ground level of what you could do if you had that neural link between your brain and technology. Imagine if you scale it up, you could, imagine if you had the internet plugged into your brain at all times. So instead of researching for something, you could link all of the known intelligence that's out there on the internet and have it accessible in your brain. Of course, you'd have to be pretty good at doing Google searches already, but if you could have it easily, that easily accessible, intelligence, human intelligence would exponentially grow. And would that be artificial intelligence, or would that be real intelligence? Who knows? Another thing that we're talking about is building a technology that will allow deaf people to hear through their skin. And I have no idea how this will work, but That's essentially what they've been— that was one of the big announcements. And I didn't watch the full video, I just read an article that said the 4 things you should know about from Facebook's recent conference. And the other one was Developer Circles, which is sort of small groups and communities in local areas that are aimed at people sort of wanting to get into— involved in developing things for Facebook. I might look into that in the future because I'm I'm interested in Messenger, Facebook Messenger in particular, like developing bots and whatnot. So I might look into that in the future. If I do, I'll let you guys know. But at the moment, I spent all day on Khan Academy as well, learning some, some math, catching up on or relearning all the calculus I learned in high school to help with deep learning and machine learning. I also did some programming, and I bought two books on machine learning, so I'm very excited to read those. I think I've switched over the past few years. I used to be— I used to— could never read books. I hated reading the textbook for maths and whatnot. I don't know what it was, but now I enjoy reading a book and going through step by step and practicing. I guess you just— it took me a while in university. The first 3 years, let me tell you a story. The first couple of years, I didn't do much. I was really lazy. I would And I'm not entirely sure why. Actually, I think it's because I was studying something that I just sort of followed someone else's path. I didn't pick my own path. It's a lot harder to study something that someone else sort of decided for you. And I think I started off studying— well, I did start off studying biomedical science because there was a girl within the group of friends that I was friends with who was studying it as well. and I thought, hey, that's a good idea, and I just decided to study that. All through high school I was leading up to study law. I was captain of the debating team, whatnot, and I don't know, I just decided, you know what, I want to be a doctor. So, I think I spent some time— I spent some time in hospital in year 10 when I was 15, about 3 weeks or so. I lost like a third of my blood or half my blood when I got my tonsils out. I was the only person that the, the, uh, I can't remember what type of surgeon it is that, or the doctor, that he'd ever seen that had hemorrhaged on both sides. So 9 days after my tonsillectomy, I hemorrhaged on my right side, and then 2 days after that, I hemorrhaged on my left side. And he's the only person who's ever seen hemorrhage on both sides on separate days. So hey, maybe, maybe that's changed since then. Maybe I'm a winner still. But that, that sort of led me to want to be a doctor. So I was studying to be a doctor and the first year and a half of university I didn't really enjoy. I would, I would, I was failing subjects. I was coming home, not studying. I was just chilling out on the couch watching Discovery Channel, A&E, playing a lot of video games, RuneScape Online in particular. But then after, after a couple years, I realized I was into fitness and I was learning more about nutrition. And then I think it was about 2 and a half years in, or maybe 2 years in, I swapped over to nutrition and food science and nutrition as a part of my science degree rather than biomedical science. And my grades, I was getting straight 6s and 7s, which is like A's and B's pretty much, of all my subjects. And I was loving it so much more. It was a lot easier to study. It's a lot easier to study something that you're interested in. And that's, that's what I've been doing. That's why I've been studying so long over the past few weeks, all day, with machine learning and deep learning, is because I'm fundamentally interested in these concepts of AI. Like, the things that Facebook announced today really sparked my interest. There was an article actually by Wait But Why. If you've never seen that blog, check it out. On about the Neuralink, that Elon Musk has started a company called Neuralink, and it's all about what I just talked about, like linking a device to link the brain to external intelligence, because I think that's, that's where we're ultimately going. That's the next stage. That's before AI officially, computers and whatnot, machines take over humans, is we will merge ourselves with them. And then maybe one day they'll realise that they don't really need us, but who knows? Hopefully that's not— that's not in the near future. But if you imagine any advance in technology, maybe you can see that happening. But who knows? This stuff's fascinating me, and it's a lot easier to study something that you're interested in. And so that's— I don't know, maybe that's the daily challenge, is like, learn something you've been interested in. If you're Read something that you're interested in. That's it. That's the daily challenge. And I'm doing the daily challenge earlier on in the podcast rather than right at the end. And we're going to wrap this up in a few minutes anyway. But that's what— yeah, it took me— I graduated a 3-year degree. It took me 5 years at university. And I think the first 2 and a half years was me figuring out what I wanted to know. And then the next 2 and a half years was me learning how I best learned. And then, now that I've been out of university for about almost 2 years now, or no, about 18 months, I've still continued learning. I started learning Mandarin, I started learning Japanese. I've stopped that since then because I was learning Japanese because my ex-girlfriend was really into Japan. I still went to Japan and practiced Japanese, so I'll talk about that story later. But, A big thing I took away from the past 18 months, or the past 4 years or so, like learning nutrition and subsequently being out of university, is I learned how to learn. I learned how I best learn. And first of all, number one for me is it has to be something I'm interested in. There's no point me trying to push a boulder uphill and learn something that I'm not fundamentally interested in. And the second point is that I learn in a different style now. I like to do practical examples. I like to read books. Before, I wasn't like that. I would just sort of, I don't know, I would do rote learning. I would write out the same thing hundreds of times. And now I've sort of incorporated different styles of learning. It's flashcards, it's video, it's Khan Academy. Wakhan Academy's video. It's problem solving. It's being in the community. I used to never ask for help, but now I'm in a Slack channel, I ask for help, I go on the forums, I Google. I used to, yeah, just think, oh, I can solve this problem myself. But realistically, all of the knowledge that we have has come from someone else before us. So not asking for help is, is a big disadvantage. But I'm gonna wrap this up. I'm pretty hungry. It's 9:49 at night. I'm pretty tired as well. I should have done the podcast earlier, but you know how it gets. I've had a phenomenal time today. Did an epic workout with my friend Jay. You can check it out. I'm going to upload it to YouTube in the next few days. So, yeah, we had a phenomenal session. I'm pretty sore from it already, actually. You can feel it. But he's been on the podcast before. I might get him on again. He's an awesome guy. We had a great conversation. Whenever you get the blood pumping in a gym session, always have the phenomenal, phenomenal conversations. I think, I don't know, it's like when you're in a bar. Everyone's in that sort of zen mode, or not zen mode, but everyone's in a similar kind of mood. But when you're working out, it's the same thing. Everyone's on that high from lifting weights, from getting the blood rushing. You have awesome conversations. Not that you don't when you're not working out, but for me, if you've ever experienced it, if you've lifted weights before and you've talked to one of your good friends while you're there, you know what I'm about. But nonetheless, text someone you love. Yeah, that's another good challenge today. Text someone you love. I was thinking of one of my good friends today and I texted her and just said, "Hey, what are you up to?" And she was really surprised by that. But the other challenge is spend 20 minutes learning something you've been wanting to learn for a while. If you want to learn Japanese, download Memorize the app and learn Japanese. If you want to learn about artificial intelligence, look up Neuralink from Elon Musk and Wait But Why, or just Google artificial intelligence. There's a lot of stuff out there for it now. But nonetheless, I hope you're having an amazing day. Hope I've somehow brought you value from this podcast. If not, let me know. If I have, well, also let me know. I'd be happy to hear. That'll be some good encouragement. Not that I need it because I'm going to make more. But Thank you all for listening, thank you all for watching, and I'll catch you tomorrow. It is day 81. Catch you later.