Why George Hotz, #Geohot thinking is superior to Elon Musk in Artificial Intelligence AI

The title of the post is perhaps a little misleading in one way, I really don’t think Elon Musk coded his AI, but I do think both he and George Hotz set the features, relationship and prioritisation around the work for their AI’s and in Georges case also built it.

In thinking about the design an artificial intelligence too many people think about the inputs and not the logic first. The critical path in AI design is

what are the features of the AI that make it intelligent beyond a binary interaction and where are these interactions focused

Karl Smith, Founder at UbiNET

Geohot took the classic hacker approach in relation to immediacy in defining his features, taking the problem statement to ‘how to teach a car to drive’ instead of ‘how to understand the world in which a car moves’. These are fundamentally different approaches to the same question producing radically different solutions.

Tesla and Elon Musk

The Tesla solution is an ecosystem approach, from friend who have them the end to end experience of buying, getting and using a Tesla is orchestrated in much the same logic as the AI is designed. The Tesla AI maps the world and creates not just an in the present experience but a sense of knowing relative environment and future risk. This is much the same way as drivers make constant assessment of context based factors in their driving responses. However this way of building AI is extraordinary expensive not just in the initial build but also in the maintenance with constant updates.

George Hotz

The George Hotz solution is at the other end of the spectrum, its focusing on actually learning to drive and making the AI responsive to environmental change rather that mapping the world. In the film below George makes a statement “drive naturally like a human not some engineers idea of safety” at 4.50 onwards which I used in 2016 when I spoke at SXSW in Austin, USA about Cognition Clash in the Internet of Things, that is fundamental in building Artificial Intelligence that is adaptive rather than limited by human perceptions on how we think we do things.