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321 points jhunter1016 | 1 comments | | HN request time: 0s | source
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Roark66 ◴[] No.41878594[source]
>OpenAI plans to loose $5 billion this year

Let that sink in for anyone that has incorporated Chatgpt in their work routines to the point their normal skills start to atrophy. Imagine in 2 years time OpenAI goes bust and MS gets all the IP. Now you can't really do your work without ChatGPT, but it cost has been brought up to how much it really costs to run. Maybe $2k per month per person? And you get about 1h of use per day for the money too...

I've been saying for ages, being a luditite and abstaining from using AI is not the answer (no one is tiling the fields with oxen anymore either). But it is crucial to at the very least retain 50% of capability hosted models like Chatgpt offer locally.

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bbarnett ◴[] No.41878725[source]
The cost of current compute for current versions pf chatgpt will have dropped through the floor in 2 years, due to processing improvements and on die improvements to silicon.

Power requirements will drop too.

As well, as people adopt, the output of training costs will be averaged over an ever increasing market of licensing sales.

Looking at the cost today, and sales today in a massively, rapidly expanding market, is not how to assess costs tomorrow.

I will say one thing, those that need gpt to code will be the first to go. Becoming a click-click, just passing on chatgpt output, will relegate those people to minimum wage.

We already have some of this sort, those that cannot write a loop in their primary coding language without stackoverflow, or those that need an IDE to fill in correct function usage.

Those who code in vi, while reading manpages need not worry.

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1. ben_w ◴[] No.41878943[source]
> We already have some of this sort, those that cannot write a loop in their primary coding language without stackoverflow, or those that need an IDE to fill in correct function usage.

> Those who code in vi, while reading manpages need not worry

I think that's the wrong dichotomy: LLMs are fine at turning man pages into working code. In huge codebases, LLMs do indeed lose track and make stuff up… but that's also where IDEs giving correct function usage is really useful for humans.

The way I think we're going to change, is that "LGTM" will no longer be sufficient depth of code review: LLMs can attend to more than we can, but they can't attend as well as we can.

And, of course, we will be getting a lot of LLM-generated code, and having to make sure that it really does what we want, without surprise side-effects.