In the eletica wrap.


Inside a $600,000,000 Australian Tech Company

Yeah, that'd be amazing.


Thank you.


Cool artworks, eh?


Melbourne is full of these things in the streets and alleyways.


Look at this.


There's Sanic.


Sanic the Hedgehog.


Show me the way to end it all.


But what you saw there was I was answering some questions on LinkedIn.


A lot of messages.


Here's another one.


I think that's...


Is that Johnny Bravo?


I'm not entirely sure.


All these memes.


But I was answering some questions on LinkedIn.


After posting about getting an internship and whatnot and a role,


I had a lot of questions saying, what's the best way to do it?


What are the courses to do?


Where do I start?


Well, to be honest, I'm not entirely sure what the best courses are,


but I can share what I've learned and what worked for me.


So it happened by sharing my work, by putting it out online,


letting people know what I was working on,


and just putting myself out there.


And then someone reached out to me,


and then that person put me in contact with another person,


and then that person put me in contact with another person again,


and then I was offered a role.


And of course, it's important to learn the skills and whatnot.


That's fundamental, of course.


That's a variable we can all take care of.


There is no one magic bullet course.


But I think what's really important is to not forget


how important relationships are in the field.


So if you're looking to break into, whether it's data science,


machine learning, or technology, anything,


start messaging people.


Start going to meetups, meeting people who are involved


in what you want to get involved in.


That's what's worked for me.


Will it work for you?


I'm not entirely sure.


As I said, everyone's journey will be different,


but that's essentially what happened to me.


So start messaging people.


Reach out.


Share what you're working on so people can find you.


That's my advice on how to get an internship.


Morning.


Excellent.


How are you?


I'm here to see Nigel, I think.


I'll get you to sign into the iPad, please.


And Nigel will be your host for today.


Beautiful.


So what do you think of our area?


Pretty good.


I'm going to go back 22 years.


Yeah.


And...


That's not too long.


No, in the 90s, it was just the dot com boom.


That's younger than me.


Totally.


And in the 90s, it was all about how many URLs can you


actually register?


And really, the dot com.au turned out to be a great one.


Over 200 from the guys who originally founded the company.


Over 200 original URLs.


To maintain those, we have to maintain them.


Some of them are hilarious.


And many of them never got executed or were campaign-based


or otherwise, but the one that won was realestate.com.au.


Oh, Realtor.


Yeah, well, we've brought into various other businesses


along the way.


Myfund.com.


We started in China.


One form is a business we bought.


Yep.


Real commercial was an obvious addition.


I wish I caught on to that earlier so I could have


registered DanielBerg.com.


I don't have DanielBerg.com.


Oh, no.


Do you have your name?


No, I don't.


But who knows?


In the world of apps, maybe it's not important.


Yeah.


But brand names become incredibly important.


Yeah, that's it.


And all of these as well?


Yeah, so that's our international family there.


And you can see we've just added realestate.com.au


homelands by hand.


It's not...


It's a time era to ever go putting something up


because we grow so fast.


Yeah, that's what I figured.


So rapidly that it becomes a challenge.


So really the change across the board is a change


from searching through the photographs of secondhand


houses on the internet...


Yep.


...through to a world of match.


So search...


Search.


...for years of match.


Match.


And this is where our strategy now lies.


It's machine learning artificial intelligence to


match people to things in property.


Yeah.


So they could be content.


They could be a homeowner.


I just saw there.


They could be an investment property, a rental property.


This is the thing.


Now people are just going to go, I want to spend less


time searching.


Well, that's...


Yeah, that's exactly...


I was thinking about that the other day.


I was talking with my brothers when we go on YouTube.


I don't think I've searched for a video...


Exactly.


...in the last year.


Well, I can't remember actually searching for a video


like that.


It just knows what I want to watch.


It knows what I'm interested in.


Same for other platforms, right?


You get there.


And what happens is trust builds over time.


So people, they start out going, oh, I've got these


suggestions.


We've been doing push notifications.


We do 18 million a month.


Yeah.


For years.


So the biggest question in this company across that


whole lifetime, what do you reckon that's been?


What do you reckon our research lab every single


time comes back with this is a question?


The biggest question.


In real estate today, in digital real estate, what's


the number one question?


If you were the greatest real estate agent in


this, and you had one of those, a Motorola StarTech


by the phone.


That's no iPhone.


1996 calling.


There's a driver and a co-driver, a pilot and a


co-pilot.


Yep.


This increases the quality of what you build and


reduces the cost of what you build.


Finding The Right Medium - TDBS 18 April 2017

Yo, what is going on everyone? Welcome back to day 77 of the Daniel Burke Show.


Well, this is day 77 of the podcast but it's only about day six of these YouTube


videos and I'm really glad that I started making the podcast in the form


of, I don't know, more than just one outlet. It's video and now it's audio. So if you're


listening to the podcast make sure you check out my YouTube channel


mrsdberke.com slash videos. You can find all the links there or if you're watching on


YouTube and you want an audio form of this, you don't have time to watch it,


check it out mrsdberke.com slash podcast. But whatever you guys are up to, I hope


you're having an awesome day. Thank you so much for tuning in YouTube or podcast.


I just finished leg day so that's why I'm all sweaty and leg day is hard. I


failed today. I failed. I tried to get five by five of 95 kilos on the squat


and I've been reworking my squat over the last few months to get to get a


better technique. I've had some knee pain in the past and I've been reading books


and implementing studies and things like that, or studies, implementing my own


fixes to get this knee pain better and so far it's it's working amazing. I've


been focusing on yoga, increasing mobility in my ankle, just generally


improving my squat, activation of my glutes. I missed out a lot on that when I


when I was like just starting squat. If I was to go back and start working out


again, however long it was, I would start squatting earlier. I didn't do legs for


at least the first year of training just because I only thought the upper body


was was worth doing because they're the girl getting muscles. But definitely the


squat is the number one exercise. If I had to pick one exercise it would be it


would be right now between pull-up and squat as to what I think are the best


for overall physique development. And that's just my personal opinion, maybe


shared with others, may not be, but that's my personal opinion. If you want to get


bigger and stronger do pull-ups and squats and you'll be on the right path.


But oh yeah where did I fail? I tried to get 95 by 5 and I failed on the last set.


I only got three reps. I scratched my back, I couldn't I dropped down, I couldn't


get the bar back up. So that's a good feeling actually. I haven't failed on a


weight in a long time and so the fact that I'm failing at all is is good. 5x5


you're sort of meant to be pushing the bar each time and literally


pushing the bar as well as figuratively in terms of upping the amount of weight


that you do each time. So the camera's only got about 30% more battery and I


don't know how long it will last for this podcast so we're going to keep it,


try to keep it 10 minutes so we get everything on the on the video as well


as the audio. So what am I going to do? I'm recording this on YouTube but if


you've checked out my YouTube channel it doesn't have all the recent episodes and


I know that. I've been, the podcast goes out every day because that that's


something quick that I can publish and it's a small file so I can upload it


quickly to SoundCloud. But YouTube I'm gonna probably going to do it in batches.


Reason being is because I live at home with with my family and if I'm uploading


YouTube that's gonna wipe out the internet for like four solid hours. Maybe


I just wake up at 3 a.m. and upload it then. That's that could be an idea. I'll


figure that out in the past, in the future, in the past. But at the moment I


think I'm gonna make make four or five videos at a time, go to my local Apple


Store or go to my local library which have fast internet and just upload them


all in one hit. Spend a day there studying while I'm uploading and


everything will be gravy and then you guys will get four, four, five YouTube


videos at a time. But still slowly trying to work it out. And what I've been up to


today? I think I overslept. I think I did. I went to bed at maybe 10 and I woke up


at 8. I didn't set, I forgot to set my alarm just just out of pure coincidence.


Maybe I didn't set it on purpose I don't think. I can't remember. But then all day


I was in this slump of just being in and out of being tired. I had like two naps


today and it was harder and harder to get up each time and I think I had a


fair bit of caffeine yesterday. Much more than I would usually and so my body


was just titrating the caffeine out and it was slowly, slowly getting out of my


body and I know this is just me thinking out loud. I don't know if this is the exact


principle. I just had to keep napping. It was hard to like stay awake and stay


focused. But nonetheless I did a bunch of Python study which is a programming


language if you've never heard of it. Did some work on my


Udacity course on deep learning in a very complicated section at the moment.


It really, it was frustrating at some points because I couldn't understand a


fair bit of it. But then after enough time, after enough practice I was


able to get the problem solved. And I mean that's like anything. Learning


programming is easy. It's like learning how to work out. I'm good at


working out. I wasn't good when I started. It took me seven years to get where I am


now. And now I'm a low body weight and I'm pretty ripped and I've got a fair


bit of muscle but that that's taken seven years of consistent working out.


No, it's six years of diet and exercise and I work out five to six times a week


and it's hard. But now it's easier for me to work out than it is to


not work out. Because I just did leg day and it was ridiculously hard but I feel


amazing right now which is why I'm recording the podcast. I'm incredibly


hungry after that workout but I'm gonna do this podcast now so that I can get


inside, have some dinner and then I'll spend the next couple of hours editing


some videos. And I had that epiphany today as well. I'm trying to work out


what the best best way for me to make content is. I would document my life. I


like writing so I've been posting on on Medium if you check me out. MrDberg.com


slash blog. There's my blog. I do a monthly newsletter if you want to sign


up to it there. I've been starting to make YouTube videos which I'm absolutely


loving and I've made 76 days of a podcast. Today's day 77. And if you are


one of those people who is majestically, you're probably very rare because I'll


be honest, the maximum listens I get on a podcast episode is 50. Maximum


views I have had on YouTube video is a hundred and something. So there aren't


many people that I may be hitting at the moment but that's alright. I'm happy to


start small. I'm happy to to cop the criticism for years on end. But if you're


one of those people who's seen all of my content like YouTube, Medium, podcast, hit


me up on one of my outlets. You know where to find it if you follow me enough.


Let me know which one you think is the best. And I'm still experimenting with


which one. I'm enjoying all three at the moment. So if you want to see more of me


on YouTube, let me know. If you want to see more podcasts, let me know. If you want to


see more writing, let me know. I'd love to hear. Even if no one lets me know, I'll


just keep keep putting it out. I don't really look at what other people are


doing. I just I listen to some podcasts. I watch some YouTube but I'm just at the


moment just working my creative muscles something fierce. I'm just putting out


writing, putting out YouTube videos, putting out podcasts. And it was all


daunting at the start. But now it's... I don't know. I need to... I feel like I need to do it.


It's incredibly fun documenting all this stuff and creating all these


things. If you've never tried it before, I highly suggest creating something. I've


spent so much time in the past consuming rather than creating. And now that I've


sort of made a switch to creating more than I consume, it's one of the best


things I've ever done and brought me an incredible amount of satisfaction. And so


another point I was going to talk about is that training is paying off. So I've


been consistent over the last few weeks with my workouts and I'm noticing


changes in my physique already. And I've been doing it for so long now that I can


I can tell when I'm in a good zone. And I feel like I'm in a good zone with


training right now. And so that's that that mental model that I just spoke


about, about the fact that I've been working out for six years, I just need to


apply that. That's what my intuition is telling me to apply to


this creation of content. I wasn't good working out for the first year. I've


only just started writing. I've only just started making podcasts. I've only just


started making YouTube videos. So I know I'm not going to be good for the first


maybe year, two years, three years. It was only when I started working out, it


was only until maybe the year four, year five of putting in hard work that I was


confident in in taking my shirt off and showing people what I looked like.


Because before then I was like, oh I'm putting on this work but I still don't


look that good in the mirror. And now after all this hard work it's finally


I'm in a good place right now. But it's only after having that six to seven


years of work to put in. And that's what I can see the future. I can't


and what am I saying? I can see the future like of this show, of the Daniel


Burke show, maybe being the same thing. As long as I put in the work, make it


continually better. Right now for me it's a really early version. I'm kind


of embarrassed by the work I'm putting out but not in the sense that it's


bad but it's like okay you can do better. But it's I know that it's a


process to slowly get better and I'm only ever gonna get better if I keep


doing it. And so yeah that's what I plan on doing. Time is over but I'm gonna


finish up on some quick more quick points here. Oh yeah my meditation


practice has been lacking over the past few days and they just got back into it


today but after doing that session felt phenomenal. And really once you become


sort of self-aware so much you can you can see yourself I know swaying from


from rationalism with your decisions and I'm finding this hard to explain but


after meditating for a total of 75 hours or so this year through headspace my


self-awareness is incredibly high. Like I can sense when I'm I'm I know not in the


good headspace now or and this is I know I'm having trouble explaining it but I


find that if I if I deviate from doing the practice every single day I my


judgment and my self-awareness falls falls down it starts just like just like


working out. If I stop working out for a consecutive number of days getting back


into it is a lot harder and I can feel my body not being as functional as what


it would be if it was continually training. Same with not eating well over


the for a number of days. So I find getting back into the practice it really


after about six or seven days a week or so of meditating every day it just I hit


this another level of self-awareness which is which is a superpower in my


opinion. Self-awareness is a superpower but I'm gonna wrap this podcast up it's


just over just under 12 minutes and what am I gonna do I'm gonna go inside eat


some dinner I'll edit some YouTube videos they'll be up in the next week or


so of all the latest podcast episodes and I did one yesterday Monday of what I


ate during the day and tracking my macronutrients in my fitness pal just a


nice little short video and but yeah thank you all so much for watching thank


you all so much for listening leave a review leave a like whatever you want to


do I'd greatly appreciate it hope you're all having an amazing day oh daily


challenge try it some form of meditation google it download headspace try it out


one session so I'm so I'm gonna give you one session try it out change my life


maybe it'll do the same for yours if not that's alright let me try things out


that's what life is an experiment right it's an experiment right I'm talking too


fast but tomorrow's day 78 not sure what it'll be on but I'm lining up one of my


friends actually for a future episode she's an amazing girl so you'll know


Using Machine Learning to Replicate Airbnb's Amenity Detection Part 1: Overview

What's going on everyone? Machine learning engineer Daniel Burke here.


Aka Mr. My whole body is covered in sweat because it is extremely humid where I am,


but that's all right because I love the heat.


Aka Dr. Delts, because look at that deltoid, you know, that was my nickname when we first started


gym. I was going to be a doctor, but then I decided against it. And I am very excited today


because it is a Monday and I mean, I live a life at the moment where it's like every morning is


Monday morning and every night, Saturday night. That's like my motto. But it is Monday and it is


the start of a new project. I am absolutely pumped and I'm calling it 42 days because this is kind of


like, it's like an experiment. And this is the first video. And the reason being is 42 days is


six weeks and I go on a trip with some friends to Vietnam in 47 days, give or take a few. So I've


kind of got to fill that little space. Someone's decided to do a little burnout outside my place.


But what is 42 days? Well, I wrote a blog post on my website. I'll link everything I mentioned in


these videos in the description, by the way. I wrote a blog post on my website called 42 days


and another one called how to communicate and show your work, which is a part of my


machine learning course, which just finished up. And there was a section in there called start


the job before you have it. So the whole premise is if you wanted some role, let's say in the


technical field, instead of just going through and applying with a resume in some online portal,


which is most definitely going to be clogged, you figure out what that role, what that person


in that ideal role does, or you design it yourself, and then you start doing it.


And so the whole idea of, oh wait, I've got a framework for this, like a little cool poster.


I'm going to print that out and come back.


All right, we got it printed out. So I'm going to stick this on my wall. And as you see there,


we've got six weeks. That's 42 days. Yeah. And so all I'm going to do is this one little project.


So I'm going to introduce you to that in this video and do that project and write it up here.


Write it up here. And then we're going to work through this, this section together. And today


is because it's Monday, it's like a research day. So and it's day one of this project. So I'm


basically going to just be outlining the rest of the days today. So let me let me write this


project out and then we'll get back into what I'm actually doing. All right. So you see here,


we've got it there. I don't know if you can read that, but it says project.


2020 FI, Airbnb's object detection pipeline. I'm thinking, what is that? Well, I read this amazing


article by Airbnb engineering. And when I think about it of companies I'd like to work for Airbnb,


there's not very many, right? Because I'm not searching for a job, but Airbnb would be pretty


high on that list. And I read an amazing article by them. I'll probably put it here. And it's about


their object detection pipeline. And I decided what would be fun is if I just replicated that.


And there's a few tools that I want to try out a few new things, a few shiny new things.


And so working on this project for the next six weeks will give me something to work towards,


aka replicating and potentially improving Airbnb's object detection pipeline and try out all these


new tools. So I don't know how this is going to turn out. It's an experiment, but that's the whole


idea of it. The beautiful thing about six weeks, aka 42 days, is that if it doesn't work out,


it's only six weeks. So that's enough talking. Let's get into it. I'm going to spend the next


couple of hours doing some research, putting together a notion document of everything I'm doing.


And then we'll come back here.


All righty. So as you saw, I've kind of spent the last hour or so building up this little


notion template. And how good is notion? How beautiful is this? Look at that little house,


that Airbnb photo I found on Unsplash. Anyway, so this is the 42 days template,


2020 applying Airbnb's object detection pipeline. And what I did was I went through this article


here and of course, everything will be linked below in the description. I'm kind of developing


a central ground truth of the project that I'm going to be working on for the next 42 days.


And so the last hour was basically me doing research and planning, going through this article


that I want to reproduce at least or improve or just put my own little twist on it. And I was


just putting the subjects here. So I've broken it down, problem, data, because all machine learning


problems come with data, right? Modeling, what kind of model did they use? And then any additions


and learns. And so if we go back up here, I'm developing some criteria for myself. So if I'm


doing a 42 day project, what is success for that project? And I haven't quite figured that out yet.


So I looked at the article reading in there. And a little tidbit is that when you're trying to build


like some sort of project, if you find that there are pain points, aka one of their pain points was


they ended up using AutoML. So Google's AutoML service, they can't download the original model.


So that's potentially something that I could fix. This is just early days still. But I've got some


tools and techniques I'd like to cover and explore. But basically, let's sum this up.


What is their problem? Well, if we look here, basically, this is what they want to do.


They want to automatically do this on any image that gets uploaded to Airbnb. So if you've ever


used Airbnb's app, they've got a whole bunch of different properties that you can stay in. And


they want to figure out what amenities or like tables and chairs and ovens, those properties,


those listings have so that they can put that in the description on their app. So that's their


problem in one line automatically label an uploaded image with what amenities it has in it.


What data did they use? They had 25,000 total images with 30 labeled classes. So this is where


I'm thinking I'm going to go first. 32k from open source, 43k from their internal data set. That's


might be where I get let down is because I don't have access to their internal data set. It just


means that I'm going to have to be crafty. There's a bit of a distribution of the classes.


This is how they set up their data labeling. So basically, they used open source labels plus


or open source data plus Google's data labeling service. So they pay people to label their own


data. Modeling, they tried out using some transfer learning with TensorFlow object detection,


aka MobileNet v2 and FasterRNN Inception ResNet v2. What a name, FasterRNN Inception,


CRNN Inception ResNet v2. One of them was fast with lower accuracy. The other one was slow with


higher accuracy. But in the long run, they ended up going with Google's AutoML object detection API,


which got the best results. And is this, is my lens fogging up? I guess it doesn't really matter.


I look kind of clear. And it achieved, so their evaluation metric is mean average precision. We'll


jump into that later. So that's 68%. I calculated with some off the hand calculations that when they


were doing transfer learning, they spent about $51 in GPU compute, which is pretty cheap,


five days of training there on AWS. But if they used Google's AutoML service,


I got two figures. So they said three days wall time. If it's three days wall time,


it costs about 1800 US. If it's three days compute time, because of the way Google's AutoML service


works, it was $226. So there's some metrics and costs that I will be trying to keep in mind when


I'm working on my own project. And there's some more classes. And takeaways are when they use


their own customized model, it performed way better than some third party model. That's really


important. So that's their business getting sold, their business use case. And additions in one line,


object detection is one thing, but how good does a photo look? So that's another thing they're


looking at for when they advertise their properties. Does a photo look good? So when


someone uploads a photo of their property, does that look good? Like is it blurry or is it just


a crap photo? And learns. So this is some good takeaways. Right down the bottom of the article


is some amazing takeaways. I like these ones. Basically, what it says is data is very important


and don't be afraid to try experiments. So we're going to go to the whiteboard and I'm going to


take what I've learned from here and basically try to structure out the next six weeks and see


where we get to. I think that's enough to begin with. That's for sure. We'll keep it simple. Let


me walk you through this. Let me take it off this here tripod. And so what have we got? Well,


we've got something simple. Project 2020 of flying Airbnb's object detection pipeline.


It is day one of 42. We have one, two, three, four, five, six weeks broken up. And as you see,


the columns aren't that evenly spaced, but it doesn't really matter. Again,


we are cooks, not chemists. So this is Airbnb's metric that they were using for their proof of


concept. That's how this all started out. So when you're starting a project like this, like a


machine learning or data science project, it's always good to kind of set yourself an evaluation


metric. That's step three of the machine learning framework in my machine learning course.


A little plug there, but that's kind of just something that you can work towards,


know what defines success for you. So if I did spend six weeks on this project, which I'm going


to do, what is success for me? So I want to at least equal or better Airbnb's MVP of 50% mean


average precision. We'll get into that. I'll leave a link where you can look that up. That's just a


metric to evaluate object detection models. But I want to at least equal that. And as I said,


I want it to be, this is week five, deploy and make it accessible. Now, of course, all of these


will change, but let's go through them. Week one, which is now, we'll build a small working model.


So something works. We'll get the data sources together. So remember data is really important


point. We'll set up a project outline. We're already starting that notion. Week two, we're


going to refine the data sources because one of the takeaways in the Airbnb article that we saw


was that data makes up a massive part of the project. So you'll spend 90% of your time.


And I've put two weeks here to get data ready. Maybe that might not be enough. As you see here,


is public data enough? Who knows? Week three, I'm going to start scaling up the model with


different data sources that I've collected. So this build small working model is going to take


the data from week one and week two. We'll scale it up in week three. Week four, hopefully we can


finish modeling. Five and six is going to be deploy and make accessible to you. Airbnb used a


REST API, or at least that's what Google's AutoML object detection model was. So just basically,


you can take a photo on your phone, upload it, and get some results back. That's what I would


like to have by the end of this. And then week six is going to be evaluate next steps. What would


I do if I took another six week block using this original project? And is there something I can do


with the retraining pipeline? And another question that I'm really, really concerned about is what


doesn't my model know? So AKA, we'll dive into this deeper later on, but AKA, which samples or


which images, if we did upload them in bulk, which images is the model most confused on? Which is


it most uncertain about? Because at the end of the day, we're not really too concerned on the images


our model is getting right, or the guesses our model is predicting correctly. We're most concerned


about the ones that it doesn't really know. But we'll look more into this later on. Now I've got


a little bit of a rough outline on both the whiteboard and in Notion. I think it's time to


build a small model and get into it. And as I said, this video here is an experiment. It's the


first one. I haven't done this sort of 42 days, six weeks thing. So let me know in the comments


below. We're going to wrap this video up here, but let me know in the comments below if you like this


sort of style. I'm trying to keep them relatively short. I have a tendency to go too long. But I'd


like to make at least a video or two per week of the entire six weeks, basically just giving an


update of where it's at, what I'm going to be doing next, and what I've done so far, interesting


things. If you do find anything interesting, please leave a note in the comment. If you'd like


to check out the 42 days thing that I created, I'll leave a link to that blog post as well.


As you can see here, I've got the project on my wall now. So we've got the start date,


which is today, the 17th of February, and the end date is going to be the 30th of March. So as I go


through, I'm just going to tick off those little boxes. This is fun. I am very, very excited. So


thanks for watching. And again, because it's an experiment, I'm not quite sure if it'll work out,


but that's part of the fun. I'll see you in the next video. I think it'll be either in a couple


of days, probably at the end of this week. It's Monday today. So maybe I'll get two videos in


DALLE-2 has a secret language!? | Theories and explanations

Hello! Did you hear the news? Dalituu has a secret language. If one Letz-Dalituu generated


image from Apoploves reaitais, it will generate birds. Kontara chetkniams lurika tanionons


generates bugs or pests. Miss Coffee Bean, are you drunk? In this video, we will discuss


what the discoverers of this phenomenon have told us on Twitter and in their archive paper


about this. We will see what theories the community has come up with to explain how


Dalituu can generate sensible output from gibberish. And we will realize that we should


guard ourselves from the incoming flood of clickbait titles, because spoilers but no,


Dalituu does not have an own language. Language or not, Dalituu's gibberish is an interesting


phenomenon to look at nonetheless. So let's discuss this in this AI Coffee Break. But


before we dive in, let's thank Weights & Biases for supporting us in this video. Today, we


are discussing Dalituu from OpenAI that generates images from text, only that the code and weights


for this model are not released. But Dalimini and Dalimega are open source projects by Boris


Daima that replicate OpenAI's efforts, and the cool thing is that Boris used Weights


& Biases' reports to track and communicate his progress. Of course, because Weights & Biases'


reports are incredibly flexible, allowing to communicate your work to colleagues, managers


or even just yourself. In this report, Boris is keeping a training journal of how his latest


model training is going, which he updates regularly with notes about new experiments


and changes to the model's training regime that he's trying. Reports are a great tool


for education and sharing analysis for your colleagues or the wider world. The report


here is more polished than the previous one and contains educational graphics as well


as interactive Weights & Biases charts and tables to help the reader understand the results


of his work. Finally, for those of us with not enough time, reports are a perfect way


to create a concise real-time and high-level dashboard for a more focused summary of how


a project or model is doing. Go to 1db.me slash ai-coffee-break to explore and interact


with these reports yourself and see how reports can help you share your work with colleagues


around the world.


Okay, so here's the news. We have this text-to-image generation model Dali2 from OpenAI. It's a


diffusion model that can take in text and produce an amazing picture. If you're interested


in how text-to-image diffusion models work, check out our previous videos on this. But


now here's the catch. Dali2 can not only take in sensible input text and produce its


best shots at an image from this, but no, it can take in gibberish and produce output


that looks really good. And even more, it seems like this gibberish does mean something


for the model, because the combination of something that produces birds with something


that produces bugs in Apoploves reaitais eating contara cet niams luricatagnonuns gives images


of birds eating bugs. Is this language? No, it's not, as the authors have quickly realized


after announcing their findings on Twitter and changed their paper title from Secret


Language to Secret Vocabulary. Language has syntax and grammar, but Dali2 seems rather


to respond at gibberish words. So how did the authors find and generate such examples?


It seems like the discovery happened while the authors were playing with the text rendering


capabilities of Dali2. The model is already known to produce very weird results on this,


so they gave the model an input where it had to produce text, like two farmers talking


about vegetables with subtitles, and found that the produced text is not as random as


one might think. This word, vikutes, produces dishes with vegetables, and Apoploves reaitais


produces birds. So the authors concluded that the farmers must be talking about birds messing


with their vegetables. In this thread you can see other examples too, but what we see


there and in the paper are not really many examples, and it is a bit unclear on what


the success rate of this method is. Sometimes it works, sometimes it doesn't, as highlighted


in this thread, where only 4 out of 10 examples generate sports, from the word tibur, even


though like in the farmers' examples those two men speak about tibur, which seems to


be about sports. So why does this even happen that Dali2 generates good looking pictures


from gibberish? The authors make the fuzzy claim that the model has internally developed


a hidden language, we mean vocabulary, after being trained on image-text pairs. Well, this


is not very specific, so let's look at the theories circulating on Twitter right now,


because there are a few very interesting ones. The first one I saw was by Joscha Bach. He


points out that the text generations are quite inconsistent. In the paper the authors prompt


Dali2 with two whales talking about food with subtitles, but Joscha Bach points out that


the secret words one gets from this are different every time. So Joscha Bach goes on, saying


that the secret words are just random strings that sometimes point to consistent regions


in the embedding space. The model projects the samples into high-dimensional space and


clusters neighboring concepts. Then honestly, I do not get what the rest of the explanation


wants to say, maybe you know, so go to the comments and explain it if you want. So here


is Ms. Coffee Bean's take on this, which might be very different from the one in this


thread, sorry. The model has a limited number of parameters and for efficiency reasons it


needs to cluster the space of words well, so concepts that are related to one another


should be close in this space. Since we are working with neural networks, the text is


represented as continuous vectors, but surprise, text is discrete and is composed of words


that do not have an in-between as continuous vectors do, and since the model always must


produce an output, whatever the input, the in-between words, so gibberish, will also


produce an output. As it turns out, this is sometimes consistent between the string input


and rendered text in the image. How seldomly this works and how inconsistent this is, is


highlighted by another Twitter user, who points out that the bug-producing prompt does not


produce so many bugs or pests after all, since in these Dalitul generations we also have


animals like deer and goats. Still along the line of the discreteness of language are the


opinions that say that the secret language is mostly due to tokenizer effects, since


apodide and ploseide are families of birds, each with more than 100 species. Apodiforms


is the biggest order of birds, with 400 and more species of birds, so the model has connected


the apo- and plo-subwords to birds. Somebody else found that one can infer some of these


subwords that will work with Dalitul by looking at Wikipedia, where actinopterygii and placodermi


are two families of fish, and then placoactin cnunfidc generates fish images. You know,


with neural networks sometimes it is great input in, garbage out. Now it's gibberish


in, quality images out, and everybody freaks out. It's clear that we do not yet understand


these black boxes, and unless some more rigorous interpretability goes into these models, we


will continue prompting in the dark, and we will hope for the best. It's important to


highlight that as long as we are surprised by this weird way of communication from Dalitul


and similar models, we are also ignorant of some security issues. Adversarial attacks with


these gibberish prompts, as well as not so gibberish prompts, can trigger unwanted behavior


from models, circumventing filters on the allowed inputs. It's clear that so far these


models do not behave like humans would expect them to, and malicious humans could take advantage


of this. What do you think about this? Would you be interested to enroll in Ms. Coffee


Burn fat and have fun with these unconventional movements *follow along*

The weird turn pro, Hunter S. Thompson. You know what day it is? It's day 27. It's also


Easter Sunday, so happy Easter if you celebrate it. If not, happy Sunday. Anyway, I'm going


to have some chocolate today. Now today is 27. You know what? You might be thinking,


by the way, you'll need a ball for this one. I was like, what could this be? And for some


reason we've lost it, but I'll get that in a second. I had to fight my puppies for that


this morning. Day 27 reminded me of the 27 Club, if you ever heard of that. It's a couple


of artists that tragically died at the age of 27. That's Kurt Cobain, Amy Winehouse.


There's a few more. Heath Ledger, I think. And now I thought about, yeah, what do they


have in common? And their style was unconventional. So that's the theme of today. It's unconventional.


We're going to do some locomotion type movements. It's not really targeting any one thing in


particular. I need to get control of this ball. It's more focused on just movement.


Now I've been watching Ido Portell videos as well. I'd really like to practice that


style of movement. So if you haven't looked up Ido Portell before, make sure you do. So


today we have five different types of movements. They're animalistic style, as well as a little


bit of coordination. Unconventional sort of stuff. Maybe you would call them animal crawls


or animal flow or just movement. So we have frog hops, bear crawls, sidewards crab, juggling.


You could get two balls if you want, but I've only got one. And then bunny hops because


Easter bunny, we have to finish off with some bunny hops, you know? So let's get on the


starter. We got 40 seconds on, 20 seconds rest. And now again, adding a timer to it


makes this a little bit more conventional. So feel free to just take these movements


and then do them however you want. But I've got a limited amount of time. We've got a


family breakfast again today, which I'm really excited about. So let's get started. The first


one we have is frog hops. So you want to come down, jump towards your arms like this. Arms


forward, jump. And then we'll go back. I've only got a limited amount of space, so we're


doing this one indoors because you might be locked at home for the coronavirus like me.


But that doesn't mean we have to stop moving. This feels amazing on the hips. Beautiful.


And one of the benefits of having the ball is that in the rest time we can practice our


body movement. Get those hands aligned, hand-eye coordination, move around, have a little


dance. My dogs are barking at the moment. Now we have bear crawls. So we're just going


to crawl up. You can go high if you want. I've seen a variation of people going high.


So we'll go high and then we'll come back low for a reverse bear crawl, going backwards.


Just practicing really moving our bodies, twisting our hips, twisting our legs, taking


deep breaths, doing some movements you wouldn't usually see in a standard gym, which is a


great thing. That's what we're doing today. We're getting a little unconventional. We're


going against the grain. We're trying to get a little bit creative. That's what all those


artists had in common, right? They looked at the world through a different lens. They


saw, you know what? I don't like this story. I'm going to make my own. So now we have a


sidewards crab. So you start here and you just bring your legs together like this. So


this is again another way to really loosen up those hips, activate those glutes. Beautiful.


Keep it coming. Now, if you really wanted to go advanced with this one, you come down


to the ground, hands on the ground and hop to the right. It's a little bit more of a


modified crab here. Otherwise, if not, I'm feeling that well and truly in my hip set.


Just a great hip activator. A great way to, I mean, if your ball joints, if your shoulder


joint and your hip joint are tight, your entire body's going to be tight. So anything you


can do to release those and get moving. Great. Now we have probably my favorite, some juggling


one. What's the last time? You know, I tried to learn to juggle in year six when I was


like 11, but I gave up because I only got to do two balls and getting to three was hard.


Maybe that's another project. So this is, we're just bouncing the ball back and forth


between our hands. Keep it in the middle. You can go up, top of your hands. We've lost


the ball. See, that's the fun part about it. You don't know where it's going to go. So


be careful if you're doing the ball inside and you've got potentially expensive equipment


around you. Now the final one is bunny hops. If you can't do these bunny hops, the progression


is to just sit like this. If you can't sit like this, the progression is to just sit


on your knees. But if you can, we're going to just hop back and forth like we're a little


Easter bunny. This is a great one for strengthening the feet, helping with ankle mobility, getting


a little calm pump. If your feet are tired as well from being in a foot prison all day,


from being in a shoe, it might be affecting other parts of the body. We'll do some twists


to break it up. We're back to the frog hops now. Get some air in this room. There we go.


Twist it up. Getting a little bit unconventional. Soon enough, you start doing these kind of


movements and soon enough you'll see these as the conventional movements rather than


the ones you might typically see at a gym or something like that. I know, my perspective


changed. Keep moving. I need to release my hips. Again, no real schedule here. If something


needs to move, it needs to move. That's the important point. Now, we have bear crawls.


The talk test is catching up to us at the moment. Breathing heavy. The closer you are


to the ground, the harder it is to move. Let's go bear crawls, unless you're lying down,


of course. Nice and slow for these ones. Let's go back, feeling out where we need to move.


Crawling, dragging our hands along the ground, feeling the earth. These are great to do on


a patch of grass. Bare feet, bare hands, feeling everything. Come forward. This is a progression


towards the lizard crawl. Beautiful. Do some body whips. After they get their skin, registering


the fat. It's a great one to wake up with. I woke up an hour ago, drank some water. Now,


we're getting into movement. Sidewards crabs. Start up top. A lap each way. Keep going.


Now, we're going to the ground. Jump, jump, jump. That's it. Oh, whole body. Whole body


getting up. Now, you know what? We got the juggle. Can you juggle? If you can, leave


a comment below. You got any resources to learn to juggle? Oh, that was a good count.


Let's go. Hand bumps. We'll try and move around the ball. Keep the ball in the center. We'll


move our body around it. Walk around. That's it. Two on the right, two on the left. We're


going to keep it up for the whole time this time. Let's do a circle. Circle with the right.


Circle with the left. Missed that one. Circle with the left. Beautiful. That's actually


really fun. You can just stand there for a while, practicing, bumping around the ball.


The next one, the next progression is for that, is to whack the ball up in front of


your head with your fists. I'm not up to that stage yet. Now, the final one. The bunny hops.


In spirit of the Easter Bunny. You know I've been doing a bunch of walking around and there's


young kids leaving chalk paintings on the ground and teddy bears outside their houses


in the windows, all to just spread the love, because everyone's locked down at the moment.


Keep it up. We're just hopping. You can try some high hops if you want. Yes. Look at that.


Where's our ball? I got to go and return this to the puppies. Let me put that on pause.


That was actually really fun. I had a lot of fun trying to come up with that one this


morning. I was like, yes, day 27, we've done a whole bunch of stuff. We've covered basically


the entire body almost with body weight sort of stuff, except for anything to do with major


pieces of equipment that you may or may not have at home. I was like, yes, let's get a


little bit unconventional. We've covered some of the exercises before, like the bear crawl,


the cybers crab, the frog hop. We haven't seen the juggling or the bunny hops before,


so give that a try. It's a whole body session, a little bit unconventional, but trust me,


when you start to do them, when you start to feel what it's like to try different movements,


to practice different things that you haven't tried before, you start to go, you know what?


10-minute Morning Wake Up Stretching Routine for Beginners

Good morning! We are up to day 14 of Reps For Rona. And you know what that means? A lot of people


who were coming back into the country, like for example my friend Justin, we were having a


conversation this morning, he had to go into self-isolation for two weeks. And since we're


up to day 14, that means two weeks. Two weeks of doing Reps For Rona. If you've been following along


for every day, you've been doing the movement, if you're watching this in the future, this series


is doing 10 minutes of movement every day while the coronavirus is alive and taking over the world


basically and everyone's indoors. It's paramount that even though you're indoors and you're,


a lot of people are on house arrest, it's that you keep moving. What does it do? Helps boost your


immune system and plus it's fun. So today on the menu is we are adjusting as needed. The last few


days we've done a lot of tense exercises. I explained this in a previous video about life


being like an accordion, same with the body. Some exercises tighten the body up and other exercises


loosen them. And so today we're adjusting as needed. I woke up this morning feeling a little


bit tight and it's still morning, it's almost lunchtime here really, but this is the theme


today is adjusting as needed. This is going to be 10 minutes of wake up stretches. I like to get


moving as soon as I get out of bed or really just anytime I've been inactive. So whether you're just


getting out of bed or you just decided you want to get moving for 10 minutes, these are some


stretches slash movements that you can do anytime of the day. But let's get started. We've got 10


minutes on the clock. We'll start off with the lunge kneel, then we'll do the shin underbody,


Jefferson curl, squat reach, and then arms crossed underbody. So let's get started. Whole body,


we're trying to mobilize here. This is if you're just a little bit too tight, you've gotten out of


bed and you want to get moving. So let's come to the ground. We're starting with a lunge kneel.


Now you can start off like this. This is probably the first stage that you'll get to is just have


one knee back, one knee forward. In my case, I'm doing the left side for the first round.


If you want to go more advanced, you can put your elbows on the ground. What we're trying to


do here is we're not really staying static. We're moving around. So try and look behind your knee


and come this way. Look towards your foot. Just trying to get our bodies moving. And now I've set


this up to be 30 seconds on, 30 seconds off for the sake of 10 minutes. But this is something that


you don't necessarily have to, you can take as much time as you want, especially with mobility.


In fact, it feels better the longer you do it. It's like a relieving pain. The next one,


we have a shin under body. Remember for the first round of this five exercises, we're doing


the left side. So this is where we're going to get our leg horizontal underneath us. Now you might,


if you're a bit tight, you might have to come start like this. But if you've had some practice,


you can move your leg up, hold your right hand on your left ankle. And we're just going to sit here,


go back and forth, looking forward, a deep breath. If you're feeling it in your hip here,


try and breathe into that hip there. Again, keep moving. We might even hold these for a little bit


into the rest period because that's when most of the benefits start to come. After you've gone


through that little bit of, and what I need to stress here is that I'm not holding it in any one


position. I'm digging around. I'm adjusting as needed, finding the parts that need a bit more


stretching than others. See, that's a nice tight little bit there. So we'll just squeeze my glutes


there. There we go. There was a full minute. I've got to check what the next one was.


Now, Jefferson curls. This is one of my favorite ones ever. If you have a weight here, you could


stand up on the elevated platform and then hold the weight in front of you. But what we're going


to do, head forward, touch your chin to your chest. And we're going to bend our spines as if


we're bending every vertebrae one by one. And then all the way to the bottom, the slower the better.


Touch the ground if you can. We're going to keep going through the rest of this one and then curl


back right up to the top. You can also reach out to finish this one off and then come down,


hands to your chest, chin on chest again, all the way down, stretching out to the bottom.


And now when you're here, you can shake it out like you're a broom, hands are brushing the floor,


and then curl right back up to the top.


Oh, beautiful. I'm feeling better already. Getting jumping and jiving. And now we have a squat reach.


This one's probably a little bit advanced. If you can hold this one here, we're going to reach up.


But again, if you can't, just hold a squat like this, reach up to the roof. But I'm going to go


right down to the bottom, grab a heel, reach up. Same thing to the other side. Reach up,


reach up. Same thing to the other side. Reach up, nice and slow.


Deep breaths. We're going to go all the way through the rest again.


You could even hold just a squat here and then just move around.


The goal here is just to mobilize. We've just gotten out of bed, lying flat. You may have to


do a little bit more of a warm up to get this deep in a squat if you've just gotten out of bed


or maybe you've been sitting down all day. You just want to do some wake up stretches,


some wake up movements. You're going, hey, body, let's feel what it's like to be here.


There we go. Beautiful. So now we're going to do arms crossed under body. I'm going to go with my


left one in front. So come down onto your forearms, put one in front of the other. My left arm is in


front of my right arm. I'm going to roll side to side with my arms underneath my body. You can even


hold it here. We're going to cross over. Look at all the dog hair on my ground, on my floor here.


My puppies have been coming in and out like it's no tomorrow, but that's okay, man.


This is beautiful. Hold it. We're going to hold it. A really deep breath into the back,


back of the shoulder. And then on the exhale, let's sink down.


Try and get that forehead to the floor.


Hold it.


Beautiful. Now, we're going to come back.


Beautiful. Now, we're going to come back into the leaning lunge. So this time my right foot is


forward. We're alternating. So remember, if you can't get your elbows on the ground, you can come


here. I want to emphasize the fact that you keep moving. Look behind, look at your foot, look over


your knee, then come to the other side. Look back to your foot. If you can, go to the ground with


your elbow. So I just found out that this side is a bit tighter because my elbow doesn't touch the


ground as easy, but that's all right. That's what you want to work on. So I'm going to come around,


look behind my shin, or try to, that is, and then reach over, look at my foot, come back to the


middle, hold it there, work out that nice tight hip. Find, adjust as needed. Find that tight part.


Just, I like to call it cleaning out the cobwebs. I'm finding the cobwebs,


finding the rust in my ball joint, and then getting rid of that rust. So now we've got the


right leg with the shin under the body. Same thing again. You can sit down on the right side of the


glute. Hold your right ankle with your left hand. And then we're just moving around again. If you


can, you can come forward, lie down like this, but you don't have to, of course. You can just sit up


like this, try to get your leg parallel. And we're going to hold it through the rest period as well.


So that way we're getting about a minute, a minute or so on each of these, at least twice. But for


the ones we're doing the single side, it's about a minute at least. And that's a good amount of time.


60 seconds is probably the sweet spot. If you want, you can, if this is feeling good by the end,


I mean, it's feeling great for me now. Just to get active, get moving, get rid of that tightness


in the body. When there's tightness in the body, there's tightness in the mind.


All right, we're back to Jefferson Curl. So standing up straight, chin on chest.


Deep breath, we're going right down, just sinking down.


Can you touch your toes? Can you touch the floor? Can you get your elbows to the floor?


No, I'm kidding, I can't do that. A little swivel when we're down here, because we're playing around.


Come up, not very structured, just nice and slow. Deep breath at the top, let's come back down.


Breathe out so you can hear it. I want to be able to hear it.


Very nice, keep it up. Getting mobilized, just working up, getting the blood flowing a little bit.


Nothing too strenuous.


Just moving, feeling good for being able to move. We've got the squat reach. Let's come down.


You can hold the squat if you want. Left ankle, right arm to the sky. Right ankle, left arm to the sky.


Hold the squat if you want. Left ankle, right arm to the sky. Right ankle, left arm to the sky.


Hold it, back down. Reaching. Excellent, keep it up. This is one of my all-time favorites.


We're going to hold that there. Nice and deep squat hold if you can.


If you can't do a squat hold like this, maybe you want to hold on to something.


Just use this as a leverage so that you don't fall backwards.


Then just work on moving around. Stretch out those hips, stretch out those ankles.


Come up into a nice tall position. Deep breath to tell your body that this position is okay to stay in.


We're back. We've got the final one, which is arms crossed under the body. I'm putting my right arm


in front of my left one this time. We'll go up like that. We're going to spend the first 30


seconds rolling back and forth. I think this is underrated. The value of being on the floor


and rolling around. We could even just go like this just to mix it up. Come up, come back down.


Right arm in front. Now for the last 30 seconds we're going to hold the right arm in front and


just sink down. You know my friend Don, he's really flexible. He can get both of his arms


fully flat on the ground and then his face is basically touching the ground. Whereas I find


if my shoulders, if I've been sitting at a computer desk for too long, like that one, training machine


learning model, my shoulders get really tight and this position is kind of painful to begin with.


One big breath. Hold it in until we hear the victory.


Done. Great workout.


Listen to that.


This is seven seconds exercising.


How good. I mean that was 10 minutes but I could definitely keep going with that. So we did,


we started off with the lunge kneel, alternated. You might want to do two sessions of that so that


way you get at least two minutes per leg. Then we did the shin under the body, the Jefferson curl,


chin to chest. So important to get that spine, get that spine mobilized, squat reach and then


we did the arms crossed under the body. Now the metaphor or the theme for today is adjusting as


needed. I think that's what the whole world is doing. You see a really, a really loser way to


think is by always saying to someone you could have done that sooner and I think that's what's


happening a lot right now. You see people trying to make decisions, doctors, politicians, everyone,


leaders. Of course every decision you ever made you could always say with any of them you could


have made that decision sooner. What I think is happening right now is the world is adjusting as


needed. Just like what we're doing. We're getting out of the bed, feeling a little bit tight and


then we're doing this workout to adjust as needed. So leave a comment below. How are you, how is your


lifestyle adjusting as needed? Have you been following along with the 14 days? What other


kinds of workout would you like to see if there are any? But otherwise keep moving, adjust as needed,


Taking Bumblebee for a drive! (455hp Camaro SS)

You know what this is? We just rented a car. Let's go check it out. We're gonna do a big drive along the coastline.


Okay we need... what is it?


All right we're looking for P... it's not focusing. P22. E.D. All right let's find P. P22.


P22. Thank you. I hope it looks like that.


P6, P7. Shouldn't be too far away. P19, P20.


P20. Oh yes. This is us. Look at it. P22. We got Bumblebee! Hey Bumblebee.


What? Oh I've gone to the wrong side. The driver's side's on the other side.


This is America. Keys are in it apparently. Let's go for a ride. There's no key on this thing. Hold on.


Oh baby!


I had to make a pit stop. It's actually not too bad of a bad view.


Look at that! It's no great ocean road but it's close.


Oh yeah so I realized that most of the clips I took at the start of this video,


the microphone wasn't on. I think it should be now. Look where we are. See that bridge right down


in there? I'm pretty sure that's the bridge that gets used in a lot of different car commercials.


Oh and the Pacific Ocean is looking beautiful as this beast is. Look at that. It's been so much fun.


I actually had to wind the, put the top on because it was getting a little cold but now the sun is out


and I am excited. We're gonna go probably go check out that bridge and in the meantime I'll put some


b-roll over it until we get there which which just means a few clips of of scenery and then


we'll do some more adventuring. It's been a fun time exploring in this thing.


I'm not the biggest fan of driving but I can make do with this.


It's on top of a rock. Look. Nothing around.


What a cool little place. You probably get lonely sometimes but it is what it is. All right we're


about 13 minutes away from Big Sur. I'm not even sure what Big Sur is but we got a wide open road


ahead. Let's do it.


Pit stop. All right I think I think we've made it or we've even passed it. I'm gonna keep going


for a little bit and then see if it's an actual destination. It might just be a national park


but we'll figure it out.


All right I think I've gone way past it. Maybe not way past it but a little bit past it.


I think it was just a national park but the view is good enough for me. Look at this.


That's what it's about.


That's all I need. I don't need some big icon or destination place to go to. This is the


destination for me. That sunset's going to be epic. I'll probably turn around soon because I want to


I want to drive home. Well I don't really have a home tonight. I haven't booked anywhere to stay


tonight. I'm going to take the car back to San Francisco but I think today's trip or where what


we've done today is kind of like a a metaphor and I'm about to go real deep here. I've been thinking


because the open road is is such a great place to to think deeply. Bear with me. But I think today


has been a great metaphor for something that I've only just come to the realization the last couple


of years. It's life is not about the destination. So today I was looking for this really cool


like I thought it was a mountain of some sort. Big Sur. I'm probably going to look it up when I


get home. You're going to look it up online and be like Daniel you idiot. Might be a national park


or something like that but that's how I plan things. I sort of just go and see how it turns out.


But I think I realized a couple of years ago or maybe 18 months I don't know recently fairly


recently in the recent life that the goal the destination is not the goal. The journey is the


goal. So the the whole trip that I've done the winding roads the driving through forests the


the singing out loud to the music in the car that's what it's about. Not just just arriving


at a point. And that's what I've found the most fun out of is the journey. So when I competed in


bodybuilding with my friend the funnest part was not getting on stage it was it was working out


every single day with with my best mate and challenging ourselves. And getting a role as


a machine learning engineer the fun part wasn't necessarily signing the contract to get the role.


The fun part was studying and challenging myself every every day. And that's once I think once you


realize that that's that's when you're in you get in a good place when you realize that the


the journey is the goal right because then you're driven day by day not just by an end point. And


that's that's how I've trying to be trying to be trying to trying to live life lately is day by day


because you have one perfect day eventually that turns into a perfect week and then you have a few


perfect weeks and becomes a perfect month a few perfect months 12 perfect months becomes a perfect


year well not perfect it won't be perfect but you get the point well it could become a good year


and then enough good years you end up with a good life. But I think it's I'm going to go find another


place we'll watch the sunset we'll get a maybe get a time lapse of that if the camera battery survives


and then start heading back to San Francisco before it gets too dark.


All right cool story so I checked out of this hostel this morning drove 500 miles down the


coastline of America specifically this bed as well and I come back I get to the bath


I left my toothbrush here I had no idea where I was going to stay tonight and I come back


check my bag this bad boy is not here but it's still in the bathroom it's meant to be


This graph tells you whether you're intelligent or stupid

Future's looking so bright, we're gonna have to start wearing sunglasses indoor.


Or what? We're on? Oh well, hello there, happy new year, happy 2020, I hope your 2019 was


incredible and I hope the same for this this brand new decade that we're in. You know it's


an exciting time right, what's happening in the world, all you have to do is just look online and


you just see so many new things going down from data science to machine learning to deep learning


to all kinds of different technology to renewable energy to biotechnology to insert something here


technology. It's an exciting time and that's not really what this video is about, it's about,


well better get rid of that. I read a book recently, it's called the basic laws of human


stupidity, it's quite funny actually and there's a little graph in there that is very simple and


often the best things are simple and I've been thinking about it ever since I saw it. So that's


what I'm going to talk about here, it's probably the, I don't know, let's try to keep this video


nice and swift, let's keep it under 10 minutes, you know I have it if you've been on the channel


before I have a tendency to ramble upon things and just start talking about things that don't matter


but let's dive into this graph. First I'll draw it up and then I'll explain it. So it's actually


just an x y axis, you can go here, here, here, here and there's four quadrants. Up here we have i, b,


that's a b, h and then s and so what are the, what are the axes and what do these letters stand for?


Well over here we've got helps oneself and up here we've got helps others.


You might be wondering what do the i, the h and the d and the s stand for? And one of the funny


things right at the start of the book, man this chair is creaky and I apologise if there's


construction noise, one of my neighbours seems to want to use power tools every single day,


I think they might be building like a spaceship or some kind of underground bunker because the


construction has been going for that long, like seriously it's every day, it's a lot of work.


Construction has been going for that long, like seriously it's every day, but no complaining,


that's rule two, no complaints. But these quadrants here, this is why I've been thinking about it,


because it's a change of year, it's 2020, I don't have a resolution or a goal or anything like that,


actually the only probably goal that I have is to keep myself employed,


so I need to work towards that, to do things to keep myself, end of last year I employed


myself, started my own business and that's the goal for this year, just keep myself employed,


keep working on the things I want to work on, but pay attention to this graph here.


So the quadrants, i stands for intelligent, b stands for bandit, s stands for stupid and h


stands for helpless. Now if you have a look at this, you can probably figure out


why they're named what they are, and one of the premises of the book, The Basic Laws of Human


Stupidity, is that the average person severely underestimates the number of stupid people


in circulation, I love how they use the word circulation, and so that is in this bottom left


quadrant, it's not where you want to be, and so I did a little experiment with this, it's my thought


experiment is how can I spend 2020 or the next decade, you know because it's a shifting year,


right, it's like everyone's thinking about oh what's my new year's resolution, oh can I make


a change, what can I do differently this year that I haven't done in the past, and I'm thinking


about that too, but truthfully this is probably my only guiding principle, and I think it's simple


enough that you could adhere to it too, as long as you're not in the s category, but I mean everyone


says that they're not in the s category, it's alright if you are, I've been there before.


So this is what I'm thinking about, the top right quadrant is an intelligent person,


and their actions, of course we're talking about actions here, it's a different thing between


thoughts, because everyone has stupid thoughts, let's be real, in the top right quadrant,


the intelligent person, what do their actions do? Well at the same time as helping themselves,


they help others, so that's the ideal place you want to be, right, we'll just put it in here,


maybe you can't see this on the camera, I don't know if the glare or the angle,


but we're just, what I'm writing here is where you want to be, and because it's a new year,


it can't be a good time to think about making a change, and it doesn't really have to be a new


year, I mean any day of the year is a good time to make a change, any moment is a good time to


make a change, there's this concept in, I think it's Buddhist philosophy or something like that,


or maybe not even Buddhist, so just, let's just, this is a concept, and it's a sudden versus


gradual realization, and you have a choice, you can take a while to come to a realization,


know it, if you already know it deep down, your instincts, but your instincts are going against


thought, you're holding yourself back, trust me, instincts evolve from evolution, we've only just,


you can't change those, you're born with those, whereas thought, you kind of learn as you go,


so trust your instincts, is a long story short here, but it's the sudden versus gradual change,


you can make a change like that, all you have to do is just get rid of the old thoughts that are


holding back that new change, so this part of the axis is where you want to be, if we had lots of


people here, that'd be great, but truthfully, even if you know the concept, some people are still


going to end up in this S category, now let's describe the rest of the graph, the B is bandit,


so a bandit is someone who helps oneself, but doesn't necessarily help others,


and truthfully, that's actually not too much of a bad place to be, because you're not really


burning anyone, it means that your actions, if you're a bandit, it's like net neutral in society


and the people around you, so you're out for yourself, and whatever you do, benefits you,


but it doesn't really benefit many other people, but it also doesn't take away from other people,


that's the important part, important part, oh we're not talking about shipping channels,


Daniel, come on, that's bandit, helpless, is someone who helps others, but doesn't help themselves,


now when you think about it, why would it be called helpless, you could think that's kind of


harsh, when someone helps others, but not themselves, you could call that self-lish,


self-less, but the reason why it's called helpless, is the same principle as when it's,


when you're in an aircraft, and you go, the safety announcement comes over, and they tell you,


put on your safety mask first, the reason being is because, if all you're doing is trying to help


others, and you're not helping yourself, that means if something goes wrong with you, you're


pretty helpless, because all you're doing is just giving away, now an intelligent person


could help themselves, and help others at the same time, now a helpless person forgets to take care


of themselves, they're constantly thinking, oh my gosh, I need to take care of this person,


I need to do that, I need to do this, I need to do that, and all of a sudden, they end up as a


train wreck, because they forgot the most important person to take care of first, is yourself, put


your own mask on first, and finally, the bottom left, we've already spoken about this one, well


this is the stupid, stupid quadrant, now this is someone who not only doesn't help themselves,


their actions actually degrade from themselves, and their actions also degrade from others,


this is what you really want to avoid, now a fun exercise for this is to introduce this concept


to your friends, maybe to your family, or wherever you want, or just think about it yourself, and


think about the people you spend the most time with, think about the people you hold in, in high


regard, someone that you look up to, where would they fit in each of these quadrants,


and I mean, I'm not perfect, I've spent time here, being stupid, I've spent time here being helpless,


I've been spent time here being a bandit, but my perspective is, I want to try and move towards


the intelligent quadrant, and so I did an exercise with my friends the other day, and we're like,


I told them about this concept, and they're like, where would you place each other, and it's really


tough, I mean, the most valuable opinion on this, or thought to consider is where you'd place yourself,


and you have to be really self-critical about this, because at any one time, you could change


if you're not thinking about what's going on, thinking about where your actions could go, and so


this,


where the ideal place is,


where the ideal place to start trending towards is the intelligence section, where the ideal


place to surround yourself with the people you want to spend the most time with,


is the people who you would place in the intelligent quadrant, and how can you demonstrate,


how can you help someone move from here, well the first step is remember, put your own mask on first,


make your actions move towards this, and then truthfully, it's up to the individual themselves


to recognize where they are on this little plot here, and then it's up to them themselves to decide,


okay, I'm being pretty stupid this last year, I want to move towards intelligent, I want to help


myself, I want to take care of my physical, my mental, my spiritual health, and at the same time,


I want to do things that help others, so I think that's a good place to finish off,


I just wanted to introduce you to this fun little concept, and fun little exercise that you can try


with yourself, really be honest with yourself, you could try it with others, you could write it down,


I spent some time journaling, trying to figure out what I could do, where I could end up on this,


and again, it's an iterative process, you're not going to constantly stumble upon the answer,


what's better is rather than looking for the correct answer, is asking the question,


or continually asking the question, how can I move myself more towards that intelligent bracket,


but it's an exciting new year, it's a new decade, and if you're new to this channel,


it's an exciting new year, it's a new decade, and if you're new to the channel, welcome,


I'm going to make sort of a lot of videos this year, put it that way, well I hope so, I hope to


keep making videos, as long as I'm here, I'll keep making videos, and I mean here, as in just


in this existence, my dogs are starting to go off, they must be getting suspicious of the


the man next door building that spaceship, otherwise I'll leave you off with one more


question that I'm thinking about, because when I read this, it hit me like a ton of bricks,


it's if you could spend a year working on something that wouldn't, is not so much important,


but would be really interesting, what would you work on, if you watched it here, and you've


thought about that question, leave a comment below, I've been thinking about it, it's been


the thought topic of many walks, otherwise I'll leave some resources in the in the description,


that you can read more about the basic laws of human stupidity, where I got this this chart from,


and an essay by Paul Graham, where I got that question, I just just dumped on you right at


the end of this video, but otherwise, have an amazing day, and I'll see you next time,


deeplearning.ai Sequence Models Course Progress | Learning Intelligence 21

Hey Siri, play my shower playlist.


Okay, playing playlist shower.


Music


What's going on guys? Welcome to Learning Intelligence episode 21.


And this week's episode is all about sequence models.


So using AI to deconstruct data over time scales.


And that's the driving force, sequence models are the driving force behind technologies such as Google Home, Alexa and Siri.


And I think voice is going to be the next big epic platform.


This is an expanding space and I had a lot of fun this week learning some awesome things.


The past two days I haven't really got much done.


And that's because I've been saying yes to different things and things have come up, things I had to take care of and whatnot.


I woke up this morning, I was feeling pretty down.


I was pretty down on myself. I'm like, I should have been doing this.


I'm not hitting the goals I set for myself each day.


I was writing about it because I was kind of having a conversation with myself.


That's what I do every morning in my journal.


And I realized I come to the conclusion, you can be too harsh on yourself sometimes.


Because you got to be your own harshest critic as well as the same time you got to be your own biggest supporter.


And I realized it came back to a point that I read in one of my favorite books of all time,


Love Yourself Like Your Life Depends On It by Kamal Ravikant.


And I wrote down, would I be treating myself like this if I truly love myself?


And which I do of course. It's taken me a while to get to here.


But I realized if I'm being this harsh on myself, it's not reflecting the fact that I truly love myself and I'm my own biggest supporter.


So I do believe you have to be firm on yourself.


But you also have to realize that things are going to come up, things are going to get in the way.


You're always going to hit your goals and whatnot.


You may have study goals, you may, for my example, you may not hit them all the time.


But as long as you keep putting one foot in front of the other, you keep making little incremental goals,


come back to it, which is what I'm going to do today.


I've got some time, I've blocked out, I've closed my door.


Door to my room is closed.


I'm going to spend the next couple of hours getting back on track.


And I think that's probably the most important part is that we will have times in life.


This is like a philosophical digression from the normal content you see.


That's a big part of my life too. I love reading philosophy and learning about different ways of how to live.


So I believe it's important you got to be firm on yourself at the same time realize these stumbles will come


and get back on track.


You can get back on track. That's the most important part.


If you can get back on track and get back to where you were and set yourself a few goals


and slowly start building that momentum back up, then what are you worried about?


What are you so worried about? And this is sort of a reflection to myself, a lesson to myself.


And so I'm going to get back into it. I know what I have to do, set myself some work for today.


And I realized if I can't get it done all today, because I've sort of backlogged a few things that I wanted to get done in the last two days.


And if I can't get it all done today, that's all right. Tomorrow's another day. We're going to keep pushing forward.


Guys, I'm heading into my local startup hub. There's an event on AI and healthcare.


Two of the areas I really love and where I want to get into.


And so I'll film some stuff there if I can. And when I get back home, I'll show you what I've been working on.


It's really cool. Well, I find it really cool anyway.


So I just got home from the AI and healthcare meetup and it was awesome.


Some really great insights into, there was one of the professors at the Gold Coast Hospital, which is a major hospital near my home city.


He was giving a talk on how he's foreseeing how AI can be implemented into his hospital.


They're already starting to see deep learning models on the data rich hospital.


The data sets in hospitals are incredible because they just collect so much data.


They're seeing deep learning models improve some of their, they use logistic regression on most of their data.


And so the deep learning models are already improving them by up to 10% in some cases.


And for that, like the healthcare, the amount of money that goes through there, that 10% in saving or 10% in just, not even in money, actually, in patient diagnosis.


Rather than giving someone a cookie cutter healthcare plan, it's really moving towards how do we tailor a specific plan per patient?


How do I treat this patient, the one I've got in front of me, rather than averaging a whole bunch of treatments from someone else?


That sort of stuff really excites me. That's what I want to look at.


To me, the hospital is sort of a reactive measure.


I would prefer having a nutrition and fitness background using AI to work on principles to prevent someone from getting into a hospital in the first place.


So that's where my goal is, is to use AI and healthcare in that space and really let people live the healthiest version or become the healthiest version themselves,


leveraging AI technologies before they end up in a hospital.


So it will prevent them from getting into a hospital because I don't know about you, but I'm not a fan of spending any time or as little as time as possible in hospital.


I want to be the healthiest version I can outside of hospital.


Let me show you what I was working on yesterday.


So this is project two of week one.


So it's Dinosaur Island, create a character level language model final version.


And so what we were doing was using RNNs to take an input of text.


In this case, it was a list of dinosaur names and output a bunch of new dinosaur names.


And this one was my favorite, Lit-a-saurus.


That was a really fun assignment.


And then the next part was we used a bunch of Shakespeare text, analyzed that, and then we put an input into the RNN and use the data from the Shakespeare text to produce a poem based on that input.


Let me show you mine.


We'll find it down here.


So there we go.


There's the man himself, William Shakespeare.


And I'll read this out for you.


Here is your poem.


So the input I used was I love artificial intelligence.


I love artificial intelligence by Daniel Burke and William Shakespeare, courtesy of a recurrent neural network.


I love artificial intelligence.


So confond, test mest mos as yet bied, and de chop de I heldt mol nom moem I fall astore.


That funda loras o wanco su of payet.


My ole is my betes ever loge for ferte.


Is death the quiets for seds with defore?


But bum lay ever not, pair of nom, heel ot es sittefe.


Prove the wan wongness so hot to mine ander.


Thought dece kill clive, sunce cun that side ot.


Nor were to ach wote with derard.


That I kit.


Almost sounds like Lauren Ipsum.


I think that's really cool.


Even though it was virtually gibberish, the structure of the poem is there.


So it started off with I love artificial intelligence.


Who knows if it uses this to produce that properly.


At least the lines are intact.


The words are actually the size of words.


So that's why I could actually read it.


If it wasn't, if they weren't that size and they didn't have vowels in the right positions or most of the words,


I wouldn't be able to read it at all.


But check this out.


We go up here.


Pass that one. 100% out of 100%.


And where are we up to today?


So today I'm going to be working on jazz improvisation with LSTM.


And one more thing I want to show you is this book by Francis Chollet.


I think I'm saying his name right.


Which is from the authors of Keras.


I got recommended this book on my medium, on one of the comments of my post.


And I'm reading it so far and it's incredible.


So I haven't decided yet if I'll buy it, the whole thing.


But I'm reading the sample chapters.


I think there's a few free ones here.


What is deployment? Look at that.


There's so much information there.


Before we get started, the math of neural networks.


That's free as well.


So I'll leave a link to that in the description.


Upcoding early this morning because I'm meeting a friend out for breakfast.


Really close friend of mine.


So I'm excited to see him and talk about the stuff.


I'll probably talk about the stuff I learned at the meetup last night.


That was really fun.


Probably more on that meetup or not the meetup, sorry, but AI and healthcare in the future.


So stay tuned for that.


Oh, yeah.


Check it out, guys.


So I've just passed the final assignment of week one of the Coursera programming assignment,


Jazz Improvisation with LSTM.


It's the third project in week one of the sequence models course.


And that's, of course, what this week has been all about.


But that's boring.


Let me show you what I actually did.


We go into this Jupyter notebook here.


This assignment was improvise a jazz solo with an LSTM network.


So ideally, we were going to send our friend a copy of a brand new jazz solo.


I can't play any musical instrument.


I should be able to.


That's really, that'd be really fun.


But anyway, I can use AI to play them for me.


So this is the initial data set.


So we will train an algorithm on a corpus of jazz music.


So this is a little example.


Can you hear that?


We go DJ mode.


All right.


So that was the input and that's well and truly already above anything that I could ever do on my own


unless I devoted lots and lots and lots of practice to that.


So what did we do?


Well, we grabbed a few samples of that and then we built an LSTM or an RNN network.


We'll go through here.


I'll skip through some of the details there.


But essentially, this is the type of network we were building.


So we had input LSTM cells, outputs,


and then these outputs would be forwarded to the next cells and continue on and continue on.


And then we go down here.


Once our model was trained, here is my output of my own brand new jazz file.


So let's see how that sounds.


It's like I'm in an elevator.


I don't know if my friend would really appreciate this, but it's for you, friend.


So that's really cool.


That was the assignment for the week and that was really fun.


That to me is something that it just shows the power of AI.


For example, as I said, I don't know anything about musical instruments.


I'm probably offbeat, especially with my dance moves and whatnot.


But the fact that we can use AI to help us with these things is what really excites me in the future.


It means that people in certain fields, if they don't know how to do things,


they can recruit the power of artificial intelligence


if the human intelligence isn't available to give them a hand.


Imagine in the future, I could just ask Siri, like I did at the start,


to generate me an entirely new playlist that no one's ever heard before just for me,


just for my own personal interest.


And it's making it up on the fly.


That's something really cool and potentially something you'll see in the near future.


One of the takeaways from that project, I'll show you here.


Here's what we should remember from that project.


A sequence model can be used to generate musical values,


which are then post-project into MIDI music, which is essentially just a music file.


Fairly similar models can be used to generate dinosaur names or generate music.


That's what we did in the last project.


And then in Keras, sequence model generation involves defining layers with shared weights,


which are then replaced for the different time steps.


Because of course, the sequence model is over time.


And now that's going to wrap up Learning Intelligence 21.


Let's get into some shout outs.


Alrighty then.


So, these beautiful people have reached out to me on one way or another,


either via email, danielatmrdberk.com, or twitter, at mrdberk.


I almost forgot my own twitter handle then, that would have been interesting.


Or YouTube comment, of course. You can leave a comment below.


Anything you send to me, I'll definitely do my best to answer your questions.


Ask me whatever you like.


What did I have for breakfast last week?


Good question. I can't really remember.


I think it was potentially a protein pancake, but I made a video on that.


Check that out if you want.


Anything you like about AI, fitness, health, life.


I'm happy to do my best to answer your questions.


And if you want to leave a comment below, that way other people can check it out.


Without any further ado, thank you so much to Saurav Anand.


Thank you for your kind words, Saurav Anand,


and all the best with the deep learning Nautilus degree.


I know you just signed up to it and I know you're doing it at the same time as work.


And you're almost looking to, I think you're looking to move on as well from your job


and break into the world of deep learning and AI.


So all the best with your learning journey.


If you have any questions for me, of course, if I can help out in any way, let me know.


Ahmad, thank you for the great question on last week's YouTube video,


last week's version of learning intelligence.


So what are my plans after I finish my machine learning and deep learning learning journey,


the AI masters curriculum?


It isn't completely set in stone, but I know the trajectory I'm heading on.


Once I finished my curriculum, once I finished all the courses,


I'm looking to move into the AI and healthcare space.


So what does that mean?


Well, I want to join an AI and health starter or an AI and health-focused tech company or create my own.


So of course, I'm looking for a job somewhere in the field of AI, particularly in health,


but as whether it's through my own startup or through someone else's,


we'll see how the future plays out.


But of course, I'll bring you guys along with me for the journey.


And last but not least, Shaikh Asad, you've started your own YouTube channel,


you're making guides on GitHub, you're an absolute wizard.


I had a conversation with Shaikh a few days ago actually,


or a few weeks ago, I posted the video on my YouTube.


He's an amazing AI developer, 14 years old from India.


He's going to change the world. He's definitely going to change the world.


I look forward to meeting you eventually in person, but as for your support,


I can't thank you enough. I really appreciate it. So thanks, brother.


As for plans for next week, next week I'm going to be jumping into the final two weeks of the Sequence Models course.


I plan on finishing the Sequence Models course on Coursera by the end of next week,


potentially by the start of next week, and then from there,


we'll be going back into the Udacity artificial intelligence nanodegree.


So I'm having a really great time and learning so many amazing things.


And as I said in the video earlier on, sometimes it does get a bit hard,


and I know I do portray a really excited personality on these videos,


and that's generally how I am, but don't get me wrong.


You still get up those days and it takes a lot to get into it.


And what's important is not to be hard on yourself when that happens.


It's to just write down what you want to do and write down the next actions that you want to do


and just slowly work towards those goals because sustained effort over time is what will get you towards those.


I almost forgot, the question of the week, it's going to be a new segment I'm going to put at the end of each video.


This week's question of the week is, if you had a choice to use Sequence Models to build some kind of technology,


let's say you built an Alexa skill, what would it be?


Leave a comment below and I'll shout out the best comment in the next week's video.


Keep learning.


It didn't stuff that one up. Yes.


Drawing Flowers in Python

Okay, so my task was to draw one of these shapes using Python.


Drawing Flowers in Python

And now I didn't exactly draw one of these shapes.


Drawing Flowers in Python

I just decided to draw some pretty flowers on my own,


Drawing Flowers in Python

which may be a bit easier than drawing something like that or that.


Drawing Flowers in Python

But nonetheless, I'll show you what I drew anyway.


Drawing Flowers in Python

So we'll just move this off the screen.


Drawing Flowers in Python

Here's my code.


Drawing Flowers in Python

I'll show you what it does and then I'll walk you through each of it step by step.


Drawing Flowers in Python

So we'll start off, we'll turn the speed down a little bit.


Drawing Flowers in Python

Let's make it 8.


Drawing Flowers in Python

Save it.


Drawing Flowers in Python

And go up here and go run.


Drawing Flowers in Python

Oh, there's an error.


Drawing Flowers in Python

This is all live.


Drawing Flowers in Python

There we go.


Drawing Flowers in Python

Maybe that'll work now.


Drawing Flowers in Python

Run.


Drawing Flowers in Python

So, we've got a little turtle there.


Drawing Flowers in Python

Using the Python draw function, see that one drew a flower to start with.


Drawing Flowers in Python

Didn't intentionally make it look like that.


Drawing Flowers in Python

Then we've got flower 2.


Drawing Flowers in Python

And then it finishes up with a blue flower.


Drawing Flowers in Python

You get the point.


Drawing Flowers in Python

So, how did we get from this to this?


Drawing Flowers in Python

And now I think the graphics is going to be not responsive.


Drawing Flowers in Python

That's all right.


Drawing Flowers in Python

We can run it again.


Drawing Flowers in Python

So, what do we start with?


Drawing Flowers in Python

Import turtle.


Drawing Flowers in Python

Now, why do we import turtle?


Drawing Flowers in Python

Because turtle is a library of, let's just call it drawing,


Drawing Flowers in Python

a whole bunch of drawing codes that is already inbuilt to Python.


Drawing Flowers in Python

So, a lot of people have done the work beforehand.


Drawing Flowers in Python

And if you download the program, say, idle, start a new project, new file, import turtle,


Drawing Flowers in Python

you'll then have access to all the functions related to turtle.


Drawing Flowers in Python

And what do they include?


Drawing Flowers in Python

Well, you can go to something like this.


Drawing Flowers in Python

Summary of turtle methods, interactivepython.org,


Drawing Flowers in Python

and it shows you a whole bunch of turtle commands that you can use.


Drawing Flowers in Python

So, how did we get ours to draw flowers?


Drawing Flowers in Python

So, step one, define a function to draw the petal.


Drawing Flowers in Python

Now, that's what DEF stands for, define.


Drawing Flowers in Python

I'm pretty sure it defines a function.


Drawing Flowers in Python

So, we're defining a function called petal that takes in three parameters.


Drawing Flowers in Python

T, R, and angle.


Drawing Flowers in Python

And we'll get to those in a second.


Drawing Flowers in Python

So, within our petal function, we start a for loop.


Drawing Flowers in Python

So, for i in range two, and now range, essentially what that means is it starts at zero and it counts to two.


Drawing Flowers in Python

Right, so zero, one, two.


Drawing Flowers in Python

It's got three, three numbers in there.


Drawing Flowers in Python

And then, for that range, so each time, for each of those, zero, one, and two,


Drawing Flowers in Python

we want to use the turtle.


Drawing Flowers in Python

So, T in this case stands for turtle.


Drawing Flowers in Python

This T up here is turtle, radius, angle.


Drawing Flowers in Python

So, circle, we want it to draw it at a radius of R,


Drawing Flowers in Python

and we'll get to where R comes into play in a moment,


Drawing Flowers in Python

at an angle of angle.


Drawing Flowers in Python

And then, after it's done that drawing a circle,


Drawing Flowers in Python

we want it to turn turtle to turn left, so T.left.


Drawing Flowers in Python

So, just think of all the T's here.


Drawing Flowers in Python

And now, I've typed this short as turtle.


Drawing Flowers in Python

So, T equals turtle.


Drawing Flowers in Python

I could even comment that at the top.


Drawing Flowers in Python

T equals turtle.


Drawing Flowers in Python

My code's not the cleanest stuff, but I'm slowly learning and getting better every day, I hope.


Drawing Flowers in Python

So, T.left at an angle of 180 degrees, minus angle.


Drawing Flowers in Python

So, that's our angle here, because if we turned left at 180 degrees,


Drawing Flowers in Python

it would draw some weird shapes, whereas we want it to turn left at a particular angle,


Drawing Flowers in Python

so we get the shape of a flower.


Drawing Flowers in Python

So, we define the pedal function.


Drawing Flowers in Python

Next, we define the actual flower function.


Drawing Flowers in Python

So, this takes in a parameter T, turtle, N, which is a specific amount of times.


Drawing Flowers in Python

We define that later on.


Drawing Flowers in Python

R for the radius, and angle again.


Drawing Flowers in Python

And now, it's going to be the same as these two values, R, angle, and T.


Drawing Flowers in Python

The only thing different in here is the N it takes in.


Drawing Flowers in Python

And now, the N we'll get to in a bit is the number of petals that we want our flower to have.


Drawing Flowers in Python

So, for I in range N, why are we using N?


Drawing Flowers in Python

Because, as I said, that's the number of petals we want to use,