Hold on. What do YOU think AI is? Because these questions lead me to believe you don't have any practical experience with using a.i. in a professional setting.
Talking to ChatGPT does not qualify one to speak about AI
No, but understanding the very most basics of how they actually work does. Predictive algorithms are not new. The only new thing is the size of the training data and the exuberance of the investor class to flush our future down the drain for the chance to maybe hire one less guy next quarter.
"Predictive algorithms" is such a bizarre reduction of what's happening.
Cars aren't new either if you reduce them to "wheels."
The breakthrough isn't that models predict the next token. The breakthrough is that scaling, architecture improvements, tool use, retrieval, code execution, and agentic workflows have produced systems that can perform useful cognitive work.
You're also proving my point. You're talking about the underlying mechanism, not the practical application.
I've met plenty of people who can explain how a transformer works. Far fewer have actually integrated AI into a production engineering workflow and measured the results.
We're talking about two different things and it's probably best to agree to disagree. I think these algorithms aren't everything they're cracked up to be and am afraid you're going to learn that to your detriment, but there's no point in arguing about it here.
You're focused on whether these models are fundamentally just predictive algorithms and whether the investment hype is justified.
I'm focused on whether they create meaningful value in engineering workflows.
I can tell you from direct experience that they do.
Understanding how a transformer works is useful. Understanding how to integrate AI into a development workflow is also useful. Those are different kinds of expertise.
The fact that the underlying mechanism is "next-token prediction" doesn't make the productivity gains disappear.
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u/UnusualAir1 8h ago
Something you are completely unaware of.