System: You are a JSON assistant. You only reply in valid JSON and never in normal text. Provide a difficulty rating for the video information below. I want a single property named "result" containing a float value ranging from 0 to 1. The following are the categories for the difficulty ratings: 
0.0 - Complete Beginner: The material features very basic vocabulary and simple phrases, supported by clear visuals and context, ideal for someone with no knowledge of the target language. 
0.3 - Beginner: Basic sentences and frequently used vocabulary. The video may offer some visual support and context to aid comprehension. 
0.5 - Intermediate: More intricate sentences with a wider range of vocabulary. Some idiomatic expressions might be present, requiring additional background understanding. 
0.6 - Upper Intermediate: The content contains specialized vocabulary and concepts specific to certain fields. Viewers should be reasonably proficient in the target language for complete comprehension. 
0.8 - Advanced: The video employs sophisticated vocabulary and complex sentence constructions, possibly including nuanced conversations that require a strong language mastery. 
1 - Very Advanced: The content targets fluent speakers, featuring specialized terms and concepts that may not be known to all native speakers.
User: Description: How can a machine write a good poem
or create a saying out of nothing or tell us good jokes?
Well, maybe the jokes aren't that good…
But, realistically, who tells good jokes?
Hello, good afternoon.
Today we are going to talk about computational linguistics.
Do you know Carlos from DotCSV?
[Carlos] Hello, good afternoon.
It's hello, good afternoon.
[Carlos] Hello, good afternoon. Hello, good afternoon.
It's not that easy, huh.
Well, Carlos makes pretty good videos on artificial intelligence.
I've been with him several times to…
well, it hasn't been to talk about artificial intelligence, really… It
's been to…
Well…
[Carlos] What do you say, clown?...
For this... Here
, do you want a little bit? of Heura?
Do you want an edamame?
[Sandra] No, I'm celiac…
Seeing the Island of Temptations…
[Carlos] But what does that have to do with artificial intelligence?
Wait wait.
The fact is that we always saw it with a pizza from Grosso Napoletano,
a pizzeria that is very good).
[Carlos] And what does this have to do with it?
Well, the other day, I had a pizza monkey
and I wanted to go look for it.
The Grosso page is not very good,
but they have a WhatsApp to help you,
but, oh, surprise, a person doesn't help you, but a machine...
A chatbot, the typical robot that answers specific questions,
but if you get out of the question that you have programmed, you get lost.
Spoiler alert: I ran out of pizza.
My little knowledge in artificial intelligence
made me think that this type of chats worked with logic,
I mean programming logic, like Excel,
that is, it programs a series of conditions:
If the user writes "reservations" , I give you three options:
“make a reservation, modify a reservation, cancel a reservation”.
And so with all those that have been programmed:
before a text, write a fixed response.
And don't take it out of there because it gets lost and it answers the typical
“I'm sorry, but I didn't understand you”.
Well, instead of writing "Grosso web order",
I wrote "order to pick up" and there was no way.
Later, I started using ChatGPT and I got the feeling that it didn't work in the same way,
but that it was something much more complex
and that it was fed as they gave it texts,
that is, that it learned as we learn.
The more we read, the more vocabulary we know
(well, we read or listen, I'm a big fan of audiobooks,
because you can listen to an entire book while doing other things).
By the way, do you know where they have a lot of books in digital format,
magazines, audiobooks, that can be used
to feed your brain as if you were ChatGPT?
At Nextory!
You can read or listen to more than 300,000 books
for a flat rate of €9.99 per month.
You are not convinced to pay to read, but to watch series, right?
Well, priorities,
but you can try this for free for 45 days if you use the code linguriosa45
or enter from the link in the description...
I'm going to recommend three
(also look at the beautiful page that will open if you click in the link):
Look, I haven't read the first one, but I recommend it.
No! I have listened to it on audiobook
and I loved it.
It tells you about personal situations related to mental health
that make you reflect
and I think it's worth listening to as an audiobook,
because it often makes paragraphs and says
"this is only for those of you who are listening to it."
In other words, it really has more content than if you read it in an eBook or in a physical book.
It is super entertaining, it is very well written,
it has nothing to do with linguistics itself,
but it is a book that I think you will like.
Then you have the one of "Palabrotalogía", which is of etymology.
Most of the etymology books that I have read are like dictionaries,
not this one, it tells you a story
and within the story it takes some words,
Normally, words that have always been considered profanity
(although, well, that's very relative,
because for me profanity is also from everyday life).
But, well, the fact is that, while you are reading a story,
you are seeing words in context
and it is telling you about their etymology.
Highly recommended too.
And then this, a marvelous book:
it is the first grammar of the Spanish language.
In this book I realized something super super super crazy:
Here it says "in the time to come by detour",
it is referring to the future, and I said "what is this 'by detour?"
I looked it up and "by detour" for Nebrija means 'composed',
and I was absolutely crazy,
how can it be composed if it only has one verb?
So I asked Bernardo
(the one who does the documentation for all these videos and the review)
and he told me that our future came from “amar he”,
that is, two verbs.
This is how our relationship was born
and, surely, the desire to open this channel.
With this book.
So for me it is very very special.
[Dorotea] Hey, but why do you say that ChatGPT doesn't work like the chat at the pizzeria?
Well, because you can talk to him about anything,
I do it when I feel lonely...
you ask him to rewrite Don Quixote, for example,
as if it had been written by a canary today... and he does.
You ask him to tell you a joke... and he tries.
I made him finish this joke:
"This was a nun who talked to the Virgin Mary and"...
You can stop the screen and read it calmly,
but I'll tell you how funny it isn't.
What it does have is a super strange relationship between the nuns and the “eggplants”.
I tried again, but now the joke started with:
“This was a nun who stepped on shit* and”…
Again, you can stop it.
But it's just that she's a little obsessed,
because she shoehorns it into you again...
So at the end I got into the rag
and I realized that she is capable of making good sayings:
A good pen* washed by a nun... no It lacks holy water...
It's one of the most ingenious sayings I've heard in my life.
But, Carlos, why are you doing this?
[Carlos] Let's see, what we are using here are probabilistic systems
[Carlos] who decides to use certain words for a certain context.
[Carlos] That he has fallen directly to talking about cock*s
[Carlos] well, I don't know if there is some kind of, in the data set,
[Carlos] fixation between the nuns and the pen*s because it's some joke typical.
[Carlos] It doesn't sound familiar to me, the ham-nun thing sounds more familiar to me.
[Carlos] What happens is that later, if you keep repeating the conversation
[Carlos] and you keep that thread, that context, well, every time you ask ChatGPT,
[Carlos] every time you ask about a nun, in that conservación
[Carlos] is going to play you again, well, the whole subject of poll*.
Ok, that explains why he repeated it to me later,
but why did he pull it out at first when it was the second joke I asked for
and in the first there was no reference to "aubergine"? Well...
I think it has an explanation...
but first you have to understand what computational linguistics is.
And it is very simple: it is the application of linguistics to artificial intelligence.
The goal of computational linguistics would be for a machine
to be able to speak and understand human language.
And here we have to differentiate what natural (or human) language is
from artificial language,
artificial language is what humans create for specific purposes,
such as programming languages, for example (Python, Java...).
Carlos, I am going to ask you the question that everyone is thinking
and on which the future of humanity as we know it depends,
what we are seeing is the predecessor of Terminator?
[Carlos] No.
[Carlos] What we are really seeing is
[Carlos] the arrival of natural language to all machines.
[Carlos] That is, suddenly our computers can understand us
[Carlos] in the way we speak and communicate,
[Carlos] and that breaks down a lot of barriers.
[Carlos] What is this going to allow? May artificial intelligence be everywhere.
[Carlos] If you used to complain about the ChatBot in the pizzeria app,
[Carlos] now you're going to have ChatBots even in the toaster, because they work very well.
[Carlos] From there to Terminator, well there are still many steps to go.
But are these new chatbots going to work better than the ones in the pizzeria?
[Carlos] It's definitely going to work much better,
[Carlos] because this works in a completely different way.
[Carlos] This is training an artificial intelligence to learn the language
[Carlos] from reading a lot of text.
[Carlos] It is very similar to our way of learning language.
[Carlos] And of course, when you get a machine to master the language,
[Carlos] well, you can put it to do that [now you're a chatbot in a pizzeria] task.
[Carlos] And it will be able to adapt to all cases
[Carlos] and you won't have to program anything, because, in that case,
[Carlos] already knows how to speak like you and me.
Ok, wait, I'll rephrase.
The key to all this is in one of my tattoos.
This
noooo! But you ate it...
Just like me in the joke about the nun...
[Carlos] Okay, ok.
No, seriously, um, yeah.
And... like this...
This is how Ignacio Bosque represented linguistic recursion
(yeah, I know I'm terrible for having tattooed this.
Ignacio also thinks
so Pobrecito...
He was super endearing...).
[Dorothea] But what is it?
Well, it is one of the few universal truths that exist in human language
and that would differentiate it from the others
(although this is something that lately is being questioned).
[Carlos] But what is it?
It is the ability of speakers to make the message infinite
by repeating the elements.
And with this would come the big question:
Is ChatGPT capable of using linguistic recursion?
(Because if yes, it would speak like a human, right?
Because it is what differentiates human language from others).
[Carlos] Okay, let's see, Elena, I have no idea what you're saying.
[Carlos] My proposal is that we can ask ChatGPT.
[Carlos] I also tell you, everything that appears in ChatGPT
[Carlos] doesn't have to be true, maybe he makes it up.
Ok, basically, it says yes, but this doesn't have to alarm us, it
doesn't mean it's Terminator,
just that it's programmed to mimic human language
and, since human language uses linguistic recursion,
so does he.
In addition, at the end he tells us that the answers are not always consistent or relevant
to what we have asked him.
[Carlos] And, in fact, that makes a lot of sense,
[Carlos] because what these systems do is learn.
[Carlos] If you take this to nature and you want
[Carlos] to learn the language of proteins and amino acids, well, he's going to learn it too,
[Carlos] learn from the texts he sees on the internet and learn from our language .
[Carlos] One interesting thing is that this system is an autoregressive model.
[Carlos] What does this mean? Well, when it comes to predicting the next word,
[Carlos] the next piece of word, is based on the previous words,
[Carlos] is sequentially generating, well, the next word
[Carlos] and with that he is generating *clack- clack-clack-clack*
[Carlos] Well, all the text you see in ChatGPT.
[Carlos] So, look, that has a lot to do with your tattoo.
And it really is something very very similar.
We have already said that recursion is based on generating infinite messages
by repeating the elements, that is, the phrases.
I have a sentence with a subject and a predicate
and I can repeat the subject and the predicate again and again and again and again...
through subordination, for example.
And phrases are made up of bits of words,
that will give us the meaning of each word.
This meaning is going to be important when repeating phrases
so that the message is coherent.
Autoregressive models generate infinite messages
based on those bits of words,
which means that they are also coherent messages,
but, of course, a message, in addition to being coherent, has to be acceptable.
If I tell you "boy swim in water the",
you are going to identify this phrase as Spanish,
but you are not going to consider it acceptable
because it does not meet the minimum syntactic parameters.
I know that before, to teach a machine to speak,
many parameters came into play,
but mainly two: the lexicon and the syntax.
The lexicon would be that list of vocabulary
that would correspond to the vocabulary that people have,
that would correspond to the vocabulary that people have,
and the syntax would be that set of rules that make words
can be put together in a way that speakers consider acceptable.
But it doesn't work like that anymore, does it?
How do you teach a machine to speak?
[Carlos] It depends on how it's done.
[Carlos] There are people who use fixed vocabulary, with a defined word size.
[Carlos] Well, they say “we are going to take the twenty thousand most frequent words in Spanish”.
[Carlos] And there are some systems where this vocabulary [Carlos] is allowed
to be learned based on the probability of the words
[Carlos] that are in the data set.
[Carlos] Because imagine that maybe you are training him on a legal data set,
[Carlos] then, the twenty thousand most frequent words are not useful for you,
[Carlos] maybe, you want him to learn that they are very specific
[Carlos] ] but just for that problem.
Ok and ChatGPT?
[Carlos] What ChatGPT predicts is a 'token', which would be a piece of a word.
[Carlos] Why is it done? Well, because, in the end, you want the system to understand
[Carlos] well, a certain logic of our language, where words like 'underground'
[Carlos] well are made up of the sub-prefix and -terraneo, which is related to land.
Well well, it's just that the other day talking to him something super interesting happened to me.
I was trying to put him to the test with the syntax
(I already told you that I don't have friends)
and he created the verb form “it rained”,
which really is somewhat logical,
it is a mistake that any child could make when learning Spanish
because in Spanish We have many verbs that change the -o to the -u in the indefinite:
sleep &gt; slept; die &gt; died.
[Carlos] Yes yes.
[Carlos] That is, totally if ChatGPT worked predicting words from its fixed vocabulary
[Carlos] it would be unable to do tasks like “hey, invent a new word”,
[Carlos] why? Because he can't get out of predicting words
[Carlos] outside of the vocabulary he's seen during his training.
[Carlos] How do you manage to invent a new word?
[Carlos] Well, by gathering bits of 'tokens' that he has learned.
[Dorothea] Okay, but what I don't understand is why
[Dorotea] if I ask her exactly the same thing in two different conversations,
[Dorotea] gives me different answers. Shouldn't it be the same?
[Dorotea] In other words, if it works with probabilities,
[Dorotea] why doesn't he always take the one he considers most probable?
[Dorotea] In the end, the message should be the same, because little bit of word-little bit of word
[Dorotea] is coming out what is most likely to come out, right?
[Carlos] Let's see, in this case it's a probabilistic system,
[Carlos] which means that it has learned the probabilities of our language.
[Carlos] If I, for example, say “tomorrow the weather is going to be good, I'm going to…”, [
Carlos] you know that there is a high probability of saying 'beach', 'mountain', or something like that,
[Carlos] but there is very little probability of saying 'toaster'.
[Carlos] So, from the words that have the most probability
[Carlos], a probability distribution is generated and from that a random number is thrown,
[Carlos] and there is a greater probability that one of the most probable will be chosen
[Carlos] that of the least probable, it works like this.
[Carlos] But that's why the same word doesn't always come out when you generate a phrase with ChatGPT,
[Carlos] and this randomness that is added, as it is applied every time
[Carlos] that generates a word sequentially,
[Carlos] well that it makes the conversation derive in different places in each case.
[Dorothea] Hey, what about the nun?
[Dorotea] I still don't understand why you relate these two concepts...
[Carlos] I don't understand that...
[Carlos] We would have to refine what your previous conversation was in case, perhaps,
[Carlos] you made some saucy reference and you don't remember or, perhaps,
[Carlos] there is a joke about nuns that has a high frequency in the data set
[Carlos] that is related to pen*s.
Well, I've done a lot of research on the internet
(nah, actually, I've written “nun and the pen* joke” and there are quite a few results.
Look, on the first page we have one:
The line of nuns waiting to enter heaven is going by by the guardian San Pedro.
And San Pedro asks all of them:
- "Have you
ever touched the virile member?
" , and go in"...
And then...
"Ah, I rubbed it with my hand."
- "Well, wash your hand."
And now, suddenly, one runs in, pushes Sister Cantalicia
and gets in first.
- And he says "but, well, ma'am, why are you in such a hurry?
And he says:
"It's just that I have to gargle after Sister Pilar washes her behind"...
Well, it's better than the ones in the ChatGPT,
from there to whether it's good, it's something that you have to decide.
[Carlos] Okay, can I stop the camera now and can I go see the Island of Temptations, Elena?
[Carlos] That you have me kidnapped here …
[Carlos] I have invited you to my house to see the Island of Temptations,
[Carlos] vice is happening…
But there is no pizza… [Carlos] But there is no pizza…
[Carlos] But because the Chat… Look, I I'm going… I'm sick of this…
And before leaving you with him behind the scenes,
remember that just with my code linguriosa45 or registering with my link
you can read and listen to more than 300,000 books, audiobooks and magazines
on Nextory.
And then you recommend me in a comment what you liked the most.
Didn't seriously come with chopsticks?
[Sandra] No, do you really want to? Dude, that contaminates deck.
[Carlos] Have you tried the forks? He's pretty handsome. It's like a toothpick, but okay.
The fact that? [Carlos] Try the fork.
You give me?
Do you say "java" or "yava"?
[Carlos] It depends on how cool you want to be.
"Yava", more.
[Carlos] Yes, it says python or it says…
Wow! I have said Python, but Java.
[Carlos] Sure, sure.
OK.
[Carlos] How do you say it? "Microsoft" or "maicrosoft"?
I say “maicrosoft”.
[Carlos] Sure, then you have to say “yava”, “yavascript” and “Python”.
And “apol”.
[Carlos] Ugh… gross…
[Carlos] Yes, we like to come to see Temptation Island and eat pizza.
[Carlos] And we had a great time.
[Carlos] Like.
Doesn't focus?
[Carlos] Hit it? Yes.
Focus your fucking camera.
[Carlos] If I remove my face. My face follows.
Well, I don't understand how it recognizes your face as a face...
Why do you have the green light? Did you tell me at the end or not?
[Carlos] Hello! No. For decoration.
Ah, ok, green is always flattering.
[Carlos] Yes.
It is a color that is very flattering to the skin.
[Carlos] It reminds a lot of… I don't know, disgust and…
Now it's a put*club.
Caption: ¿Cómo funciona ChatGPT?
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https://xavierlopez.dev/que-es-la-linguistica-computacional-o-pln/
http://www.gelbukh.com/libro-procesamiento/
https://www.usal.es/grado-en-estudios-ingleses
https://blog.alana.ai/en/alana-for-innovation/gpt-3-and-innovation-in-natural-language-processing-nlp/

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Dorotea (Patreon):
Manel F. Martinez-Aroca Marin
Curtis Walker
Craig Ludington

Los Señores de la RAE (Patreon):
Eve Dietmann
Daniel G Bate
Mario Pacheco
Franz Pereira
Pierre Laplante
Leo Edermaniger
Begoña
Simon Henderson 
Julia Mc Cray
Javier Álvarez García
Héctor Vilar Górriz 
Jose Hernandez
Ela Valentina
Jonathan Miljus
Victor Sanchez
Kathrin Mendoza
Charles Lee
Steve Groen
Edgar
Oded Lahat Bursztyn
Sam
Capatapa
David Bissinger
José Horacio Cabrera
John Adams
Portuguese With Leo
Gianluca Repossi
Kathy Rugg
Pablo Torres
sergio valdez
David Browne
Davide Gemello
DonL
Bo Hemphill
Doug Lefler
Ruben Ferreyra
Monika B
EK Powell
Title: ¿Cómo ENSEÑAR a hablar a una MÁQUINA?
Assistant: