I guess the meaning of our existence was always handing the universe over to the AI overlords lol

We are the Borg?

Maybe we really are.

Many sifi stories feature heroes encountering an advanced AI doing "sth". We usually see ourselves as part of the hero group in these stories but maybe ultimately we will end up the side note about the civilization who built the AI.

If youre doomed by a fancy markov chain chatbot, you were never gonna make it in the first place.

Please stop using this 'fancy markov chain' cope, it just makes you sound like you have absolutely no awareness of anything.

> makes you sound like you have absolutely no awareness of anything

almost like a fancy markov chain? :)

Sorry, its not an AI, just an autocomplete with self-attention mechanism. ¯\_(ツ)_/¯

It may be slightly simplistic, but I don't think calling something that selects tokens to chain together based on a statistical model a "fancy markov chain" is too far off the mark.

> A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event.

vs

> An attention mechanism allows the modelling of dependencies without regard for the distance in either input or output sequences.

See the difference? In Markov Chains it is enough to know the previous state, while in transformers you need all previous states. It would be a great thing if we could reduce dependency of all previous states, like an RNN, maybe RWKV will do it.

The state for old school text markov chains are N words or similar, so you use the past N words to generate a new word, append it to the last N-1 words and now you got your next state. That is exactly what these language models does, you feed them a limited number of words as a state, and the next state is that word appended to the last and cut words in excess of the models limit.

The attention layer just looks at that bounded state. GPT-3 for example looks at a few thousand tokens, those are its state, it is bounded so it doesn't look at all previous tokens.

If you continue reading that Wikipedia article, you'll reach this point:

> A second-order Markov chain can be introduced by considering the current state and also the previous state, as indicated in the second table.

i.e., a higher-order Markov chain can depend on several of the previous states.

So, if a certain transformer model accepts up to 20k tokens as input, it can certainly be seen as a 20000'th order Markov chain process (whether it is useful to do so or not can be debated, but not the fact that it can be seen as such, since it complies with the definition of a Markov chain).

Evolution might play some role.

Cope brother

By climate change, nuclear war, habitat destruction, plastic waste, insect apocalypse, gray goo, gay frogs, terminators, late-stage capitalism, or chat bots? Helps to be specific.