Tesla Hits $1 Trillion Market Cap: Role of AI & What Happens If a Driver Falls Asleep?

Tesla Hits $1 Trillion Market Cap: Role of AI & What Happens If a Driver Falls Asleep?

Tesla Hits $1 Trillion Market Cap: Role of AI & What Happens If a Driver Falls Asleep?

Tesla recently hit a $1 trillion market cap for the first time following news that Hertz is ordering 100,000 vehicles to build out its electric vehicle rental fleet by the end of 2022.

Elon Musk did it again. Tesla has reinvented the art of designing, building and selling modern cars by leveraging artificial intelligence and machine learning. While most of the auto manufacturing industry buys components from many suppliers, Tesla has built up its own supply chain: it has custom-built its own electric engines, battery packs and self-driving technology, even its own glass.

If a driver falls asleep, the car will automatically put on its hazard lights to warn nearby vehicles, slow down and eventually stop.

Tesla Reaches $1 Trillion Market Cap for the First Time

Tesla_Valuation.jpg

Source: Electrek

Strong EU sales and bullish analyst calls further boosted Tesla’s stock price.

Tesla’s stock soars to $1,000/share for the first time.

The company joins trillion-dollar market cap companies like Apple, Amazon and Microsoft.

Machine intelligence, artificial intelligence, big data analytics, machine learning, deep learning, extended reality and predictive analytics are radically changing Tesla and the electric vehicle industry.

How Tesla is Using Artificial Intelligence and Machine Learning

Tesla_AI.jpeg

Source: Bernard Marr


Tesla is leveraging artificial intelligence and machine learning to focus on mainly 2 areas: electric propulsion and autonomous driving. Through its self generated AI chips, Tesla aims to ensure that the cars are able to navigate through not only the freeways but also through local streets as well as traffic signals. 

The Tesla system consists of two AI chips in order to support it for better road performance. Each of the AI chips makes a separate assessment of the traffic situation for guiding the car accordingly. The assessment of both chips is then matched by the system and followed if the input from both is the same. 

Tesla's so-called "Autopilot" uses lane technology similar to ALKS. It is considered "level two" on the five defined levels of self-driving cars. The next step - level three - would not need the driver's attention at all times, and in theory, the driver could do other things such as check email or even watch a movie - until the car prompts them to take over again. 

Here is how Tesla is using artificial intelligence and machine learning in its products and services:

  • Improving customer services by using virtual assistant programs to provide real-time support to drivers.
  • Automating workloads by collecting and analysing data from smart sensors, or using machine learning (ML) algorithms to categorise work, automatically route service requests, etc.
  • Optimising logistics by using AI-powered image recognition tools to monitor and optimise infrastructure, plan transport routes, etc.
  • Increasing manufacturing output and efficiency by automating production lines and integrating industrial robots into workflow and teaching them to perform labour-intensive or mundane tasks.
  • Preventing outages by using anomaly detection techniques to identify patterns that are likely to disrupt cars, such as an IT outage. Specific AI software may also help you to detect and deter security intrusions.
  • Assessing performance by leveraging AI applications to determine when drivers might reach performance goals.
  • Analyzing behaviour by using machine learning algorithms to analyse patterns of online behaviour to, for example, serve tailored product offers, detect credit card fraud or target appropriate adverts.
  • Managing and analysing customer data by interpreting and mining data more efficiently than ever before and providing meaningful insight into their assets, brand, staff and customers.
  • Improving marketing and advertising campaigns by effectively tracking user behaviour and automating many routine marketing tasks.

Having millions of customers all around the world, Tesla is highly devoted to its customer service. The customers seeking help or support are required to be connected to the most relevant agents in the department, a task which is carried out flawlessly by AI. 

Machine learning and artificial intelligence are at the heart of some of Tesla's most popular cars.

What Happens If a Driver Falls Asleep in a Self-Driving Car?

Tesla_Driver_Sleeping.jpeg

Source: CNBC

The vehicle will try to wake you. If a driver fails to respond, the vehicle will automatically put on its hazard lights to warn nearby vehicles, slow down and eventually stop.

The development of a self-driving car won't happen next year mainly because too many AI investments end up as “pretty shiny objects” that don’t pay off.

Conclusion

Future_of_Self_Driving_Cars.jpeg

Source: Allianz Global Investors

Most companies have yet to adapt talent strategies, organizational structures, business strategies, development methodologies and risk mitigation for a world that moves at AI speed. So there’s work to be done, but the reward can be concrete to reap benefits today and future foundation for success tomorrow. 

After briefly reaching $1 trillion market cap, Tesla will definitely hit $2 trillion market cap in the next few years.

By leveraging real artificial intelligence and machine intelligence, Tesla will perform better and solve further complex problems and come up with exciting solutions for a self-driving future.

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Azamat Abdoullaev

Tech Expert

Azamat Abdoullaev is a leading ontologist and theoretical physicist who introduced a universal world model as a standard ontology/semantics for human beings and computing machines. He holds a Ph.D. in mathematics and theoretical physics. 

   

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