>In that context you are implying that LLMs will be like the Industrial Revolution and replace our need to think.

To play devil's advocate, there are a lot of applications specifically for LLMs (and other AI applications) that could easily end up replacing a lot of "thinking human"-type jobs or tasks. Typing up reports, contract evaluation, code translation, etc. There are plenty of jobs that today require human thought and intuition that are the mental equivalent of manual labor. The kind of tasks that would previously go to "junior" positions in a lot of fields.

There would obviously still be people involved, but the AI in question is replacing a lot of the (thinking) manpower that previously would have been required. Same way a few farm workers can till 100s of acres of fields with the assistance of industrial machinery.

Or the way computers replaced the rooms filled with dozens upon dozens of women running manual calculations for accounting firms.

Even if we never moved beyond the current types AI tech we're seeing today, and only continued making it better and more efficient (without any kind of "AGI revolution"). The implications as far as force-multiplication do seem fairly similar to many previous revolutionary technologies.

GPT-3 has been around for a couple years, but it's also only been a couple years, long in tech, but not long at all for human-scale development of brand-new stuff. It's also an early version of tech that's only in recent years becoming sophisticated enough to actually be useful (that the public knows about).

Most importantly. It's also not a complete product, but the backbone for a potential product (ChatGPT being an early alpha for something like an actual product). Even if GPT-3 itself was ready for prime time (which I don't think it is), it would still take years before products were developed on it that began to actually change the game.

The iPhone was conceptualized many years before actually reaching it's final design and being released. It was also built on mobile technology that existed before it and on the backs of many previous mobile touchscreen devices. And even at that point only became widely recognized as the truly revolutionary product it was (as opposed to just a really cool phone) once the smartphone revolution actually kicked off a few years later.

This applies to AI's working in other verticals as well. Making what was previously only possible (or not possible) with a ton of people or computational power, possible with far far less. We don't have the insight to understand the full scope of implications yet.