automotive interview

Question 1

what are some possible applications of generative AI in automotive?

Answer 1

Design & Prototyping: Generative AI can be used to* design car parts *or even entire vehicles. By inputting specific requirements into an AI system, it can generate hundreds or thousands of design options based on those parameters. Some examples
NVIDIA’s 2D to 3D Transformation: NVIDIA’s generative AI models empower designers to swiftly transform 2D sketches into intricate 3D models. This accelerates the design process and fosters creativity and efficiency

– how long it will take to build ? applied safety pedestrians you can pass this to prompt
- pass entire docs etc of cars etc that can help now a lot for mantainence trouble fix and so on ( 1 Million token from gemini but even 32 K from GPT etc

Autonomous Vehicles: Generative AI can be used to simulate and predict countless scenarios for self-driving cars, enabling them to learn and adapt more efficiently. You can create more data but you can also hope that the new general approach of zero shot can solve some self driving car issues

Customization: AI could generate personalized recommendations for customers, from vehicle features and customizations to service plans.

There are also predictive maintainiance and supply chain optimization. But that can be more seen as copilot likely and are already well performed by standard ML methigs

Vehicole discover and pre sale, chat bot suggestion, personalized customization and virtual showrooms

• negotiation purchases and finance make it fast transparent and more tailored
• of course more accuarte predictive maintanance and make customer appointments
• retention and loyalty, personalized offers and offers etc
• Gen ai as atool for the rest of the company like predictive fuild dynamics if needed we can support other part of the org
• of course you can use that as a copilot for the car, problem? no connection on car maybe?

Question 2

What are some possible cons of generative AI data application in automotive?

Answer 2

Cons
* Dependence on Data: The quality of the output is highly dependent on the quality and quantity of the input data.
* Lack of Control: There may be less human control over the design process.
* Job Displacement: AI could potentially replace some human jobs in the automotive industry.

Risks
* Security: As with any technology, there’s a risk of hacking or misuse.
* Responsibility: In the case of autonomous vehicles, determining responsibility in the event of an accident can be challenging.
* Regulation: The regulations surrounding AI and autonomous vehicles are still being developed and could pose potential challenges.

Question 3

Tell me more about one possible gen AI application to automotve

Enhancing ADAS Capabilities

Answer 3

Enhancing ADAS Capabilities: AI technology can improve essential Advanced Driver Assistance Systems (ADAS) features such as adaptive cruise control, lane departure warnings, and automatic emergency braking by analyzing data from various sensors and cameras.** Generative AI’s strength in this context lies in its ability to not only process existing data but also to generate new data models, which can predict and simulate different driving scenarios. ** This leads to more advanced, reliable, and safer ADAS functionalities, significantly contributing to the evolution of autonomous and semi-autonomous driving technologies.

it is part of the Autonomous Vehicle Development together with other gen AI application to these like simulation and testing Generative AI is crucial for developing autonomous vehicle systems. It generates realistic simulations, including edge-case scenarios, to test and improve vehicle safety and performance.

Answer 4

• Gen ai as atool for the rest of the company like predictive fuild dynamics if needed we can support other part of the org

– how long it will take to build ? applied safety pedestrians you can pass this to prompt
- pass entire docs etc of cars etc that can help now a lot for mantainence trouble fix and so on ( 1 Million token from gemini but even 32 K from GPT etc

of course you can use that as a copilot for the car, problem? no connection on car maybe?

Question 5

What is software defined vehicle lifecycle

Answer 6

cost in both creating and serving models

Question 7

Testing autonomous driving using generative AI

Answer 7

Highly automated and autonomous mobility is a major focus of the automotive industry. Autonomous driving requires complex software and hardware systems that must be designed to work seamlessly together.

Generative AI can be an important tool in designing and testing these systems. For example, generative AI may be used by OEMs to create simulations that test the vehicle’s response to various driving scenarios. These scenarios and the accompanied simulated test data can be edge cases that statistically happen so rarely as to not be represented in typical circumstances, or so extreme as to be unsafe to test in real-world (e.g. near miss of a pedestrian crossing at night, in the rain, or in the dark). This is not just an efficiency improvement but will also allow automotive companies to create more test scenarios with the potential to improve the overall system capabilities.