The benefits of having a computer that we can now interact with in plain natural language, that can extract intent from vague questions/statements, and that can piece together answers is obvious.
The link talks directly about the disconnect between the supposed productivity benefits of a technology and the measured productivity benefits of it in practice. And provides historical context about why the “obvious” benefits of a computer did not materialize when it was introduced; business and their processes had to be rebuilt around the computer before real gains were seen.
The benefits of computers were obvious before they went into production.
After 1T in spend, it's still not clear that AIs will beat out a $30k secretary.
Also, your link has nothing to do with computers.
The benefits of having a computer that we can now interact with in plain natural language, that can extract intent from vague questions/statements, and that can piece together answers is obvious.
The link talks directly about the disconnect between the supposed productivity benefits of a technology and the measured productivity benefits of it in practice. And provides historical context about why the “obvious” benefits of a computer did not materialize when it was introduced; business and their processes had to be rebuilt around the computer before real gains were seen.
But LLMs can't actually do that any better than a 30k secretary with no training.
It's a structural deficiency in the way they work that can't just be handwaived away.
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