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hi everyone so by now you have probably
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heard of chat GPT it has taken the world
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and AI Community by storm and it is a
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system that allows you to interact with
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an AI and give it text based tasks so
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for example we can ask chat GPT to write
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us a small Hau about how important it is
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that people understand Ai and then they
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can use it to improve the world and make
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it more prosperous so when we run this
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AI knowledge brings prosperity for all
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to see Embrace its
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power okay not bad and so you could see
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that chpt went from left to right and
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generated all these words SE sort of
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sequentially now I asked it already the
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exact same prompt a little bit earlier
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and it generated a slightly different
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outcome ai's power to grow ignorance
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holds us back learn Prosperity weights
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so uh pretty good in both cases and
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slightly different so you can see that
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chat GPT is a probabilistic system and
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for any one prompt it can give us
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multiple answers sort of uh replying to
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it now this is just one example of a
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problem people have come up with many
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many examples and there are entire
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websites that index interactions with
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chpt and so many of them are quite
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humorous explain HTML to me like I'm a
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dog uh write release notes for chess 2
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write a note about Elon Musk buying a
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Twitter and so on so as an example uh
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please write a breaking news article
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about a leaf falling from a
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tree uh and a shocking turn of events a
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leaf has fallen from a tree in the local
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park Witnesses report that the leaf
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which was previously attached to a
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branch of a tree attached itself and
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fell to the ground very dramatic so you
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can see that this is a pretty remarkable
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system and it is what we call a language
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model uh because it um it models the
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sequence of words or characters or
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tokens more generally and it knows how
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sort of words follow each other in
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English language and so from its
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perspective what it is doing is it is
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completing the sequence so I give it the
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start of a sequence and it completes the
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sequence with the outcome and so it's a
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language model in that sense now I would
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like to focus on the under the hood of
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um under the hood components of what
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makes CH GPT work so what is the neural
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network under the hood that models the
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sequence of these words and that comes
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from this paper called attention is all
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you need in 2017 a landmark paper a
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landmark paper in AI that produced and
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proposed the Transformer
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architecture so GPT is uh short for
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generally generatively pre-trained
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Transformer so Transformer is the neuron
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nut that actually does all the heavy
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lifting under the hood it comes from
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this paper in 2017 now if you read this
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paper this uh reads like a pretty random
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machine translation paper and that's
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because I think the authors didn't fully
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anticipate the impact that the
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Transformer would have on the field and
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this architecture that they produced in
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the context of machine translation in
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their case actually ended up taking over
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uh the rest of AI in the next 5 years
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after and so this architecture with
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minor changes was copy pasted into a
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huge amount of applications in AI in
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more recent years and that includes at
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the core of chat GPT now we are not
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going to what I'd like to do now is I'd
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like to build out something like chat
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GPT but uh we're not going to be able to
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of course reproduce chat GPT this is a
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very serious production grade system it
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is trained on uh a good chunk of
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internet and then there's a lot of uh
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pre-training and fine-tuning stages to
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it and so it's very complicated what I'd
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like to focus on is just to train a
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Transformer based language model and in
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our case it's going to be a character
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level language model I still think that
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is uh very educational with respect to
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how these systems work so I don't want
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to train on the chunk of Internet we
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need a smaller data set in this case I
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