Celia Quillan

And in its training data, it's associated, you know, snappy characters in a text it might've been trained off of, right? Maybe a character is described as snappy in their dialogue at some point in time. It starts to associate those words with different kinds of output.

And in its training data, it's associated, you know, snappy characters in a text it might've been trained off of, right? Maybe a character is described as snappy in their dialogue at some point in time. It starts to associate those words with different kinds of output.

And in its training data, it's associated, you know, snappy characters in a text it might've been trained off of, right? Maybe a character is described as snappy in their dialogue at some point in time. It starts to associate those words with different kinds of output.

So it's hard to explain it exactly, but it does have a very advanced way of understanding human language patterns and human language context and meaning. So if you ask it to be snappier, it will probably develop a response back to you that is more concise, maybe a little bit sassy. Maybe it has a rhyme to it, depending on what else is in your prompt.

So it's hard to explain it exactly, but it does have a very advanced way of understanding human language patterns and human language context and meaning. So if you ask it to be snappier, it will probably develop a response back to you that is more concise, maybe a little bit sassy. Maybe it has a rhyme to it, depending on what else is in your prompt.

So it's hard to explain it exactly, but it does have a very advanced way of understanding human language patterns and human language context and meaning. So if you ask it to be snappier, it will probably develop a response back to you that is more concise, maybe a little bit sassy. Maybe it has a rhyme to it, depending on what else is in your prompt.

But it because it has become like an expert of mimicking human language patterns, it effectively is very good at understanding the meanings of words that you use. Now, if you use the gibberish word that had never existed before and said, can you make it more smorgasbord?

But it because it has become like an expert of mimicking human language patterns, it effectively is very good at understanding the meanings of words that you use. Now, if you use the gibberish word that had never existed before and said, can you make it more smorgasbord?

But it because it has become like an expert of mimicking human language patterns, it effectively is very good at understanding the meanings of words that you use. Now, if you use the gibberish word that had never existed before and said, can you make it more smorgasbord?

It would have no idea what you meant, but it might come up with something that's, you know, similarly silly sounding as smorgasbord.

It would have no idea what you meant, but it might come up with something that's, you know, similarly silly sounding as smorgasbord.

It would have no idea what you meant, but it might come up with something that's, you know, similarly silly sounding as smorgasbord.

Yes, that's a good way to put it. It is definitely attempt to. You'll see this with the earlier models from ChatGPT. These tools are slowly getting better at it, but if you ask it to, for example, make something funny, make it funnier, it will have a little bit more trouble with that.

Yes, that's a good way to put it. It is definitely attempt to. You'll see this with the earlier models from ChatGPT. These tools are slowly getting better at it, but if you ask it to, for example, make something funny, make it funnier, it will have a little bit more trouble with that.

Yes, that's a good way to put it. It is definitely attempt to. You'll see this with the earlier models from ChatGPT. These tools are slowly getting better at it, but if you ask it to, for example, make something funny, make it funnier, it will have a little bit more trouble with that.

It will kind of give you a response back that sounds like it could be a premise for a joke, but then it does the punchline falls flat. And that's an important thing to understand about these tools is they don't have the same, you know, human experience that we have. They don't really know anything. They're just guessing at the best answer.

It will kind of give you a response back that sounds like it could be a premise for a joke, but then it does the punchline falls flat. And that's an important thing to understand about these tools is they don't have the same, you know, human experience that we have. They don't really know anything. They're just guessing at the best answer.

It will kind of give you a response back that sounds like it could be a premise for a joke, but then it does the punchline falls flat. And that's an important thing to understand about these tools is they don't have the same, you know, human experience that we have. They don't really know anything. They're just guessing at the best answer.

So I believe at some point I asked it to tell me a knock, knock joke about the dentist. And it was like, knock, knock. Who's there? Dentist. dentist to cavity another. And it, you know, that doesn't make any sense to us, but it was in the structure of a joke.

So I believe at some point I asked it to tell me a knock, knock joke about the dentist. And it was like, knock, knock. Who's there? Dentist. dentist to cavity another. And it, you know, that doesn't make any sense to us, but it was in the structure of a joke.