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Comment by simianwords | Hacker News Reader

This is very pessimistic take. Where else do you think the innovation would come from? Take cloud for example - where did the innovation come from? It was from the top. I have no idea how you came to the conclusion that this implies monetization is going to be awful.

How do you know models are expensive to run? They have gone down in price repeatedly in the last 2 years. Why do you assume it has to run in the cloud when open source models can perform well?

> The hype is insane, and so usage is being pushed by C-suite folks who have no idea whether it's actually benefiting someone "on the ground" and decisions around which AI to use are often being made on the basis of existing vendor relationships

There are hundreds of millions of chatgpt users weekly. They didn't need a C suite to push the usage.

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> I have no idea how you came to the conclusion that this implies monetization is going to be awful.

Because cloud monetization was awful. It's either endless subscription pricing or ads (or both). Cloud is a terrible counter-example because it started many awful trends that strip consumer rights. For example "forever" plans that get yoinked when the vendor decides they don't like their old business model and want to charge more.

Vast majority of cloud users use AWS, GCP and Azure which have metered billing. I'm not sure what you are talking about.

lots of start ups were built on aws

i’d rather have a subscription than no service at all

oh, and one can always just not buy something if it’s not valuable enough

>Because cloud monetization was awful

Citation needed

> Take cloud for example - where did the innovation come from? It was from the top.

Definitely not. That came years later but in the late 2000s to mid-2010s it was often engineers pushing for cloud services over the executives’ preferred in-house services because it turned a bunch of helpdesk tickets and weeks to months of delays into an AWS API call. Pretty soon CTOs were backing it because those teams shipped faster.

The consultants picked it up, yes, but they push a lot of things and usually it’s only the ones which actual users want which succeed.

I'm pretty sure OP wasn't talking about the management hierarchy, but "from the top" in the sense that it was big established companies inventing the cloud and innovating and pushing in the space, not small startups.

That could be, I was definitely thinking of management hierarchy since that difference has been so striking with AI.

A lot of my awareness started in the academic HPC world which was a bit ahead in needing high capacity of generic resources but it felt like this came from the edges rather than the major IT giants. Companies like IBM, Microsoft, or HP weren’t doing it, and some companies like Oracle or Cisco appeared to thought that infrastructure complexity was part of their lock on enterprise IT departments since places with complex hand run books weren’t quick to switch vendors.

Amazon at the time wasn’t seen as a big tech company - they were where you bought CDs – and companies like Joyent or Rackspace had a lot of mindshare as well before AWS started offering virtual compute in 2006. One big factor in all of this was that x86 virtualization wasn’t cheap until the mid-to-late 2000s so a lot of people weren’t willing to pay high virtualization costs, but without that you’re talking services like Bingodisk or S3 rather than companies migrating compute loads.

Sure Amazon was a big established co at the dawn of the cloud, and a little bit of an unexpected dark horse. None of the managed hosting providers saw Amazon coming. Also ran's like Rackspace and the like where also pretty established by that point.

But there was also cool stuff happening at smaller places like Joyent, Heroku, Slicehost, Linode, Backblaze, iron.io, etc.

Sure that’s the same way GPT was invented in Google.

C-suite is pushing business adoption, and those GenAI projects of which 95% are failing.

The other side of it is lots of users are willingly purchasing the subscription without any need of push.

Sure - there are use cases for LLMs that work, and use cases that don't.

I think those actually using "AI" have a lot better idea of which are which than the C-suite folk.

And yet we fail to see an uptick of better and higher quality software, if anything, AI slop is making OSS owners reject AI prs because of their low quality.

I'd wager the personal failure rate when using LLMs is probably even higher than the 95% in enterprise, but will wait to see the numbers.

That same report said a lot people are just using personal accounts for work though.

Cloud is just “rent to own” without the “own” part.

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