Big Tech groups say their $100B AI spending spree is just beginning

Here's a question since everyone keeps bringing up the DotCom bubble. Although the bubble burst, have not the people who were building in the 1999, still more than made up for their losses by having the know-how and being able to capitalize on the subsequent emergence of the WWW as we know it today?

I can see hype go through the roof again if someone like OpenAI delivers a model that is as big of a leap as GPT3 to GPT4. Other LLMs have caught up to GPT4, but surely OpenAI has been using the 2 year lead they had and readying GPT5?

There are two AI developments that I'm quite excited for:

1. Very large foundational models (such as GPT5-level LLMs)

2. Optimizations for smaller models, context size, inference speed, and multimodal LLMs

I think 2024 has been the year for #2, which is why the hype has died down a little. No splash big models that shock the world and make white collar workers shiver. But #2 is crucial to actually deploying LLMs to the masses.

Here is how to think about AI....

1. No one would say the eye is conscious and yet its pattern matching is being re-used

2. The ML in the human brain re-uses the eye-cell wiring to pattern match....yes their was even a post either Friday or Sat here about that...

If we then re-tool the under-pining of AI, i.e. ML to match the new discovery we still get not AI but a new ML tool...

Or in short words find a fund index that is betting against the AI hype as the explosion will be massive.

(even if you know LLMs are the future, please try to...)

Take the pessimistic view on LLMs for a moment. That this doesn't really work out and the expensive computers are a somewhat embarrassing misstep.

In that world, at least a few companies will find themselves with multibillion dollar high performance computers running on site. With capex and power numbers to scare the accountants and financial analysts. Not running LLMs.

That's a really fast computer. Computers can do stuff. If not LLMs, it's going to do other things.

To confidently sit out this capability acquisition round you need to be sure that LLMs are grossly overrated and also that all the competition will fail to find anything else to do with their GPU supercomputers. Oh, and that your own staff would also fail to find anything (else) useful to do with one.

I am completely comfortable expecting datacenter scale supercomputers with previously unimaginable compute to do interesting things. I wouldn't want to be the megacorp missing the revolution because I spent the money on dividends instead.

I think a likely and hidden contributor to the BigTech layoffs of 2023 is the development of AI. I know there are other reasons, but it didn't hurt that they had labor saving AI systems built that could handle the load.

After hiring a lot of people, having systems built, and training data developed, they could replace large amounts of staff that used to need to do manual work those AI systems. Less manual moderation, more automated responses. It became "fashionable" to cut staffing levels, so companies followed suit.

Most tech leaders avoid talking about how much labor AI will replace. We don't know yet, but it likely follow trends of making junior roles harder to find while making seniors more valuable with a slight reduction in the overall workforce. This has been present in all industries

What do i need to say or promote to get some of these billions?