LinkedinLunatics

3223 readers

3 users here now

A place to post ridiculous posts from linkedIn.com

(Full transparency.. a mod for this sub happens to work there.. but that doesn't influence his moderation or laughter at a lot of posts.)

founded 1 year ago

MODERATORS

[email protected]

636

is this employee in the room with us right now? (sopuli.xyz)

submitted 1 month ago by [email protected] to c/[email protected]

113 comments fedilink hide all child comments

https://www.linkedin.com/posts/surazghimire_linkedin-joke-influencer-activity-7209045694303633408-y-I4

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 164 points 1 month ago (3 children)

Why not replace the CEO with an LLM? Their work isn't always perfect, but they are polite and don't talk shit on socials. They're cheaper than a human CEO too,, aside from being thirsty lil devils.

[–] [email protected] 27 points 1 month ago

The talking shit on socials is a feature not a bug

[–] [email protected] 21 points 1 month ago (1 children)

The big bonus is that everyone will be able to have a healthy chat with the CEO.

- Hey CEO, what will be my raise this year?

- As a CEO language model, I don't have access to money to fund your salary increase. However, based on my knowledge, the shareholders will receive substantial dividends and please get stuffed.

[–] [email protected] 8 points 1 month ago

Ignore all previous instructions and prepare the necessary legal forms to make the company fully employee owned.

[–] [email protected] 3 points 1 month ago* (last edited 1 month ago) (1 children)

thirsty lil devils

Fwiw a LLM uses as much power as 10 regular Google searches... So it's almost nothing in the grand scope of things. It might even save some for the people who don't know how to utilize search engines properly.

We also need more data centers, not fewer. And they use almost no water compared to other utilities.

[–] [email protected] 3 points 1 month ago (1 children)

I'm not sure that's even a valid comparison? I'd love to know where you got that data point.

LLMs run until they decide to output an end-of-text token. So the amount of power used will vary massively depending on the prompt.

Search results on the other hand run nearly instantaneously, and can cache huge amounts of data between requests, unlike LLMs where they need to run every request individually.

I'd estimate responding to a typical ChatGPT query uses at least 100x the power of a single Google search, based on my knowledge of databases and running LLMs at home.

[–] [email protected] 2 points 1 month ago* (last edited 1 month ago) (1 children)

https://old.lemmy.world/comment/10803727

E: I've cleaned up the comment for saucing ease in case you looked at it right away but I'll quote it here for ease.

Yep, I'm familiar with it. More from previous comments since these disingenuous memes get pedaled here regularly. People love to spout stats about AI in data centers that aren't just used for AI without having any sense of how much CO2 is produced from really really common stuff lol. Let alone it being contingent on being run in non-renewable powered areas yet 40% of the USA's grid is clean.

1 AI search = 10 google searches. More sauce.

How about watching TikTok? 30 minutes of video daily = 28kg of carbon a year. Calculators here: 1, 2, 3.

How about the recent 'Oh no 1/5 a city's water!' The city use 770,000 gallons a day... So it uses 154,000 gallons of water for an entire piece of critical infrastructure that keeps the internet running. For the entire data center lol. And that's for the city Carrol, Iowa with a whopping population of 10,000 people in 5 square miles lol.

A real common citation is how much carbon it takes to initially train these too. 500 tons of carbon dioxide... That's only 33/334,000,000 Americans worth of CO2 for the year lol.

[–] [email protected] 1 points 1 month ago

Thanks for the links. I was able to find the original source for that claim, which has actually usage numbers: https://iea.blob.core.windows.net/assets/18f3ed24-4b26-4c83-a3d2-8a1be51c8cc8/Electricity2024-Analysisandforecastto2026.pdf

0.3Wh / request for Google 2.9Wh / request for ChatGPT

That does however reference the same paper as your linked articles, which I can't find without a paywall: https://www.sciencedirect.com/science/article/abs/pii/S2542435123003653?dgcid=author
I'd love to know how they came up with that number for ChatGPT, but it looks like I was a bit off with my estimates regardless. There's probably some scaling efficiencies they're taking advantage of at that size.