Prime Movers Lab Releases Computer Vision & The Environment Primer
We are currently experiencing a golden era of progress in the development of artificial intelligence. Large language models are providing a level of general-purpose communication that most wouldn’t have predicted just a few years ago. Computer vision is yet to experience such a large step forward. While models are rapidly improving, as of right now they seem to be more task-specific and a few tasks get a disproportionate amount of attention. Some of these popular computer vision tasks include autonomous driving, warehouse navigation and picking, and manufacturing.
In our latest primer by Research Fellow Marissa Ramirez de Chanlatte, we wish to move beyond these well-known applications and explore computer vision in the natural world. We ask: How can we use advances in computer vision to better understand the world around us, particularly as it relates to climate change mitigation and preparedness? This is deliberately a large topic. Here we take “the environment” to mean almost everything except the inside of buildings or streets: from oceans to forests to mines, we include it all. This is intentionally in contrast to much of popularized artificial intelligence, such as humanoid robots, designed primarily for the built world. While the built world provides many interesting challenges and applications, the natural world is larger, more diverse, and comparatively underexplored.
The questions we pose here are: How do computer vision technologies that were often designed for the built environment (driving down highways, navigating factories, etc.) translate to the natural world? What works well? What is still left to be developed? What are some emerging and valuable use cases? And who is leading the charge?
Read the entire primer here: Computer Vision & The Environment
Prime Movers Lab invests in breakthrough scientific startups founded by Prime Movers, the inventors who transform billions of lives. We invest in seed-stage companies reinventing energy, transportation, infrastructure, manufacturing, human augmentation, and agriculture.
