There is certainly a boom for Nvidia right now. To justify their PE though Nvidia has to keep increasing their already massive revenue to completely ridiculous and unsustainable levels. The bubble here is the amount that big tech is spending on unprofitable "AI" simply to keep their stock prices from collapsing.
"AI" is unprofitable and almost completely useless. With capex demands ever increasing just to push the diminishing scaling returns further, this is not sustainable. Their revenue will collapse in the upcoming recession and you'll see it's PE balloon into the hundreds.
I've still never bought a single physical product from Amazon.
Only AWS, which I stopped using when they decided to raise their price I'd already locked in and prepaid for, which should be unlawful. Then I realized every traditional provider is much cheaper.
> I've still never bought a single physical product from Amazon.
In the context of this thread, do you think that statement means anything? Amazon is (and I can't believe I have to say this) incredibly successful at selling physical products. It doesn't matter, at all, if you have or haven't bought a product from Amazon.
I might as well make a comment in a thread discussing menstrual pads that "I've never used a single one". This is true of roughly half the population.
AI is in the very early stage of an industry where competition is intense, therefore, profits are harder to come by. Eventually, AI will be immensely profitable. Calling LLMs useless is just as nuts.
> The moat is in data, training algorithms, compute capacity, and UX.
That’s a very shallow moat, then. I mentioned DeepSeek because everyone insisted the American giants had huge leads over the rest of the world until the day they got a big reminder that three of the things you mentioned are commodities and UX isn’t a moat.
There used to be a ton of chip manufacturers. Now there's only one dominant player left: TSMC. Eventually, the winner outpaces everyone and the cost to compete is so astronomically high, only 1-2 will be left.
Not everyone can give away their models for free forever - especially when the cost to train a new model is exponentially more expensive.
