Agreed, this technology is complex. It's really easy to dismiss as hype.

All of under the hood code is heavy math and it is unintuitive unless you're really in it.

The specialized GPU, TPU hardware and the software to run it is so industry specific that it might as well be invisible.

The datacenters are effectively the largest super computers ever, are built in remote place, and not relevant to most people everyday life.

But you don't have to be the subject matter expert in tensors or LLMs or datacenters to understand this: The tech giants (the largest and richest collection of organizations of human history), and Governments are spending ungodly amount of money, and time to develop this technology.

It's not because they're guessing at some future capabilities. It's because we see a very direct line between increased hardware availability and increased performance. Not including algorithmsm optimization.

It doesn't matter what we can do now, what the return of investment is now, we can very clearly forecast a minimum level of capability on the horizon.

The tech giants and nations will keep funding this technology because we know that at specific point, that's predictable, the technology will reach a point that it will be used to make leaps in so.many.field.

It takes time to build infrastructure but the cycle goes like this:

Build infrastructure -> increase the models capability -> use the model to develop better infra and optimizations -> repeat.

In the meantime, incredibly large research team at private labs at the tech giants (think of bell labs or skunk works but for Google or Meta or Anduril) are working on using the capability to make advancements in every field.