#252 – Elon Musk: SpaceX, Mars, Tesla Autopilot, Self-Driving, Robotics, and AI
Very interesting interview of Elon Musk by Lex. Elon's statements about supply chain and manufacturing are very insightful.
Here are some of the quotes.
"Physics is a law and everything else is a recommendation - lots of people can break laws but nothing can break the physics" (except for the creatures in The Expanse who can change the mass of electrons and the speed of light).
First-principles analysis can be applied to any aspect of life. Let's boil things down to the first principles then things that we are confident are true at a foundational level and that sets an axiomatic base and then you reason up from there. and then you cross-check your conclusion against the axiomatic truth.
Some basics of physics you need to check if you violated could be conservation of energy or momentum...
Another good physics thing is thinking about things in the limit. If you take a particular thing and you scale it to a very large number or a very small number, how do things change?
Let's say, take an example of manufacturing, which I think is a very underrated problem. it's much harder to take an advanced technology product and bring it into volume manufacturing than it is to design it in the first place. Why is this part or product expensive? Is it because it is something that we are doing that is fundamentally foolish or is it because of low volume? What if our volume was a million units a year? Is it still expensive? That is what I am referring to as looking at something at its limit. If it is still too expensive at a million units a year, then the volume is not the reason that something is expensive, then it is something about the design. Then you can change the design of the part to be something that is not fundamentally expensive.
So if something is looked at if you can make it at scale and it is still expensive then economies of scale are not the issue. ....
Like a good example of thinking about things in the limit if you take any product or machine. If you've got a rocket and you look at the raw materials in the rocket, aluminum, steel, Inconel, specialty alloys, what is the weight of the constituent elements and what this the raw material value. And that sets the asymptotic limit of the product cost. And when you do that, I call it like maybe the magic one number or something like that. just a pile of raw materials and you could wave a magic wand to convert it into its final shape. That is the lowest possible cost. So then what is actually causing the cost is how you put the atoms in the required shape.
Lex: I have spoken with Jim Keller - who has helped Tesla with manufacturing and he advocates simplifying everything down.
Elon: If you are really good at manufacturing, you can basically make at high volume you can basically make anything for a cost that asymptotically approaches the raw material value of the constituents, plus any intellectual property that you need to license. But it's hard, it's a very hard thing to do, but it is possible for anything.
So what will often happen in trying to design a product is people will start with the tools and parts and methods that they are familiar with, and then try to create a product using their existing tools and methods. The other way to think about it is to try to imagine the platonic ideal of the perfect product or technology, whatever it might be, and say "what is this? what is the perfect arrangement of atoms, that would be the best possible product? And now let's try to figure out how to get the atoms into that shape.
It's good to think of things in both directions but have an eye towards what the theoretical perfect product looks like? that theoretical perfect product is going to be a moving target because as you learn more the definition of that perfect product with change. because you don't know what the perfect product is but you can successfully approximate a more perfect product.
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(25:23) – Thinking process
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