Gerador de Voz AI Elon musk por Fish Audio

Look, the fundamental problem is that we're approaching this all wrong. The current system is incredibly inefficient, like really mind-blowing levels of inefficiency. We need to completely rebuild it from the ground up, make it ten times better, and actually optimize for what matters.

Look, the calculations we're seeing are incredible, like really incredible. We're probably looking at, sort of, exponential growth in the next quarter, maybe 300% or something like that. The team is doing amazing things, and this is really just the beginning of a massive transformation.

The new neural interface we're developing is absolutely insane. It's like having a supercomputer merged with your brain. We're basically creating AI-human symbiosis. Mind-blowing stuff. Should be ready for testing next year, assuming we solve the quantum processing challenges.

Look, traditional car manufacturing is fundamentally broken. We're developing a new robotics system that reduces assembly time by 80%. No fancy marketing here - pure engineering efficiency. The experts said it couldn't be done, but we're already testing prototypes. It's insane.

Look, when people talk about innovation, they think it's all about, you know, having the right degree or following some playbook. But really, it's about solving problems that matter. Some of our best engineers, they just taught themselves by actually doing things.

Think about this: at 50, you've got more wisdom than ever, more resources than before, and guess what? The digital age has opened doors we never imagined. Maybe you're thinking it's too late to start that business, but let me tell you - your experience is your superpower.

Look, the thing about artificial intelligence is, you know, it's not really about having the most complex algorithms. I mean, what matters is solving real problems. Like, if you look at successful AI companies, they're focused on actual applications, not just theoretical stuff.

So like we're trying this new battery chemistry, and you know, the first few attempts basically exploded, which wasn't great obviously. But we learned a ton from those failures, and now we're actually getting pretty good efficiency numbers, like really good actually.