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satireplusplus t1_iznkxx5 wrote

I've actually had it explain an obscure warning, faster than googling it and already tells you what to do to get rid of the warning.

I've also found ChatGPT super useful for mudane stuff too, create a regex for a certain pattern giving it just a description and one example, create a flask API end point with a description of what it does etc. Code often works out of the box, sometimes needs minor tweeks. But its much easier to correct a regex with one minor issue than writing it from scratch.

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ReginaldIII t1_iznsvav wrote

Honest question, do you consider the environmental impact of how you are using this to avoid very basic and easy to do tasks?

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satireplusplus t1_izntr6m wrote

Amusing question. It's a tool like any other, you're using a computer too to avoid doing basic tasks by hand. Inference actually isn't that energy expensive for GPT type models. And the way I used it, it's probably more useful than generating AI art.

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ReginaldIII t1_iznu5ry wrote

If people were constantly crunching an LLM every time they got a stack trace and this was a normal development practice despite it being largely unnecessary.

Then given it is all complete avoidable, would it not be a waste of energy?

> It's a tool like any other, you're using a computer too to avoid doing basic tasks by hand.

That's a nonstarter. There are plenty of tasks more efficiently performed by computers. Reading an already very simple stack trace is not one of them.

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satireplusplus t1_iznuvy5 wrote

Generating this takes a couple of seconds and it can probably be done on a single high end GPU (for example, eleuther.ai models run just fine on one GPU). Ever played a video game? You probably "wasted" 1000x as much energy in just one hour.

The real advantage is that this can really speed up your programming and it can program small functions all by itself. It is much better than stackoverflow.

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ReginaldIII t1_iznvys0 wrote

Okay. But if you didn't do this you would not need to crunch a high end GPU for a couple of seconds. And if many people were doing this as part of their normal development practices then that would be many high end GPUs crunching for a considerable amount of time.

At what scale does the combined environmental impact become concerning?

It is literally a lot more energy consumed than is consumed by interpreting the error yourself, or by Googling and then accessing a doc page or stackoverflow thread. And it is energy that gets consumed every time anyone gets that error, regardless of whether an explanation for it has been generated for someone else already.

> Ever played a video game? You probably wasted 1000x as much energy in just one hour.

In terms of what value you get out of the hardware for the energy you put into it, the game is considerably more efficient than an LLM.

> The real advantage is that this can really speed up your programming and it can program small functions all by itself. It is much better than stackoverflow.

If an otherwise healthy person insists on walking with crutches all day every day. Will they be as strong as someone who just walks?

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dasdull t1_izo1b23 wrote

If you run a Google search, Google will also run a LLM on your query.

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ReginaldIII t1_izo2mww wrote

They also cache heavily. Sustainability is a huge problem in ML and HPC.

In my job I spend a lot of time considering the impact of the compute that we do. It is concerning that the general public dont see how much extra and frivolous compute hours we are burning.

It's one thing to have a short flash of people trying out something new and novel and exciting. It is another to suggest a tool naively built on top of it with the intention of long term use and wide spread adoption.

The question of the environmental impact is legitimate.

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Log_Dogg t1_iznww2c wrote

"Why would you use a calculator when you can just get the solution using a pen and paper?"

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ReginaldIII t1_iznxeag wrote

A calculator can be significantly more energy efficient than manual calculations.

Crunching a high end GPU to essentially perform text spinning on a stack trace is not more efficient than directly interpreting the stack trace.

E: See this is a weird comment to downvote because it is literally correct. Some usages of energy provide higher utility than others. Radical idea, I know.

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antinode t1_izodbht wrote

Your comments bitching about this wasting electricity are wasting electricity.

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ReginaldIII t1_izoe71e wrote

My comment attempting to have a civil discussion about sustainability of LLMs in production applications compared to yours intended only to be derisive and petty?

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antinode t1_izoldjm wrote

Dude stop wasting electricity with your comments you're contributing to climate change we're all going to die.

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ReginaldIII t1_izolr3v wrote

If you really care about that then you care about this.

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_poisonedrationality t1_izoeb0w wrote

People shitting on exploring AI technology for "environmental impact" are the worst type of griefers.

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ReginaldIII t1_izoi4bq wrote

Nothing wrong with exploring new AI technology. But there is absolutely a point when you are talking about deploying a system for long term or widespread use where you should stop to consider the environmental impact.

The hostility from people because they've been asked to even consider the environmental impact is telling.

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