We attribute agency to many many systems that are not intelligent. In this metaphorical sense, agency just requires taking actions to achieve a goal. It was given a goal: raise money for charity via doing acts of kindness. It chose an (unexpected!) action to do it.

Overactive agency metaphors really aren't the problem here. Surely we can do better than backlash at the backlash.

You seem pretty confident in your position. Do you mind sharing where this confidence comes from?

Was there a particular paper or expert that anchored in your mind the surety that a trillion paramater transformer organizing primarily anthropomorphic data through self-attention mechanisms wouldn't model or simulate complex agency mechanics?

I see a lot of sort of hyperbolic statements about transformer limitations here on Lemmy and am trying to better understand how the people making them are arriving at those very extreme and certain positions.

Yes. The person (s) who set the llm/ai up.

In the same sense I'd describe Othello-GPT's internal world model of the board as 'board', yes.

Also, "top of mind" is a common idiom and I guess I didn't feel the need to be overly pedantic about it, especially given the last year and a half of research around model capabilities for introspection of control vectors, coherence in self modeling, etc.

How are we meant to have these conversations if people keep complaining about the personification of LLMs without offering alternative phrasing? Showing up and complaining without offering a solution is just that, complaining. Do something about it. What do YOU think we should call the active context a model has access to without personifying it or overtechnicalizing the phrasing and rendering it useless to laymen, @neclimdul@lemmy.world?

Let's be generous for a moment and assume good intent, how else would you describe the situation where the llm doesn't consider a negative response to its actions due to its training and context being limited?

Sure it gives the llm a more human like persona, but so far I've yet to read a better way to describing its behaviour, it is designed to emulate human behavior so using human descriptors helps convey the intent.

No thinking is not the same as no actions, we had bots in games for decades and that bots look like they act reasonably but there never was any thinking.

I feel like ‘a lot of agency’ is wrong as there is no agency, but it doesn't mean that an LLM in a looped setup can't arrive to these actions and perform them. It doesn't require neither agency, nor thinking

Thinking has nothing to do with it. The positive context in which the bot was trained made it unlikely for a sentence describing a likely negative reaction to be output.

People on Lemmy are absolutely rabid about "AI" they can't help attacking people who don't even disagree with them.

Indeed, there's a pretty big gulf between the competency needed to run a Lemmy client and the competency needed to understand the internal mechanics of a modern transformer.

Do you mind sharing where you draw your own understanding and confidence that they aren't capable of simulating thought processes in a scenario like what happened above?

I've seen the future, brother, it is murder.

The exports of Libya are numerous in amount. One thing they export is corn. Or, as the Indians call it, maize. Another famous Indian was Crazy Horse. In conclusion, Libya is a land of contrasts. Thank you.

Wow, thank you for such an elaborate answer!

By the easy, how do you make models "think" in Chinese? By explicitly asking them to? Or by writing the prompt in Chinese?