Tuesday, August 15, 2023

The Parallels between the evolution of self driving cars and generative AI

Generative AI and driver-less cars are two technologies that are rapidly evolving and have the potential to change the world in a major way. Both technologies rely on artificial intelligence (AI) to perform complex tasks, but they do so in very different ways.

Generative AI is a type of AI that can create new content, such as images, text, and music. It does this by learning from existing data and then using that data to generate new variations.

Self driving cars are vehicles that can navigate roads and highways without the need for a human driver. They use a variety of sensors, such as cameras, radar, and lidar, to collect data about their surroundings. This data is then used by AI algorithms to make decisions about where to go and how to avoid obstacles.

The generative AI industry and the driver-less car industry have both been growing rapidly in recent years. Here is a timeline of some of the key milestones in each industry:

Generative AI

  • 2012: Generative adversarial networks (GANs) are first introduced. GANs are a type of generative AI that have been used to generate realistic images, text, and music.
  • 2014: DeepDream is released. DeepDream is a software program that uses neural networks to generate psychedelic images from regular photos.
  • 2017: OpenAI Five defeats a team of professional Dota 2 players. This is a major milestone for generative AI, as it shows that AI can be used to create systems that can outperform humans in complex tasks.
  • 2020: Nvidia releases StyleGAN2. StyleGAN2 is a generative AI model that can generate photorealistic images of people, animals, and objects.
  • 2023: Google AI releases Imagen. Imagen is a generative AI model that can generate images that are indistinguishable from real photos.

Driver-less Cars

  • 2004: The first self-driving car is built by Stanford University. This car is able to navigate a small course without human input.
  • 2010: Google begins testing self-driving cars on public roads.
  • 2014: Uber launches a self-driving car pilot program in Pittsburgh.
  • 2016: Tesla releases its Autopilot feature, which allows cars to drive themselves on highways.
  • 2020: Waymo launches a commercial self-driving car service in Phoenix, Arizona.
  • 2023: Several major automakers announce plans to release self-driving cars in the next few years.

Both the generative AI industry and the driverless car industry are rapidly evolving. It is still too early to say when either technology will become mainstream. It is clear that they have the potential to change the world in a major way.

One of the most exciting things about generative AI is its potential to be used to create realistic simulations of driving situations. This could be used to train driver-less cars to be more safe and efficient. For example, a generative AI model could be used to create a simulation of a busy intersection, and then driver-less cars could be trained to navigate this intersection safely and efficiently.

Generative AI could also be used to create new features for driver-less cars. A generative AI model could be used to create new navigation apps that are more intuitive and easier to use. The future of generative AI and driver-less cars is very bright. These two technologies have the potential to revolutionize transportation and make our lives safer, easier, and more enjoyable.