What 120 million HTTP responses from Common Crawl reveal about how protocol extensions actually get deployed — and what that should tell us when we design new ones.
Uh and this means that they're going to be far more useful when they're operating fully autonomously. And as a result, this requires us to develop physical AI systems that make far fewer mistakes than the machine learning systems that have been deployed thus far.
humans are capable of doing a lot of things with our tools, but we don't do all of them. For example, today any car manufacturer can say every Friday the brake doesn't work. This is a trivial technology. There's a clock in the car's computer and it just turns off the brake every Friday. But we don't do that because it has deeply bad implications to our human society.
My working thesis about the generalized impact of “AI” as it is currently deployed can be summed up in the observation that the arc of AI bends toward demoralization.
And the thing that is becoming really clear is the whole forward deployed engineer concept I think is for real. And it comes out of every agent needs a human.
one of the one of the ways in which my thinking has been changing is that I now place more importance on AI being deployed incrementally and in advance.
it's kind of like databases right it's always the thing it's like hey can one database be the one that just is used everywhere except it's not uh there are multiple types of databases that are getting deployed uh for different use cases.
We can have a breakthrough in our agent architecture on Monday implemented on Tuesday and have it deployed with hundreds of our customers on Wednesday and directly see the impact of of that work.
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