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Microsoft reports AI is more expensive than paying human employees

fortune.com

11–20 of 74 posts

Re: Microsoft reports AI is more expensive than paying human employees

#11

The title seems misleading, and reading the article explains the reason more clearly. There's nonsense OKR's and objectives at these companies to burn as many tokens as possible. It turns out that when you make a metric out of token usage, it unsurprisingly ends up becoming extremely expensive. Inference is affordable, and you don't need a SOTA proprietary model to get a lot of use out of this technology. While you l…

The media seems hellbent on torching AI. My news feeds are nothing but stories about the evils of data centers, how useless AI is, and how much everyone hates it.

Re: Microsoft reports AI is more expensive than paying human employees

#12
The premise of this article is incorrect - MS isn't cancelling Claude code internal usage because of AI costs too much, they're cancelling it because GitHub copilot is the compete product and they want their employees to use their product.

It's the same reason Teams got so much attention during lockdown.

Re: Microsoft reports AI is more expensive than paying human employees

#15
Taalas: https://taalas.com/products/

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.

Re: Microsoft reports AI is more expensive than paying human employees

#19
Burning tokens is as easy as throwing dollars in a furnace. Token usage is not a good measure of productivity. Problem is nobody has really been able to figure out how to gauge productive AI engagement. Are your developers maximizing productivity or are they burning tokens or resisting change.

Re: Microsoft reports AI is more expensive than paying human employees

#20

The title seems misleading, and reading the article explains the reason more clearly. There's nonsense OKR's and objectives at these companies to burn as many tokens as possible. It turns out that when you make a metric out of token usage, it unsurprisingly ends up becoming extremely expensive. Inference is affordable, and you don't need a SOTA proprietary model to get a lot of use out of this technology. While you l…

I am afraid that the TL would be uncomfortable if they have no human team members but only agents, which means they have no space to pass the bulk and have to take responsibilities for the business results.
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