171–180 of 244 posts
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Why not let it do all the work then?
It's not perfect, ofcourse.
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I've been trying to make it be a DM for a while now. It works seemingly well for a while but it's making everything up on the fly, which is fine as long as there's not state that needs to be maintained/remembered. Once you start trying to get it to do combat, it seems like it's working pretty well but eventually you realize that it's just making shit up behind the scenes. It'll tell you there are 4 goblins ambushing…
You should put a blog/site up with some examples. "GPT being the worst DM ever" sounds hilarious. "I attack the goblin." "What goblin?" "The goblin you just said was there." "I'm sorry, I was mistaken. It's actually a Beholder."
[1] https://en.wikipedia.org/wiki/HarmonQuest [2] https://en.wikipedia.org/wiki/Drunk_History
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- "ftxbro"
After lurking I made this account only to post a joking-not-joking explanation of why Alameda had the weirdly specific credit limit $65,355,999,994 with FTX and why I thought it could be a funny off-by-almost-1000x bug/typo/mishap https://news.ycombinator.com/item?id=34473811 but I think almost no one read my comment because I posted it so late after the thread had scrolled off the front page :(
> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. I don't know why, but my brain refuses to accept GPT-4 as something close to AGI. Maybe I am wrong. It is hard to believe that our brain is just a bunch of attention layers and neural nets.
It seems clear to me that these systems think in a meaningful sense, but I don't think they are beings . In Cybernetics there is a result that says that any well-regulated system must contain a model of itself. This seems as good a definition as any of a "being", and by this definition these language models don't make the cut.
> Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. But it's just statistics, a fancy text predictor, a Markov-chain. Surely these scientists that work in the field of AI and are intimately familiar with how this stuff works aren't so stupid as to think emergent behavior pote…
> Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. But it's just statistics, a fancy text predictor, a Markov-chain. Surely these scientists that work in the field of AI and are intimately familiar with how this stuff works aren't so stupid as to think emergent behavior pote…
GPT-4 is often overhyped and underhyped because few really understand it. It's not a Markov Chain or a fancy text predictor. It's a ~200 layer neural network that models a vast hierarchy of concepts through language. It has emergent properties that we don't yet understand.
I remember reading this somewhere - "There is a considerable overlap between the intelligence of the smartest bears and the dumbest tourists.". Though I do not think GPT-4 is even close to AGI it can definitely claim to be better at faking it than many intelligent beings can.
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GPT-4 is often overhyped and underhyped because few really understand it. It's not a Markov Chain or a fancy text predictor. It's a ~200 layer neural network that models a vast hierarchy of concepts through language. It has emergent properties that we don't yet understand.
it is a markov chain; At least the underlying decoder only transformer is.
GPT-3.5, like its predecessor GPT-3, is not a Markov chain. GPT-3.5 is based on the GPT (Generative Pre-trained Transformer) architecture, which is a type of neural network known as a Transformer. Transformers use self-attention mechanisms to process and generate text, allowing them to capture long-range dependencies and context in the input data.
On the other hand, a Markov chain is a stochastic model that describes a sequence of possible events, where the probability of each event depends only on the state attained in the previous event. While Markov chains can be used for simple text generation, they lack the ability to capture the complex relationships and long-range dependencies that GPT-3.5 can handle.