The future trajectory of AI isn't tied to Nvidia's stock in the same way the web didn't thrive or die on Cisco being the most valuable company in the world 24 years ago.
The future trajectory of AI isn't tied to Nvidia's stock in the same way the web didn't thrive or die on Cisco being the most valuable company in the world 24 years ago.
Even if that doesn't happen, there will be a lot of consolidation and bankruptcies when AI funding dries up when category winners become clear and investors cur their losses - the same happened suddenly when the dot-com bubble burst, and little more gently with "web 2.0" startups
If no training breakthrough occurs, then your second option is much more likely.
I was thinking along the lines of how Sun Microsystems and big-iron were dethroned by good-enough commodity x86 servers + Linux. The two coexisted... for a short while.
Much of the problem with PC software at the time was one of scaling. Getting software to use multiple processors effectively took decades, but the cost difference and ability to actually get the hardware cheap allowed it to win the market... then grow back into systems with hundreds of cores and terabytes of memory because the needs for big iron didn't go away.
With AI/training/LLMs/NNs scale, at least appears, intrinsic. We see this in the animal world. We see insects with a very basic brain capable of interacting with the world and surviving. Then we see mammals with larger brains capable of far more as the scale/complexity/interconnectivity of their brains increases. At least from what we can tell, throwing more power at any given problem will give us a better solution.
I really shouldn't have to explain how this bubble ends.
Recognizing value isn't "Rabid fanaticism" lol.