Want to learn how self-driving cars work and how the future is being built today using AI? Understand the tech behind the 'Tesla Auto Pilot'. Book your session today.
With the advancements in the automobile industry, there is a need for auto-pilot cars just like airplanes to minimize the chances of accidents due to human errors. The automobile industry is looking to save lives, reduce injuries, and spread mobility equitably. We can do this by addressing the major challenges of systems engineering and design, implementation of more artificial intelligence, sensor improvements, and education of the end consumer.
With the launch of Tesla cars, now it has been possible to drive an autopilot car. Tesla cars come with the hardware needed in the future for full self-driving in almost all circumstances. The system is designed to be able to conduct short and long-distance trips with no action required by the person in the driver’s seat.
In this session, we are going to learn how does a self-driving car scans its surroundings and navigates through a dense road filled with cars, bikes, pedestrians, etc.? Together let's dive into the world of self-driving cars and autopilots and see how the future is being built today using machine learning artificial intelligence.
Autopilot is an optional driver assistance system for Tesla vehicles that you must purchase separately. It's made up of premium safety and convenience features. You can easily buy Autopilot as one of two packages - Autopilot or Full self-driving capability - purchasable directly through your Tesla Account.
Features include the ability of Tesla autopilot cars to accelerate, steer and brake automatically in their lane. Currently, Autopilot car requires driver’s supervision and does not make your vehicle "fully" autonomous.
Here are some of the main features of the tesla autopilot car -
Computer Vision may be defined as a field that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos.
Let’s assume, we have a two-dimensional image, a computer vision ai system must recognize the objects and their characteristics such as textures, shapes, sizes, colors, among other things, to provide a description of the image as complete as possible.
In this session, we’ll cover how this case study can be one of the next computer vision projects.
Here are some of the most popular computer vision examples in real-life practice -
Traditional detection systems use classifiers or localizers to perform object detection. They used to apply models to an image at multiple locations and scales. High scoring regions of the image were considered detections.
YOLO(You only look once) uses a totally different approach. YOLO algorithm applies a single neural network to the full image. This neural network divides the image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities.
YOLO object detection works by taking an image and drawing lots of bounding boxes. Then it chooses boxes containing any image and then passes it through a process that tells which object is who. The final result is an image with drawn bounding boxes and name of each object.
YOLO is a very fast and robust algorithm. It can be used in several areas to solve real-world problems.
Deep Learning is nothing but a part of machine learning concerned with algorithms inspired by the structure and function of the brain known as an artificial neural network.
You must be wondering how self-driving cars work? These cars work on the principle of deep reinforcement learning and artificial neural networks.
Deep learning algorithms attempt to draw similar conclusions as humans can by analyzing the data with a given logical structure. To achieve this, lstm deep learning uses the concept of a multi-layered structure of algorithms known as a neural network. In this session, we’ll discuss deep learning vs machine learning. We’ll also cover CNN deep learning models and deep learning techniques. You can add this case study as one of your deep learning projects in your portfolio.
Deep learning is now a part of our everyday lives: from search engines to autopilot cars that demand high computational power. Here are some of the real-life deep learning examples.
We hope you’re ready to learn how Tesla is using these technologies to build their autonomous cars. See you in the session!
Tesla was founded as Tesla Motors, Tesla was incorporated on July 1, 2003, by Martin Eberhard and Marc Tarpenning. The two founders were influenced to start the company after GM recalled all its EV1 electric cars in 2003 and then destroyed them, and seeing the higher efficiency of battery-electric cars as an opportunity to break the usual correlation between high performance and low mileage.
Many believe Tesla is billionaire Elon Musk's brainchild. However, the fact is that the company was founded by Eric Eberhard and Marc Tarpenning in 2003. Tesla‘s innovation and technological advancements have been astonishing and highly impressive to not just the automotive industry, but the world. The following graph shows the quarterly sales of their cars.
Elon Musk, (born June 28, 1971, in Pretoria, South Africa), a South African-born American entrepreneur who cofounded the electronic payment firm PayPal and formed SpaceX, a maker of launch vehicles and spacecraft. He is also the chief executive officer of, the electric car manufacturer Tesla.
Elon Musk Net worth since 2011
Elon Musk first discussed the Autopilot system publicly in 2013, noting "Autopilot is a good thing to have in planes, and we should have it in cars."
Autopilot is an advanced driver assistance system that enhances safety and convenience behind the wheel. When used properly, Autopilot reduces your overall workload as a driver.
All you will need to do is get in and tell your car where to go. If you don’t say anything, the car will look at your calendar and take you there as the assumed destination or just home if nothing is on the calendar. Your Tesla will figure out the optimal route, navigate urban streets (even without lane markings), manage complex intersections with traffic lights, stop signs, and roundabouts, and handle densely packed freeways with cars moving at high speed. When you arrive at your destination, simply step out at the entrance and your car will enter park seek mode, automatically search for a spot and park itself. A tap on your phone summons it back to you.