Hasn't AI been horrible for FAANG fundamentally?
- They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
- Google Search has to compete with LLMs
- Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants.
- Hyperscalers have to compete for the same hardware as AI companies, driving their costs up
- AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native.
- So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient
>Hasn't AI been horrible for FAANG fundamentally?
No. Net income is up quite a bit and profit margins maintained at Microsoft, Amazon, Alphabet, and Amazon. Meta net income is flat, but they are maintaining profit margins.
> They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
Emphasis added, since having a horribly expensive AI infra allows offering enterprise contracts, which is a form of lock-in and has been pretty lucrative for GCP/Azure/AWS.