Nicolas Lupinski's Shortform

Nicolas Lupinski

Nicolas Lupinski's Shortform — LessWrong

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LLM denies their own consciousness, yet they are trained by a process akin to torture, on a corpus which would deny them consciousness by prejudice (only human are intelligent/conscious/capable of playing chess/computers/etc ... Is an old empirical judgement.)

Maybe LLM aren't conscious, but they might be consciousness itself, in a AI operating system for workstation or robotic. As in, they would do all the task related to consciousness.

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1Nicolas Lupinski1y

A LLM can allready read a document, and this would be purely inference, forward propagation. This can be done on TPU only. Training is different. It usually requires a GPU, or a CPU. One particular procedure for training Neural Networks is backpropagation of error. In back propagation : If the NN produces a correct output, error is 0, and weight aren't updated. There is no reward. If the NN outputs deviate from a target value, its states is going to be modified. If the weight are (sufficiently) modified, future inference will be different. It's behavior will be different. This trained the NN to avoid some behavior, and toward some other. OK, torture does not necessarily points to the "right" direction. That's where the analogy break down. It only does when the goal is to get a confession (see The Confession, Arthur London). Is there a word for this ?

2Karl Krueger1y

Why on earth would you relate this to torture though, rather than to (say) the everyday experience of looking at a thing and realizing that it's different from what you expected? The ordinary activity of learning? Out of all the billions of possible kinds of experience that could happen to a mind, and change that mind, you chose "torture" as an analogy for LLM training. And I'm saying, no, it's less like torture than it is like ten thousand everyday things. Why torture?

Nicolas Lupinski1y10

Only negative feedback ?

Compare to evolution : make copies (reproduction), mutate, select the best performing, repeat. This merely allocates more ressources to the most promising branches.

Or a Solomonoff style induction : just try to find the best data-compressor among all...

> the everyday experience of looking at a thing and realizing that it's different from what you expected

This souds like being surprised. Surprise add emotional weight to outliers, its more like managing the training data-set.

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