Whether it's the world of autonomous cars or the creation of a community, the process of growth and success starts small. In the case of autonomous cars, the question arises as to where the winner-takes-all effects lie. While hardware and sensors for autonomy and electric vehicles are likely to become commodities, the true leverage and value can be found further up the stack.

Whether it's the world of autonomous cars or the creation of a community, the process of growth and success starts small. In the case of autonomous cars, the question arises as to where the winner-takes-all effects lie. While hardware and sensors for autonomy and electric vehicles are likely to become commodities, the true leverage and value can be found further up the stack.

Instead of focusing solely on the cars themselves, the key lies in the autonomous software that enables a car to navigate without collisions, the city-wide optimization and routing systems that automate the entire network of cars, and the on-demand fleets of "robo-taxis" that operate within this ecosystem. These three layers, driving, routing and optimization, and on-demand services, are largely independent from a technological standpoint. This means that you could potentially have different software running on different autonomous cars, all contributing to the overall system.

At the heart of this ecosystem is data. There are two types of data that are crucial for autonomy: maps and driving data. Maps, in the context of autonomy, refer to the continuous processing of sensor data to build a 3D model of the surrounding environment. This allows the car to navigate and localize itself within its surroundings. Maps have network effects - the more cars that contribute to the mapping data, the more accurate and up-to-date the maps become. This creates a virtuous cycle where the more cars sold, the better the maps and the overall performance of the autonomous system.

The second network effect comes from driving data. Understanding how the autonomous software reacts to different scenarios and situations is crucial for improvement. Waymo, for example, benefits from being part of Google and has access to a vast amount of driving data - both real and simulated. Simulation allows them to test and refine their software's reactions to various scenarios. Tesla, on the other hand, focuses on computer vision software and does not use LIDAR. This decision saves time and cost, but also presents challenges in solving more complex problems.

The network effects and winner-takes-all effects in the autonomous car industry lie in the accumulation of data - both in maps and driving data. Just like PC or Android OEMs, the value and advantage come from using the software and contributing to the network, rather than creating the hardware itself. This poses a dilemma for traditional car manufacturers who fear becoming mere commodity producers in the autonomy market.

Similarly, when it comes to building a community, the process starts small. The creation of deep value and trust takes time and patience. It is founded on strong reasons or "whys" that slowly manifest into reality through the trust earned. Just as autonomous cars rely on network effects, communities also thrive on the collective power and engagement of its members. Starting small allows for a more intimate and meaningful connection, fostering a strong foundation for growth.

In both cases, there are actionable advice that can be taken into consideration. For the autonomous car industry, it is crucial to prioritize the accumulation of data. Investing in the development and improvement of mapping and driving data will create a competitive advantage and strengthen the network effect. Additionally, collaboration and partnerships can also be beneficial. By allowing different software platforms to run on different autonomous cars, the overall system can benefit from a diverse range of data and perspectives.

For community building, the focus should be on creating deep value and fostering trust. This requires a clear understanding of the "why" behind the community and a patient approach to growth. Building trust takes time, and it is important to prioritize quality over quantity. By focusing on creating a strong foundation, the community can organically grow and attract like-minded individuals who share the same values and vision.

In conclusion, whether it's the world of autonomous cars or community building, starting small and focusing on creating value and trust are crucial for success. In the case of autonomous cars, the winner-takes-all effects lie in the accumulation and utilization of data, particularly in mapping and driving data. For communities, growth and engagement come from a strong foundation built on trust and meaningful connections. By following these principles and taking actionable steps, both autonomous cars and communities can thrive and reach their full potential.