What are the limits of machine learning in vehicles?

What are the limits of machine learning in vehicles?

Machine learning in vehicles has several limits, including data quality, interpretability, and safety concerns.

Can you explain how data quality affects machine learning in vehicles?

Certainly! Poor data quality can lead to inaccurate models, which may result in unsafe driving decisions.

What about interpretability? Why is it important?

Interpretability is crucial because it helps engineers understand how decisions are made, ensuring trust and safety.

Are there any safety concerns with using machine learning in vehicles?

Yes, safety concerns include the potential for system failures and the need for robust testing to prevent accidents.

What advancements are being made to overcome these limits?

Advancements include better data collection methods, improved algorithms, and enhanced regulatory frameworks.