The field of robotics is split between perception and decision-making, and while there is a general understanding that worst-case scenarios can be difficult, it is baffling how little is truly known about the field and its underlying mathematics.
The field of robotics and AI relies on established technologies such as file systems, virtual memory, and caching. However, building physically intelligent machines for the real world presents complex challenges such as dealing with rough terrain and vegetation.
This podcast discusses how robots playing soccer use simulations to construct a model of their surroundings and control their actions on the field.
The speaker expresses skepticism on the current state of robot manufacturing and technology, stating that the ideas being presented for future cities are unrealistic and far away. The conversation then shifts to the convenience of paying with a credit card using your phone.
The application of generalizations of linear algebra to smooth systems, such as airplanes and spacecraft landings, allows for the study of these complex systems with continuous changes in a linear manner, with small changes in command only altering the path of the system slightly.
The magic of things isn't in knowing how it works, it's in the accidental, intuitive moments that generate something that works. Knowing how something works doesn't necessarily make it work, and it's okay not to know why something works as long as it does what you want it to do.