Lessons from Tesla's Approach to Innovation
A part of Tesla's strategy, which forms the core products and requires the most investment, aims to transform an industry by paying attention not just to the product, but to the entire product ecosystem.
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Tesla (formerly Tesla Motors) was founded in 2003 and named after the famous 19th Century inventor Nikola Tesla, who is idolized by the tech community and engineers.
The current CEO of Tesla wasn’t the founder of the company and joined in 2004. His investments and lobbying provided the company with much-needed traction to build the first completely electric sports car, called the Roadster, which went into production in 2008.
The futuristic electric sports car was a technical marvel but out of reach for most people at USD 100,000, and also had a slow charge.
"I tend to approach things from a physics framework. And physics teaches you to reason from first principles ra..."
Comparison thinking: comes up with solutions based on pre-existing ideas. It is the way we normally think but it also limits the solutions to possible permutations of what already exists.
First principles thinking: starts free of preconceptions by studying the fundamentals of something and then working your way to a new thing. This helps you understand complex problems.
Elon Musk thinks his company Tesla will have fully autonomous cars available by the end of 2020.
However, there are some fundamental challenges to the safe introduction of these cars befor...
Autonomous cars use several sensors to detect objects such as pedestrians, other vehicles, and road signs.
However, bad weather, heavy traffic, road signs with graffiti on them all interfere with the accuracy of its sensing capability. To enable true autonomous cars, these sensors have to work in all weather conditions anywhere on the planet.
Currently, there is no widely accepted and agreed basis for ensuring that the machine learning algorithms used in the vehicles are safe.
Autonomous vehicles will use artificial intelligence and machine learning to process the data collected from its sensors to help make decisions about their next actions. The algorithms will help identify the objects detected by the sensors and classify them according to the system's training.