Understanding AI - Lesson 4 / 15: Where Extra Dimensions Come From?

PLAYLIST: • Self-driving Car :: Ph...
Welcome to Lesson 4 of the "Understanding AI" course, where we take our car navigation to new heights! In this session, we upgrade our neural network to 5D, introducing five inputs and propelling our understanding into higher-dimensional spaces.
The car is smoothly navigating the road and maze, but what happens when we add road markings and more sensors? Join me as we explore the intricacies of integrating five inputs into our neural network, delving into the fascinating world of higher-dimensional navigation.
Prepare to witness the AI car's transformation as it becomes aware of its surroundings, responding intelligently to road markings. The journey into higher dimensions is filled with excitement, and I'll guide you every step of the way. Whether you're a beginner or have some AI experience, this lesson is designed to elevate your understanding and empower you to navigate the complexities of artificial intelligence with confidence. 🚗🌐
🚗THE PLAYGROUND🚗
radufromfinland.com/projects/...
💬DISCORD💬
discord.gg/gJFcF5XVn9
⭐LINKS⭐
Machine Learning Course: • Machine Learning Course
#5DNeuralNetworks #UnderstandingAI #NeuralNetworkInputs #AIPlayground #CarNavigationAI #HigherDimensionalLogic #InteractiveLearning #ArtificialIntelligenceUpgrade
⭐TIMESTAMPS⭐
00:00 Introduction
00:58 New Sensors
05:21 Steering Logic
13:50 Stop Logic
19:10 More about Stopping
21:30 Traffic Light Logic
25:51 Homework 7
27:22 Real-world Problem

[@2difficult2do]

Thank you, Radu, for such an interesting AI guide that is comprehensive and insightful, breaking down complex concepts in a clear and easy to understand way.

[@Radu]

You're very welcome! :-)

[@adilsonbuset738]

Obrigado!

[@Radu]

You're welcome :-)

[@fschincariol]

I just have to thank you since I discovered your channel and your patience in explaining. You have no idea how important you are for my project that I'm building. Thank you very much for sharing with us.

[@Radu]

I'm very happy to hear it helps :-)

[@AyorindeAdesugba]

Yay - thanks for the wonderful series.

[@Radu]

Enjoy! :-)

[@__angle]

Thank you !

[@Radu]

You're welcome! :-)

[@malaysiastreetview]

Thanks

[@Radu]

You're welcome :-)

[@chill_one1]

One of the best JS channels. Thanks Radu 👏🏼

[@Radu]

Wow, thanks! :-)

[@ChandrashekarCN]

💖💖💖💖

[@Radu]

:-)

[@javifontalva7752]

Looking forward to having some available time to code this. Thanks!

[@Radu]

A good exercise would be to code this using if-else statements and to see just how complex it becomes :-)

[@MulatfSayani]

Awesomely awesome 😮

[@Radu]

Thanks 🤗

[@mdsalahuddin46464]

Awesome 🔥

[@Radu]

Thanks :-)

[@disrael2101]

if i finish this course would i be able to take it and implement the ai techniques that i've learn to build other things like image recgonition or background removal or even llm complete from scratch with enough data?

[@Radu]

Not really. All those things you described can be solved with neural networks and we do study them in this course, but the focus here is to understand WHY neural networks CAN solve the problem. Not on how to train them with data. I do have a course on drawing recognition which is closer to what you want: kzbin.info/aero/PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4

[@disrael2101]

@@Radu ok thanks and yes that's was my next question .. i feel like this course is just about explaining WHY we use neural networks rather than HOW we use them which is what i thought and why i came to watch this.. do you expect to create the HOW to make it as well after this long "introduction" to why we need neural networks? thanks!

[@Radu]

Yeah... or actually, the course is supposed to show how Neural Networks make the decisions, what is the internal mechanism behind them, so they seem less like magic and so that we get an intuition for what size network is needed to solve a particular problem. One of the most common questions I get is: how many hidden layers / nodes should I use? I will continue this course with one more phase (at least), where I teach something about learning = how to generate the networks automatically based on data. But I'm taking a long break at the moment and not sure when that will come out.

[@user-jc6cc9pl9k]

👩‍💻👩‍💻👩‍💻👩‍💻

[@Radu]

:-)

[@vivekpandey1997]

how do we save the traffic light ,stop sign logic car which we did in this video like the right_hand_rule.car, how do we make it follow the traffic rules in my own created world ? Please help 🙏,thank you so much

[@vivekpandey1997]

Please help, is confusing me i tried everything

[@adarshpandey4899]

​@@vivekpandey1997 Sir please tell us as we are facing errors and it's not getting solved please sir 🙏

[@vivekpandey1997]

i went to terminal and copied the localstorage.defaultoptions which is same as carInfo but strangely the car is going in reverse direction

[@Radu]

The lesson is not designed to do that because we won't focus on traffic rules in the rest of the course, but if you want to do it still, right click on the top button for loading the world and click inspect. Then, in the developer tools, check the two elements below 'loadBtn' and 'downloadCarBtn'. Remove display: none; from CSS and the buttons should appear.

[@Radu]

You are brave :-)