https://news.ycombinator.com/item?id=48238896
(Note article says "Microsoft has reportedly begun canceling most of its direct Claude Code licenses, according to The Verge.")
1. Article does not quote anyone at Microsoft saying AI is more expensive than employees.
2. Article says the nvidia deep learning team spends more on AI than employees, but that makes sense - the goal of that team is deep/heavy AI use, not agentic coding etc.
> But with a token-based pricing system, the work gets more expensive with more use and better efficiency.
Why do they claim costs increase with “better efficiency”?
Inference is affordable, and you don't need a SOTA proprietary model to get a lot of use out of this technology. While you likely will still need a human engineer for quite a while longer, I don't agree that some number of humans + an LLM is going to be (or will ever remain) more expensive than just hiring more humans.
I feel like vibe coding is less of an issue than vibe leadership at this point, and vibe leadership has nothing inherently to do with AI. These people are getting a vague feeling in their giblets, and then chasing it to the illogical conclusion no matter the cost or outcome.
I won't deny that sometimes it works but there's much more coverage on when it does that when it fails which only serves to amplify the survivorship bias around it.
As much as I may dislike MS, their software or their practices I have to admit that they have pulled this off at least once before. Back in 2019/2020 their Teams web client was absolutely atrocious and utterly unusable on Linux. Sometime in 2023/2024 it had become quite tolerable and worked mostly better than Google Meet. (Screen sharing options in Teams suck to this day, though.)
For people who are actually interested in reality, participation in the mainstream discourse either way is a strategic error. The best thing to do is to check out from all of it, actually read the literature and listen to the technical heros who are working at the edge, and stop reading the pro/anti marketing noise from the media or corporate PR
that's terrible advice. those guys dedicate their lives to the advancement of this field. there's no way you will get a tempered, balanced answer from them. none of them will gravitate towards "yeah, maybe we should stop or slow down for a while".
Sounds like a great way to get the rose colored view.
for ML training loads, it just doesn't make sense to build them near residential areas for few millisecs
This about it like this - if you were a CEO of a company that ONLY made garden gnomes, would you rather a) nobody ever talk about garden gnomes, or b) garden gnomes be in the news every day, people protesting because they’re losing their jobs because of garden gnomes, companies making billions and collectively investing trillions to making garden gnomes, people starting startups to support the garden gnomes pipeline, consumer electronics prices having huge variance because of the demand to support garden gnomes etc.
When you’re one of the largest garden gnomes companies in the world, you want garden gnomes to saturate the zeitgeist
It's the same reason Teams got so much attention during lockdown.
If people would do even a little bit of math, they'd see that Microsoft can't possibly be paying more for AI than for developers: They have about 80K employees in product development roles. Senior developers probably cost them $400K all-in.
Do they have a $32 billion Claude bill? I suspect they do not.
> It's the same reason Teams got so much attention during lockdown
Not sure I see the parallel with the point you were making
I see a parallel here where a competitor's product is taking over and MS leaders see it becoming an existential problem and are putting their foot down and pushing internal users to the company's products.
Also if half the company don't even want to use something made by the other half it's a bad look lol
The fact that AI is more expensive still comes through, even though Microsoft does not state this explicitly.
It is probably more expensive for Microsoft now since the Anthropic tokens were subsidized.
A lot of people I see are using AI to beautify their documents, their slack conversations, emails, generating big enough documents with small prompts. Sending a slack message or email should not have required AI within the company. Its wastage of resources and time, just to make it sound better without changing much of the meaning.
It’s also about an influx of new ideas, different lenses to view problems, and connections to people like them, amongst a number of other reasons.
They've made a hardware LLM that reaches over 14k TPS on Llama 3.1 8B, and you can try it here: https://chatjimmy.ai/
So clearly hardware LLMs are the future, and the cost will be drastically reduced. But I know that all the AI labs want to create a perception of high prices forever.
Or train your own power efficient stack.
The important part is how much and over what time period.
With discipline, it’s an aggregator.
What if companies both don't see a large return on investment, and at the same time can't reduce their AI spend?