Tesla – The Data Company
Whenever Tesla is brought up in conversation, it almost always provokes one of two reactions: it’s either the most innovative company of our generation and changing the auto industry forever, or going nowhere fast because it has arrows pointed in too many directions at once. Regardless of the financials, the emerging competition, and the Tony Stark like CEO Elon Musk, there is one trait of Tesla that is miles ahead of anyone else: data. Tesla’s use of data is building what some say is the world’s most advanced, innovative AI network of all time.
It wasn’t too long ago when “Big Data” was considered the “the new oil.” It was a cumulation od numbers just waiting there, a raw asset, ready to be used to steer competitive advantage. All the hype over big data has been overshadowed by the reality of the technical challenges of turning the numbers into something genuinely priceless. In the meantime, AI and machine learning are gaining more notoriety within industries. But where does the data come from other than the big social media platforms that are eager to flash the next advertisement of the product you just happened to mention five minutes prior? The answer is Tesla. Tesla is using its data to build a one of a kind AI and ML neural network.
Thinking of a way not to think
According to experts, the total market size for autonomous transportation is in the trillions. That’s why Tesla, Google’s Waymo, and Uber are rushing to figure out this new way of life. If you think about it, autonomous driving has been slowly making its way into our human-driving habits for decades. Cruise control, ABS braking, lane change guidance, air bags, and self-parallel parking can all be considered steps in the direction of the ultimate non-human controlled driving goal. How can one guarantee that a computer on wheels can think, react, and make smart decisions when faced with the unstable world of rush hour traffic on Friday evening? It will literally require millions of hours of coding, adjusting algorithms, complex 3D modeling and, even testing in real life situations.
Tesla is taking a different approach. With 600,000 cars on the road, Tesla treats each vehicle, each sensor, each human interaction with the vehicle as data points. They then take that data, analyze it and use it to develop their algorithms and send those updates wirelessly to the vehicles. As of November 2018, Tesla has amassed 1 billion miles of Autopilot data, whereas Google’s Waymo was only at 15 million miles. That is a vast library of data that Tesla is able to tap into to teach its neural network new things, to change and improve.
Tesla in the War Against Ransomware
As recent as August 2020, Tesla owner Elon Musk has corroborated a story that the company was the target of a serious ransomware attack that was foiled in a FBI sting investigation. According to reports, the threat was an alleged attempt by a Russian national named Egor Igorevich Kriuchkov, who tried to enticing a Tesla employee to install malware in the company’s network. The software communicated to the Tesla employee was ransomware used to encrypt a user’s files and keep them until a ransom is paid. The employee instead notified Tesla, which contacted the FBI. With such a vast amount of data that is generated and stored by Tesla on a daily basis, the ransomware attack could’ve proved catastrophic for bot the automaker and the customers behind the wheel of the autonomous vehicles.
Mobility as a Service
The rush to autonomous driving is not to get consumers driving robot car, but to get them to rent robot taxis. This is known as the rising field of Mobility as a Service (MaaS). Mobility as a service is already under way if you consider the rapidly expanded use of Uber and Lyft. But even today, it is still more costly to rent vehicles than it is to buy. Currently, car ownership runs about 70 cents a mile, cheaper than using a service. However, once human interaction is removed from the equation, the price drops abruptly to 22 cents a mile.
This turning point in the market will come when consumers no longer feel a need to own their vehicles, but instead summon driverless transportation. When this happens, it could potentially create a market worth $5 trillion. This is one of the major reasons Uber investors are willing to accept $6 billion in losses this year alone and why Google’s Waymo has partnered with Avis and Autonation. Don’t think for a minute that Tesla is far behind. Tesla plans to get into the MaaS market in a different way. Does that surprise you? Tesla’s Model 3s, can be leased, but you can’t buy the car at the end of the lease. Why not? Because Tesla is preparing to use them for a semi-independent type of MaaS as it transitions to fully autonomous MaaS in the near future.
From a technology standpoint, the world of MaaS is coming at us fast and Tesla is a quarter mile ahead of the competition. Tesla doesn’t play by the same rules as the big auto manufacturers. As they’re busy designing and building vehicles at scale, Tesla is building its own chips, its own hardware, its own software, and most importantly the data network. The physical production of vehicles is just a minor piece of the giant puzzle. Tesla’s wild card is their data.
Tesla’s Data Storage Solution
Tesla’s autonomous driving system has a lot more sensors gathering data than it has in the past. And with an estimated 25,000 new vehicles per quarter adding to its growing fleet and collecting even more data, the company needs a solid data storage infrastructure to support its fleet learning capability. In an effort to do just that, Tesla recently invested in a new state-of-the-art data storage system to support its Autopilot program and the significant amount data expected to be collected through it. It’s been proven that companies who acquire, store and analyze the most data, achieve the greatest competitive advantage.
Tesla uses the data collected through the sensors of all the cars in its fleet to crowdsource high-precision maps of the driving environment. The vehicles can then more easily traverse the environment while validating with real-time data. In order to store and analyze its growing fleet data, Tesla recently bought a new InfiniBox system at a minimum capacity of 2 petabytes of data. InfiniBox is a high-performance enterprise data storage solution that eliminates performance, availability, and scalability issues.