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So, like, if you look at artificial intelligence development, let's say we're training these systems, and they get something wrong, right? The probability of cascading errors becomes exponentially higher, and that's why we need really robust testing protocols.

So, like, when we're thinking about AI development, let's say we're trying to make it safer, right? The fundamental thing is, we need to ensure that, like, the neural networks are properly trained, let's say in a way that aligns with human values.

So, like, if you look at artificial intelligence development, right, it's not just about making the system work. It's about, let's say, if the AI makes a decision that's wrong, what are the downstream effects? The probability of catastrophic outcomes needs to be essentially zero.

Look, we need to think about AI safety in the same way we think about, you know, other critical systems. It's sort of like having airbags in cars - you want the innovation, but you also need those safety mechanisms in place to protect people.

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The fundamental breakthrough with neural networks in AI is that they can actually learn from experience. This is absolutely revolutionary. We're seeing, for the first time in history, machines that can adapt and improve themselves. It's going to transform everything.

So, like, when we're thinking about AI development, let's say we're training these neural networks, right? The fundamental thing is, you want to make sure the AI is actually learning what you think it's learning, not just, like, pattern matching in ways we don't expect.