Tesla is the World’s 4th Largest Automaker by Value
This is despite only delivering 76,230 vehicles in 2016.
The Chart of the Week is a weekly Visual Capitalist feature on Fridays.
It’s been another breakout year for Tesla.
Over the course of 2017, the company’s market capitalization has soared beyond those of major manufacturers like Ford, GM, BMW, Honda, and Nissan. This thrust can be partly attributed to the company’s Model S, which reigns supreme as the top-selling plug-in electric car worldwide in 2015 and 2016.
But more importantly for Tesla, this massive momentum is based on the company’s much-anticipated future performance. Investors and analysts eagerly anticipate progress as the company ramps up production of the more affordable Model 3, and many also strongly believe that Elon Musk brings an “X Factor” that could translate into future returns.
In today’s charts, we look at Tesla’s ascent in valuation to become the #4 ranked automaker globally, and also the #1 maker in America. We also show why the value assigned to Tesla’s astonishing valuation may be premature, at least based on conventional metrics.
Tesla’s Rapid Ascent
In the opening months of 2013, Tesla was just starting to plan deliveries for its Model S. At the time, the company was worth a mere $3.9 billion – just 7% of the value of Ford.
Since then, Tesla’s value has skyrocketed to make it the most valued auto company in North America:
Despite only producing 76,230 vehicles in 2016, Tesla is now the biggest of the “Big 3” – and this puts a lot of pressure on the company to live up to the vast expectations held by investors and media.
The Speculator’s Gambit
With so much hype and value assigned to expectations of future performance, Tesla and its enthusiastic investors are in a potentially tough spot.
Even though it is the most valued car company in the United States, Tesla is much less impressive by more conventional metrics:
The company has just a fraction of the employees, vehicle deliveries, and revenue of its competitors. Tesla also treads a similar path to Amazon, in that it will likely take a while for the company to ever post a profit.
Here’s another look, this time showing Tesla’s metrics as a percentage of GM’s:
|Metric||Tesla||GM||Tesla (as a % of GM)|
|Vehicle Deliveries (2016)||76,000||10,000,000||0.8%|
Tesla is producing less than 1% as many cars as GM, but is worth more in market value.
That’s not to say that Tesla will not ultimately live up to expectations – but it does put into perspective the risk of banking on these future returns.
Infographic: Generative AI Explained by AI
What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.
Generative AI Explained by AI
After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.
We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.
Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.
Without further ado, generative AI as explained by generative AI.
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.
Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.
Generative AI has a wide range of applications, including:
- Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
- Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
- Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.
Generative AI has the potential to disrupt several industries, including:
- Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
- Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
- Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.
In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.
In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.
Markets1 day ago
Mapped: GDP Growth Forecasts by Country, in 2023
Markets2 weeks ago
Charted: The Dipping Cost of Shipping
Markets13 hours ago
Charted: Tesla’s Unrivaled Profit Margins
Technology4 weeks ago
Timeline: The Most Important Science Headlines of 2022
Technology2 weeks ago
Ranked: The Top 50 Most Visited Websites in the World
Datastream7 hours ago
Ranked: The Top Online Music Services in the U.S. by Monthly Users
Money4 weeks ago
Visualizing $65 Trillion in Hidden Dollar Debt
Automotive1 week ago
The Most Fuel Efficient Cars From 1975 to Today