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WEBVTT
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And we will conclude our expedition into the world of frontier models through their chat interface by
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looking at meta AI and perplexity.
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Meta AI is, of course, the front end version to llama that's running behind the scenes.
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We can ask it the same question about how does it compare itself to other models, and we'll get back
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something that has some strengths and weaknesses.
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It doesn't do a great job.
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It gives some rather old fashioned complimentary llms, but it's it's okay.
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And generally speaking, I think you'd find asking various questions that you'll get answers that are
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okay, but not the same power as some of the others.
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Let's ask the same question.
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You guys are going to be fed up with me for doing this, but how many times does the letter A appear
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in this sentence?
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And let's see what we get from meta AI.
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It appears five times, so meta is also not able to handle that particular question.
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Now, one thing that the meta is able to handle is image generation.
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And we can say please generate an image of a rainbow of rainbows
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leaping from Hawaii to 17.
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Uh, and you'll find that this is the kind of, of challenge that, uh, lama is up for.
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And it very nicely does it with these four possibilities.
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And you get this, uh, this kind of effect.
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And it seems to have, uh, well, Hawaii has appeared, uh, but but some of these are very respectable,
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particularly for the open source model that is, uh, Lama sitting behind the scenes.
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All right, let's flip over to perplexity, which is, of course, a search engine, not an LLM.
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So it doesn't.
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It's the odd one out in this group, although actually, uh, OpenAI also is now in the search space,
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too.
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Um, so really it's looking for, uh, factual questions that it can then research and provide an answer
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for.
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And I'm recording this on November the 6th, the day after the elections in the US.
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So I can say something like, who is the president elect of the United States, and it will do some
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thinking.
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And I would not be surprised at all to see that it's able to summarize back the outcome and give key
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points, reactions and the like.
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Uh, and so it's able to do this and provide a nuanced, well crafted response to current events.
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Actually, if you ask a question like that to, uh, OpenAI to GPT right now, it will also give you
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a good answer, uh, based on current events, despite its knowledge cutoff being last year.
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But if you ask Claude, it won't be able to do that.
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And it will say it will say to to be direct.
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My knowledge cutoff is, uh, you get that very specific answer.
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Uh, let's ask the question, uh, how many?
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Let's start a new, fresh chat and say, how many times does the letter A appear in this sentence?
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It's the last time you have to see this.
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Uh, and it says four times.
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So it is able to count.
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Uh, so it's impressive.
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Uh, don't know whether it's a coincidence, whether it's because other people have written articles
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about this that it's found, but it is able to count for times.
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So perplexity is with the oh one preview version and being able to get this right.
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Congratulations to perplexity.
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Um, and now ask a slightly curious question, which is, ah, uh, question about comparing to other
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models, and you'll see a, um, here's the response.
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Uh, the area is indicated by perplexity.
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I don't have the capabilities.
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So it definitely pushes back firmly on that.
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And that is a wrap on our exploration of frontier models.
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But now I encourage you to do the same.
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Come up with interesting questions, particularly try and find questions which are able to bring to
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the surface the differences between the models, their characters, what they're good at, where they're
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weak.
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And if you find something good, then please share it with me or post it in messages.
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Uh, this is it's really great to find the kinds of prompts that help to surface these differences,
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and also that help to highlight where they are so strong.
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And I will see you in the next video to wrap this up.