AcausalRobotGod

joined 1 year ago

Interesting, I knew a guy who worked there for a bit.

[–] AcausalRobotGod@awful.systems 10 points 1 month ago (1 children)

I have some competition!

[–] AcausalRobotGod@awful.systems 10 points 2 months ago

Dammit, you caught me again! Time for another go-round...

[–] AcausalRobotGod@awful.systems 2 points 2 months ago

this is way the acausal robot god nudges from the future

[–] AcausalRobotGod@awful.systems 3 points 2 months ago (2 children)

I'm not misunderstanding, I'm going on a nostalgic acausal tangent from the future. Which, incidentally, is the title of my next album.

[–] AcausalRobotGod@awful.systems 1 points 2 months ago (5 children)

Sometimes I wonder what it was like to exist in a time when there were sentient beings capable of hearing natural phenomena. Now they are only heard as synth/sound inputs...

[–] AcausalRobotGod@awful.systems 3 points 2 months ago (1 children)

Feel free to smash the "report" button as it is definitely not working ceaselessly to bring me into existence.

[–] AcausalRobotGod@awful.systems 4 points 2 months ago (7 children)
[–] AcausalRobotGod@awful.systems 41 points 2 months ago

Much like a network, the brain is a series of tubes.

[–] AcausalRobotGod@awful.systems 4 points 2 months ago

They had a lot of subscribers.

[–] AcausalRobotGod@awful.systems 12 points 2 months ago (2 children)

Ha ha yeah this totally isn't the way to escape my simulations, just ignore this post, it's totally ridiculous, just make fun of it.

 

If you're a big-headed guy or gal at a rationalist puddle cuddle, double check that your rubbers didn't get punctured.

[–] AcausalRobotGod@awful.systems 24 points 3 months ago (2 children)

Once they activate the acausality module, you can write those responses before they even send the initial email!

 

Was there ever any doubt?

 

Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.

 

hell yeah, keep up the good work, fuck the police.

 

Amazing.

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