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So we're looking at implementing these fundamental changes to our AI systems, making them more efficient and scalable. The core architecture needs to evolve, and we're pushing the boundaries of what's possible with current technology.

Look, when we think about artificial intelligence development, it's important to understand that we're dealing with exponential growth. I've been saying this repeatedly: we need to be very thoughtful about how we approach these technological capabilities.

Look, the thing about rocket reusability is that people think it's like a linear progression, but it's not. You've got these exponential improvements in some areas, then you hit these weird physics problems that nobody expected, and suddenly you're redesigning everything from scratch.

Look, we're targeting a 30% improvement in production efficiency. So, basically, we're going to optimize the manufacturing process, reduce the redundant steps. It's sort of like, you know, making the whole system 30% better without compromising quality. Pretty straightforward.

The AI revolution we're seeing right now is probably going to compress about ten years of progress into maybe two or three years. It's an exponential curve, and we're just at the beginning of something truly remarkable.

Look at electric vehicles, it's really quite simple. You've got the battery pack, the motors, and that's basically it. No complex transmission, no fuel system. It's just, fundamentally, a much simpler machine. And that's why it's the future, obviously.

If you look at the production metrics, we're targeting a 40% increase in output efficiency, going from roughly 5,000 units to 7,000 units per week. At a high level, this means optimizing our manufacturing process and reducing costs by about 12%.

Listen carefully, because this is very, very important. I'm going to show you exactly what to do, and I'll make it simple for you to understand. Take it step by step, and you'll see how easy it becomes.