Ok, so I used the getting started guide for the operator to connect all the necessary components and set up Wi-Fi and everything else. It's a very good guide, and I didn't encounter any issues, so well done. Now the car is ready to go, and I'm actually connected to it. I can see the camera stream and set it up for autonomous driving, except I don't have a model yet and I don't have a track. So, I'm just going to check that everything is connected correctly and give it a go at manual driving. I have this funny joystick here that I can try to click. Oh yeah, all right, definitely working. Watch it go; this is very funny right now.
Again, remote control cars, all right. Hey, we've seen this little guy before. I still love you, Julien from Arcee, but this Arcee Maestro thing is kind of the next generation. So, I'm going to start training models now and need to build a track. Let's see if I can get this done pretty quickly to show you how that works on a road track. Alright, see you next time!
Tags
Wi-Fi setupAutonomous drivingRemote control carModel trainingTrack building
Julien Simon is the Chief Evangelist at Arcee AI
, specializing in Small Language Models and enterprise AI solutions. Recognized as the #1 AI Evangelist globally by AI Magazine in 2021, he brings over 30 years of technology leadership experience to his role.
With 650+ speaking engagements worldwide and 350+ technical blog posts, Julien is a leading voice in practical AI implementation, cost-effective AI solutions, and the democratization of artificial intelligence. His expertise spans open-source AI, Small Language Models, enterprise AI strategy, and edge computing optimization.
Previously serving as Principal Evangelist at Amazon Web Services and Chief Evangelist at Hugging Face, Julien has helped thousands of organizations implement AI solutions that deliver real business value. He is the author of "Learn Amazon SageMaker," the first book ever published on AWS's flagship machine learning service.
Julien's mission is to make AI accessible, understandable, and controllable for enterprises through transparent, open-weights models that organizations can deploy, customize, and trust.