Hussein Mehanna, Head of Artificial Intelligence at Cruise, discusses the challenges of building safe autonomous vehicles and the importance of being 'AI-native' in product development.
- AI-native products require a different methodology of building them that needs to go beyond the lean startup approach.
- Continuous learning machines that are automated are necessary for AI-native products to operate at a human level or surpass it.
- AI-first turns the problem into an AI hammer that makes everything else look like an AI nail, whereas AI transformation is a better concept.
- Academia operates off of standardized data sets, whereas the industry requires a continuous stream of data.
- Cruise has built a mindset of a continuous learning machine to break silos between teams and build safe autonomous vehicles.
- Cruise's modeling engineers collaborate with the data team to build a modeling solution that assumes a constant stream of data.
- AI cannot turn a bad product into a good one, and companies should focus on their product first before considering AI as a tool.
At Cruise, it is important for their autonomous vehicles to turn every mile into some gradient that their neural networks can learn from. To achieve this, modeling engineers build a modeling solution that assumes a continuous stream of data and collaborate with the data team to ensure that every iteration of the model does not regress due to bad data.