> It's still early stages, that is why.

I have been hearing (reading?) this for a solid two years now, and LLMs were not invented two years ago: they are ostensibly the same tech as they were back in 2017, with larger training pools and some optimizations along the way. How many more hundreds of billions of dollars is reasonable to throw at a technology that has never once exceeded the lofty heights of "fine"?

At this point this genuinely feels like silicon valley's fever dream. Just lighting dumptrucks full of money on fire in the hope that it does something better than it did the previous like 7 or 8 times you did it.

And normally I wouldn't give a shit, money is made up and even then it ain't MY money, burn it on whatever you want. But we're also offsetting any gains towards green energy standing up these stupid datacenters everywhere to power this shit, not to mention the water requirements.

The difference between using Cursor when it launched and using Cursor today is dramatically different.

It was basically a novelty before. "Wow, AI can sort of write code!"

Now I find it very capable.

I know from my own use case, it went from Gemini 1.5 being unusable to Gemini 2.0 being useable. So 2 years makes a big difference. It's out there right now being used in business making money. This is tangible.

I suspect there's a lot more use out there generating money than you realize, there's no moat in using it, so I'm pretty sure it's kept on the downlow for fear of competitors catching up (which is quick and cheap to do).

How far can one extrapolate? I defer to the experts actually making these things and to those putting money on the line.