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← People and their mental models

Aravind Srinivas's mental models

4 claims Aravind Srinivas made fit 4 mental models. Most often: Bottlenecks, Design is how it works, Incentives. Everything they said here.

Models we see in what they say

Our reading: their claim applies the idea without naming it. The claim is theirs; filing it here is ours.

Bottlenecks

A system moves only as fast as its narrowest point; speed up anything else and nothing changes.

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The obstacle to search is not the competition but the fact that people are not naturally good at turning curiosity into a question.

  1. Aravind Srinivas Co-founder and CEO of Perplexity, an AI answer engine There is a skill to asking good questions, and everyone’s curious though. Curiosity is unbounded in this world. Every person in the world is curious, but not all of them are blessed to translate that curiosity into a well-articulated question. Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet | Lex Fridman Podcast #434youtube.com · 19 Jun 2024 · 0:41:07 into the videoAll korrents from this video
    There is a skill to asking good questions, and everyone’s curious though. Curiosity is unbounded in this world. Every person in the world is curious, but not all of them are blessed to translate that curiosity into a well-articulated question.

Design is how it works

Judge a design by what it does for the person using it, not only by how it looks.

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Prompt engineering is not a durable skill, because a good product is one that works for the user who never learned to phrase a question.

  1. Aravind Srinivas Co-founder and CEO of Perplexity, an AI answer engine And also this is where I believe the whole prompt engineering, trying to be a good prompt engineer is not going to be a long-term thing. I think you want to make products work where a user doesn’t even ask for something, but you know that they want it and you give it to them without them even asking for it. Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet | Lex Fridman Podcast #434youtube.com · 19 Jun 2024 · 0:39:20 into the videoAll korrents from this video
    And also this is where I believe the whole prompt engineering, trying to be a good prompt engineer is not going to be a long-term thing. I think you want to make products work where a user doesn’t even ask for something, but you know that they want it and you give it to them without them even asking for it.

Incentives

Look at what people are rewarded for; it explains more behaviour than what they say, your own included.

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Google's weakness is its own margins: it cannot go aggressively after anything less profitable than a link click, which is exactly where a challenger should attack.

  1. Aravind Srinivas Co-founder and CEO of Perplexity, an AI answer engine What is the weakness of Google is that any ad unit that’s less profitable than a link, or any ad unit that kind of disincentivizes the link click is not in their interest to go aggressive on, because it takes money away from something that’s higher margins. Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet | Lex Fridman Podcast #434youtube.com · 19 Jun 2024 · 0:26:05 into the videoAll korrents from this video
    What is the weakness of Google is that any ad unit that’s less profitable than a link, or any ad unit that kind of disincentivizes the link click is not in their interest to go aggressive on, because it takes money away from something that’s higher margins.

Trade-offs

Every choice gives something up, so name the cost; and check, because some trade-offs everyone assumes are not real.

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Every announcement of a longer context window hides the cost, which is that the model gets worse at following instructions.

  1. Aravind Srinivas Co-founder and CEO of Perplexity, an AI answer engine So most people, when they advertise new context window increase, they talk a lot about finding the needle in the haystack sort of evaluation metrics and less about whether there’s any degradation in the instruction following performance. So I think that’s where you need to make sure that throwing more information at a model doesn’t actually make it more confused. Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet | Lex Fridman Podcast #434youtube.com · 19 Jun 2024 · 2:48:23 into the videoAll korrents from this video
    So most people, when they advertise new context window increase, they talk a lot about finding the needle in the haystack sort of evaluation metrics and less about whether there’s any degradation in the instruction following performance. So I think that’s where you need to make sure that throwing more information at a model doesn’t actually make it more confused.