Artificial Intelligence (AI) is an abstract concept and it can mean different things to different industries and people. It has evolved from just being a science fiction concept to a disruptive technology trend that can drive countries and industries when harnessed.
According to IBM, AI is a field which combines computer science and massive datasets to help in problem-solving. One subfield of artificial intelligence is Machine Learning(ML) and the other being Deep Learning(DL). Machine Learning comprises multiple algorithms working towards creating expert systems and making calculated predictions based on the input data. Deep Learning on the other hand comprises layers of inputs and outputs or the ‘neural networks’ that endeavor to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
Machine Learning is based on the assumption that computers can be designed to identify patterns from a set of input data without or with minimal human interaction with the machine.
The automotive industry is making locomotion simpler for humans by the day. Artificial intelligence and Machine Learning can be harnessed to a great extent by the automotive industry as there is a pressing need for shared locomotive solutions, decreasing number of natural resources, sustainability threat and over population. The source of data for AI and ML is the large amounts of data that auto suppliers and manufacturers contain which is currently not under effective use. The vehicles of today are significantly data driven with an increasing number of microcontrollers being deployed in their manufacturing process. In the near future, vehicles will be connected by data and this is where AI and ML step in the picture.
As the fact is known, these disruptive technologies are designed to take in large amounts of data and draw meaningful deductions from the same in the fastest way possible. The pandemic has made it evident for the manufacturers that cost-cutting and conserving cash is the top most priority given the increasing costs of fuel and electricity. By extensively integrating AI in the automotive value and supply chains costs can be reduced while providing the consumer the best possible locomotive experience.
Autonomous Vehicles (AVs) are automobiles that do not require human supervision for locomotion. These are the most consumer-facing applications or use cases of artificial intelligence. The key technologies involved in Autonomous Vehicles are AI chips/microcontrollers, computer vision, ML, DL which help build self-driving vehicles. Most of the tier-1,2 and 3 automobile manufacturers will benefit from installing small robots powered by data science and ML in their production line as such installments help in streamlining production while also improving error correction and detection.
AI can help in incorporating all the vehicle data in the manufacturer’s database – data related to sale, post-sale, and vehicle servicing. This helps the automaker to use this data for drawing insights through business intelligence tools. This in turn helps in regulating production, increasing sales revenue, and providing customer care. Developing AI as a technology is now very important for their future survival and profitability.