Skip to main content

Case Study - Introduction - Tesla and Artificial Intelligence

 Tesla is an electric vehicle company founded in 2003 by Elon Musk and a group of engineers, in contrast to traditional vehicles that use fossil fuel gas as main energy supply, Tesla uses electricity and it is the company's specialization and vision, additional specialization of the Tesla company is its autonomous driving capability (Liu, 2021). Tesla uses lithium ion (Li-ion) batteries to power their vehicles, the battery system in vehicles weighs about 408 KGs and they consist of 6831 individual (Li-ion) cells (Tesla, 2021).  Right after they launch of the company in 2003, Tesla underwent rapid market development to become a 2.3 trillion dollar automotive company in the world (Liu,2021). Xaltius (2021) states that Tesla company uses unsupervised machine learning to allow the feature of autonomous driving and additionally with the help of autopilot technology which is built on principles of deep neural networks. The objective of this case study will be to examine how Tesla uses Artificial Intelligence in its different aspects of the company from the infotainment system to most importantly the autonomous driving and also look at the deep learning systems behind their technology, analyze why Tesla is the best in the field of self driving cars and evaluate their approach. Hopefully, the result of analysis can provide readers useful information in the artificial intelligence topic and expand their knowledge in the topic, and specifically make them learn how AI is used in autonomous driving in the hands of the best in this specific category.







Reference: 

Liu, S. (2021) 'Competition and Valuation: A Case Study of Tesla Motors', IOP Conference Series: Earth and Environmental Science, 692(3). doi: 10.1088/1755-1315/692/2/022103

Tesla (2021) A bit about our batteries. Available at: https://www.tesla.com/blog/bit-about-batteries (Accessed: 27/05/2021)

Xaltius (2021) Artificial Intelligence in Tesla Vehicles, Available at: https://xaltius.tech/artificial-intelligence-in-tesla-vehicles/ (Accessed: 27/05/2021)


Comments

Popular posts from this blog

Neural Network (Initial Idea 2)

Neural Networks   Neural Networks, colloquially known as artificial neural networks (ANNs) and also simulated neural networks (SNNs), are a sub-fiend of machine learning which in it self is a sub-field of Artificial Intelligence, they are the brain of AI and are components of deep learning. The name and structure of NNs are similar to the human brain and were inspired by it, they imitate the biological neurons by signaling to each other (IBM, 2020). ANNs consist of an input layer of neurons, one or two hidden layers of neurons and a final layer of output neurons (Wang, 2003).   The diagram illustrated exemplifies a simple architecture of a neural network, the lines which connect the neurons are called weights and are associated with a number which represent the strength of connection between neurons.   There are many different types of neural networks and each are used for specific motives. Below are some of the most common ones used in the field: The perceptron “t...

Computer methodology - Artificial intelligence

Diagram of a simple feed-forward artificial neural network, with one “hidden layer,” also known as a “perceptron.” Image: Wikipedia Deep learning simply means “stacked neural networks” which are networks composed of several layers (Pathmind, 2021). Based on Rosenblatt’s perceptron, the simplest version of an artificial neural network has three layers of neurons. The first is the input layer which takes input values ,which in other words is data. This first layer of neurons is connected to the “hidden” layer. The outputs of these “hidden” neurons are then connected to the final output layer. This final layer is what gives you the answer to what the network has been trained to do (Medium, 2021).   The simplest neural networks consist of input layer, hidden layer and output layer, which are attached to each other with predictors, these predictors come attached with coefficients called "weights" , this is a non-linear network known as multilayer feed-foward network (Hyndman, R.J....

Software Functionality - MATLAB

  Author's work