Pioneers: A roundtable on Richard Hamming

Notion Pioneers
18 Mar 202151:41

Summary

TLDRこのトークでは、DevinがAndy Matushak、Star Simpson、Michael Nielsenと共に、科学と工学におけるエクセレンスを追求することの意味について議論しています。Hammingの著作「The Art of Doing Science and Engineering」を基に、参加者は卓越を追求することの重要性、問題解決と問題発見のアプローチ、研究文化に対する硅谷の反応、そして感情的な関与が革新的な発展にどのように影響するかについて意見を交わしています。

Takeaways

  • 🤔 研究とは、問題解決と発見の過程であり、卓越性を追求することが重要である.
  • 🚀 ハミングは、科学や工学の分野で卓越を追求するための具体的なアドバイスを提供している.
  • 💡 問題解決の過程は、単に数式を解くことだけではなく、意味のある人間の問題を解決することにも関わる.
  • 🌟 卓越性を達成するためには、自分自身の信念と闘い、自己の思考を深める必要がある.
  • 🛠️ 研究では、自分自身の環境や状況を整え、それを有利于にすることが重要である.
  • 📚 ハミングの著作は、研究文化を説明しており、実践的なアプローチがSilicon Valleyの文化に響いている.
  • 🔮 未来の予測は、大胆な行為であり、長期的な視野を持つことが重要である.
  • 🧠 コンピューターの進化は、数値計算から意味のある問題の解決へと進化していると予測された.
  • 💭 情熱的な関心を持つことは、革新的なブレークスルーが生まれる原因であるとハミングは主張している.
  • 🤖 AIの未来について、自分の意見を形成し、他人の結論を繰り返し言うのではなく、自分自身の思考を更新することが重要である.
  • 🌐 競争は生産性を持たせることがあり、しかし適切な競争のバランスを見つけることが重要である.

Q & A

  • アニディはどのようにして、最高のエクセレンスを達成するために努力するべきかを説明しましたか?

    -アニディは、基本的な現実のプロパティをより正確に理解し、その知識を他人と共有することが重要だと述べています。卓越を追求する意欲を持っているからです。

  • スターとアンディは、ハミングの考え方の中で最も興味深い部分は何ですか?

    -スターは、ハミングが明確な思考者でありながら、自己認識とコミュニケーションにコミットしているという点が魅力的だと感じています。一方、アンディは、ハミングが自分のプロセスと周りの偉大な人々のプロセスを共有するようにすることで、彼自身と共有するという点に興味を持っている。

  • ハミングが言及した「小さなノーベル賞」の概念とは何ですか?

    -「小さなノーベル賞」とは、哈明が提唱した生産性メトリックスであり、小さなが意義のある重要な洞察を指します。これは、彼の目標として提唱され、彼は自分の生産性をこの率で測るように提案しています。

  • ハミングの「ドアを開ける」のアドバイスは、どのように役立つか?

    -ハミングは、ドアを開ける頻度について具体的に言及しており、これは個人の生産性に影響を与えることがあります。ドアを開けることで、他人とのコミュニケーションやフィードバックの機会が増え、新たな知見やアイデアの獲得につながる可能性があります。

  • ハミングは、自己学習と環境構築の重要性を強調していますが、これはどのように実現するべきですか?

    -ハミングは、過去の偉大な発見者や研究者たちの研究プロセスを分析し、自分の環境をそれらに合わせて構築することが重要だと述べています。具体的には、自分のドアを開く頻度や、ビッグピクチャを考える方法、新しい分野にどのように取り組むかなど、様々な要素を考慮に入れて環境を整えることが重要だと提案しています。

  • ハミングが言及した「システムエンジニアリング」とは何ですか?

    -「システムエンジニアリング」とは、複雑な問題を解決するために必要なプロセスや技術を考案し、システム全体を構築する作業です。ハミングは、システムエンジニアリングにおいては、問題解決に必要な様々な要素を考慮し、最適な解決策を見つける必要があると述べています。

  • ハミングの「感情の深い関与」という考えは、どの程度当てはまるか?

    -ハミングは、革新的なブレークスルーは深い感情的関与から来ることが多いですと主張しています。これは、自分自身の研究や仕事に対して強い情感を持っていることで、より創造的で深い洞察力を持つことができますという考え方です。ただし、感情が過度に関与することで、仕事に悪影響を及ぼす可能性もあるため、適切なバランスが必要です。

  • ハミングの未来予測について、どのようなものですか?

    -ハミングは、コンピュータが単に計算機として使用されるわけではなく、最終的には重要な人間の問題を解決するために使用されるという未来を予測しています。また、50年後の世界についても予測しており、その大胆な予想は彼の計算が正確であることを示しています。

  • ハミングが提唱した「問題解決」のアプローチと、「問題発見」のアプローチの違いは何ですか?

    -「問題解決」のアプローチは、既に定義された問題に焦点を当て、解決策を探る方法です。一方、「問題発見」のアプローチは、新しい問題を発見し、未知の分野を探求する方法です。ハミングは、後者のアプローチにおいて、より創造的で意義深い活動であると述べています。

  • ハミングの本の中で最も強調されたことは何ですか?

    -ハミングの本では、一生懸命働くこと、問題に興味を持ち、最も賢い人々と共に重要な問題に取り組むこと、そして自己学習と環境構築の重要性が強調されています。

  • ハミングは、研究文化についてどのように述べていますか?

    -ハミングは、研究文化を実践的で、問題解決に役立つツールや環境の構築を重視する場所であると述べています。彼は、研究者が自分のプロセスや周りの偉大な人々のプロセスを共有することが、最高の仕事を行うために必要なと信じています。

Outlines

00:00

📘「科学と工学の芸術」に対する視点の紹介

デヴィンが友人アンディ、スター、マイケルを紹介し、彼らが関わるプロジェクトと経歴について語る。彼らは「科学と工学の芸術」について語り合い、その本から何を学び、どのように異なる解釈があるかを探求する。彼らは、ハミングの「卓越性」に対する定義と、それが個々にとって何を意味するかを議論し始める。

05:02

🔍卓越性への追求と世代間の視点

アンディ、スター、マイケルは卓越性とその追求についてのハミングの見解を掘り下げ、今日の社会におけるその概念との対比を考察する。彼らは、以前の世代が卓越性をどのように見ていたか、そしてそれが現代の文脈でどのように変化したかについて意見を交わす。

10:04

🤔ハミングの独創性と科学コミュニケーション

ディスカッションはハミングの独創性と、彼がどのように科学とコミュニケーションを統合したかに移行する。彼の自己認識の重要性と、彼がいかにして自分のプロセスと周囲の偉大な人々のプロセスを共有することに専念したかについて話し合う。

15:04

📈競争と知識の積み重ね

議論は競争の価値と、それが個人の成長と知識の積み重ねにどのように影響するかに焦点を当てる。彼らは、競争がいかにして自分自身を超えるための刺激となるか、または逆に生産性を阻害するかについて意見を交わす。

20:05

🌟新たな問題と分野の発見

話題は新しい問題と分野を発見する方法へと移る。彼らは、既存の問題を解決することと、まだ誰も考えていない問題を発見することの違いについて議論し、どのようにして新しいアイデアや分野を探求するかについて意見を交わす。

25:06

🚀ハミングの問題発見法とノーベル賞

最後に、彼らはハミングの問題発見法と彼の「マイクロノーベル」概念を探る。ハミングがどのようにして意義深い洞察を見出し、科学界での彼の影響をどのように評価するかについてディスカッションが展開される。

Mindmap

Keywords

💡エクセレンス

エクセレンスとは、最高の品質や性能を追求することです。このビデオでは、ハミングが求めるエクセレンスについて語されています。彼は、根本的な真理を理解し、それを他人と共有することに興味を持っています。また、この概念は、参加者が自分の仕事や人生に適用し、優れた成果を出すことを意味しています。

💡システム工学

システム工学は、複雑なシステムを設計、開発、および管理する際に使用される方法論です。このビデオでは、ハミングがシステム工学の重要性について説明し、科学やエンジニアリングの分野で成功するために必要なスキルと手法を探求しています。

💡問題解決

問題解決は、起きた問題に対処し、解決策を見つけることです。このビデオでは、参加者が直面した課題や問題对他们如何解决について議論し、そのプロセスを通じて成長と学びを促すことが強調されています。

💡研究文化

研究文化は、研究を通じて新しい知識を発見し、進歩を遂げるために必要な価値観や行動規範のセットです。このビデオでは、ハミングが提唱する研究文化について語られ、その文化が科学の進歩にどのように貢献するかが説明されています。

💡自己評価

自己評価は、自分自身の能力やパフォーマンスを客観的に評価し、改善点を特定するプロセスです。このビデオでは、ハミングが自己評価の重要性を強調し、それは個人の成長やキャリアにおける成功に不可欠であると述べています。

💡感情的関与

感情的関与とは、自分の感情や情熱を問題やプロジェクトに注ぎ込むことです。このビデオでは、ハミングが感情的関与の重要性を強調しており、それは創造性やモチベーションを高め、問題解決に役立つと述べています。

💡競争

競争とは、同じ目標を追求する個体やグループが互いに対抗することを指します。ビデオでは、競争が個人の成長や成功にどのように影響するかについて議論されており、適切な競争は刺激的であり、ただし過度になると問題を引き起こす可能性があると指摘しています。

💡オープンサイエンス

オープンサイエンスは、研究やデータが公開され、誰でも利用できることを目的とした運動です。ビデオでは、オープンサイエンスが科学の進歩にどのように貢献するかについて説明されており、共通の知識や発展を促進することが重要であると強調されています。

💡問題発見

問題発見は、新しい問題を特定し、解決策を探るプロセスです。ビデオでは、問題発見が科学や技術の進歩において重要な役割を果たすことが強調されており、未知の領域に興味を持つことで革新的な発展が期待されます。

💡コミュニケーション

コミュニケーションは、情報や考えを他者と共有する行為です。ビデオでは、コミュニケーションが問題解決や創造性にどのように重要であるかについて議論されており、適切なコミュニケーションはチームワークやプロジェクトの成功に不可欠であると述べられています。

💡未来予測

未来予測とは、将来の出来事を予測し、準備をすることです。ビデオでは、ハミングが未来のコンピューター技術の発展を予測し、その予測が実際に起こったことについて説明されています。この能力は、科学的進歩や革新的な発展を促すために重要です。

Highlights

The importance of pursuing excellence in one's work and the unabashed nature of this pursuit as described by Hamming.

Hamming's specific definition of excellence as understanding and sharing the fundamental properties of reality more accurately.

The contrast between Hamming's earnestness and the irony-laden society, highlighting the rarity of serious discussions about excellence.

The observation that past generations may have been more open about expressing interest in excellence, but not necessarily more interested.

Hamming's uniqueness as a thinker, his self-awareness, and his commitment to communicating his observations and processes.

The importance of studying the discovery process of great minds and the context that enables insights, as advocated by Hamming.

The challenge of discerning the true factors behind success in biographies and the value of learning from people doing good work firsthand.

The idea of scaling learning experiences beyond personal connections, such as through live streams and observing real-time work.

Hamming's blunt advice on work habits, like how often to have one's door open, to balance individual work with collective goals.

The anecdote about John Tukey and the importance of hard work, as well as the compounding nature of knowledge.

Hamming's emphasis on the need for continuous self-reflection and updating one's thinking to stay ahead in the field of AI.

The discussion on the productive and toxic aspects of competition, and the value of finding unique, meaningful problems to solve.

The significance of problem discovery versus problem-solving in scientific research and the importance of creating new fields or sets of problems.

Transcripts

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hello i'm devin and today i'm joined by

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three good friends

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andy matushak star simpson and michael

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nielsen

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andy's a software engineer designer and

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researcher and he works on technologies

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that expand what people

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think and do star is a hacker and

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founder

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she's working on a company called their

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craft which uses autonomous

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aircraft to enable air freight logistics

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michael is a scientist who helps pioneer

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quantum computing

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and open science movement his focus is

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on ideas and tools that help people

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think and create

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both individually and collectively so

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today we're here to talk about one of

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our favorite books the art of doing

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science and engineering and i'm really

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excited because we're all good friends

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but we also haven't talked that much

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about this particular book together

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so we're going to have a lot of fun

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diving into

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into this book what it means to us and

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ideally where we disagree on the

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interpretation too so

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for starters in the art of doing science

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and engineering

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the author hamming puts forth a

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transcendental narrative

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he answers the question of what matters

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and something

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that i've heard andy say is that

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hamming's religion is the unabashed

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pursuit of excellence so what does

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excellence mean to hamming and what does

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it mean to you

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hamming has a really specific definition

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of of excellence

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he's interested in people understanding

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fundamental properties of

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reality uh more accurately and and

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sharing that knowledge with others

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one of the things that i think is most

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interesting about his view is it's not

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even so much

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uh excellence or or what he means by

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that but the unabashed

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side of it i think it's really

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interesting to read this book in 2020

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an irony laden society or something like

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that uh the kind of like earnestness

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uh that he brings to his narrative is

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really interesting to me yeah he's

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he's like well of course you want to do

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great things and

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since you naturally want to do great

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things uh you know here are some

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considerations

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i think it stands in really stark

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contrast

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a lot of stances these days

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where i i think it's difficult to talk

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pursuing excellence seriously and not

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either come off

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as delusional or as like

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self-aggrandizing or

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arrogant or just out of touch or

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something like that and so i i enjoy

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that part of it

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what's changed well hamming was part of

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a generation

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that i think took kind of a shared

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project

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of progress and understanding

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very just among scientists but even

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society

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kind of grand projects of the mid 20th

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century

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counterculture movements i i'm

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spitballing here

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and grunge and

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generation x uh um kind of

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stereotypical cynicism perhaps or eroded

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some of this i i guess i'm not really

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sure i'd be curious what others think

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well i think hamming was kind of a rare

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person

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uh and it's not just that he was this

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very clear thinker uh he

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also had a lot of self-awareness which

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is

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very unique quality in any person and

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furthermore was committed to

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communicating about it

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right so like each of those things like

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himself being an astute observer

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and you know being uh self-aware about

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what

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you know what worked to enable that and

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also

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being committed to communicating to

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others i think are the things that make

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hamming you know so unique and his

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writing so unique and so genuine

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yeah my my instinct is that there's

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there are a lot of people who are

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very good at science and there are also

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a lot of people who are very uh

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interested in communicating about

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science

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but the the overlap isn't necessarily

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particularly strong

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it felt like with hamming he had these

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amazing discoveries did

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great mathematics and then he said wow

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this is so great that i have to share

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both this work and also my process and

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the process of great people around me

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with people as opposed to sort of

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communicating about science for

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science's sake

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yeah and he was right about you know his

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ideas but he was also right about

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you know what are the right things to do

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uh

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it all stacks up you know in such a such

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a unique way such an interesting way

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it's uh

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it's great i think that he didn't just

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give us the artifacts of his

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concepts but also gave us you know what

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he had studied along the way

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uh to become a person able to discover

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concepts that's what i love about the

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book

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michael what do you think made hamming

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special can i come back

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uh to andy's uh comment i want to

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disagree completely

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um which is very unusual for me yeah

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andy made this comment

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essentially i i would say it's almost

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sort of a nostalgic comment

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about maybe past generations being more

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interested in excellence

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i don't think you can conclude that from

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hamming at all hamming was at the 99.99

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percentile of being interested in

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excellence for his own generation

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i'm not sure you can actually infer very

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much about what was typical for people

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yeah i think that's

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i think that's fair i i think it's not

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so much that prior generations

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i think were more interested in

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excellence necessarily but rather that

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um i think it was more okay to express

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an interest in excellence

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i don't think that's true either um you

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know if you walk into a bookstore which

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of course you can't do at the moment

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you know there'll be like masses of

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shelves that are basically about nothing

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but the pursuit of excellence

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in a whole lot of different ways um and

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so

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yeah and i mean they're routinely some

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of the highest selling

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uh books i mean some of them are not

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framed as excellent exactly

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you know being becoming a millionaire

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next door or something like that isn't

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quite about that but there's certainly i

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don't know the seven habits of highly

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effective people and there's like a

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thousand

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titles like like that and they sell

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millions of copies

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so i think people are pretty interested

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and they're pretty willing to

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to accept it hamming i do think was

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a little bit unusual in you know he has

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this very precise articulation

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saying that even though a lot of people

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are sort of nominally interested in this

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they don't actually necessarily take the

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specific actions

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uh to act on it he makes this comment

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about going and talking to some of the

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other scientists

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at some of the you know at the lunch

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tables and saying you know

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what are the important problems in your

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field and some of them saying well

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i don't really know and even if they did

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know

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you know why you're not working on them

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and um

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discovering that this made him

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apparently at least some of the time not

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a very popular lunch companion

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and that's i think that's pretty

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interesting uh it might be a constant

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between his time

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and our time i'm not not sure but uh

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it's certainly an interesting

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observation i think that really speaks

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to kind of

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what amazes me is the nuts and bolts

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level of detail about his advice

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can you give us another example well you

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know as contrasted to

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self-help or self-improvement guidebooks

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i think

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hamming doesn't put it in the spirit of

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like like if you just drank a few more

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glasses of water every day you'd like

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think more clearly

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he really lays out that like it's hard

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work

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and the thing you need to do more of is

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work right

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and talk to people he advocates a

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program of like studying

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past uh eminent discoverers and trying

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to like piece apart

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what their discovery process had been

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for instance like

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uh what prior knowledge allowed them to

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like make that insight what was it about

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their context or their environment that

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enabled that

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and then trying to like shape his own

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environment around that so thinking very

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carefully about you know

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when and how often to have one's door

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open uh how to

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piece apart one's work and to kind of

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thinking big picture versus like

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you know working on very tactical tasks

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how to look at a new field that's

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emerging uh

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and kind of decide when to when to like

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jump into it

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uh he advocates like thinking very

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carefully about all of these things

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i i think that's very much right but i

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also also think it's quite challenging

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to actually

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study the context that somebody is in so

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there's no lack of

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biographies out there and histories but

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i always

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have this nagging sense when i read a

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biography that it's just a just so story

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and you're not actually learning much at

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all about what really mattered for

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having this person succeed sometimes

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it's partially about

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motivations like people want to tell a

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different story that and make it a

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little bit smoother because it's cleaner

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sometimes it's just people forgot the

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details and it just didn't really come

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up or didn't seem relevant to the author

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but i found personally that like i

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started

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i've been reading fewer and fewer

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biographies in my life and just trying

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to spend time with people who i think

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are doing good work

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because then you can actually see it

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firsthand what it is that enables them

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to do that and like what their their

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patterns of thought are um but that

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means you have to like be around

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certain types of people and like this is

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one of the reasons why i love being

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friends with people like you

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um but how can you scale that beyond

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just

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becoming friends with people okay like

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what in particular devin

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scaling what experience let's say in

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high school um

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i i did not have access to the kind of

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friends that i have now

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i didn't know twitter existed i didn't

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have the email etiquette that i now have

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i didn't live in san francisco i didn't

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have a driver's license i couldn't get

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to the people i wanted to get to

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and so i i was kind of stuck with

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reading biographies

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and so like how how would a 14 year old

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get

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more of this context so that they can

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start learning as opposed to having to

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be

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in their 20s and living in a great city

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or a great

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like university something that that is

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certainly

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yeah a lot of fun is uh uh you know

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watching sort of

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twitch live streams of people doing

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interesting things uh because you know

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you're not actually getting their kind

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of

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reconstructed just those story about how

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it is they did what they did

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no you're actually seeing them do the

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thing

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maybe sort of an even more fun uh

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example in some ways

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i mean you can you can do this um sort

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of

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i mean with anything that you can see

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done for sort of live action

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um uh i'm trying to think of what's the

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name of the the greatest sneaker player

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in the world

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ronnie o'sullivan um you know he claims

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that he put himself to play snooker

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basically by watching videos of uh the

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previous best player in the world

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uh steven hendry uh and just

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imitating him at the age of 10 11 12

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and that's pretty cool that he can sort

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of do that you know self tutorial

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uh uh sort of just by searching out well

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searching out video

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and and watching

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so i guess the takeaway is that more

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scientists should be on twitch

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actually so i i know somebody uh who was

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at stanford uh

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who did live stream in fact they're you

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know a substantial chunk of their phd

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um uh which i thought was pretty great

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um

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and there's yeah there's other things

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there's a company what is it called

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uh jove the journal of visualized

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experiments

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who will send a camera crew to your lab

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uh and actually show you you know

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actually video you

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as you know you arrange i don't know

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what

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what you do you know arrange the perfect

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in just the right way to do the

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you know the procedure um i think that's

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i don't know

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it's pretty interesting like you kind of

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just learn stuff by seeing people do

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things

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uh for real in a way that you can't

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learn from

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i i sort of i don't entirely agree with

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you about biographies

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but there is definitely a lot left out

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there are good biographies but it's

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really hard to know

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if it's true or not and i think

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biographies for me

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serve more as sort of inspiration of

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people doing great things

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and i just get really excited about

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doing things in the world when i read

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biographies

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but it's less of a manual about how to

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um usually

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um i find often interviews like

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especially less

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um like highly edited interviews are

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often good for

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for getting uh somewhat

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less just so stories i mean of course

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you'll still get them but sometimes

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you'll get these little

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these little gems where the interviewer

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was like how did you think to do that

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and the person was like well

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you know i i just encountered this other

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person who was doing this thing

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um it's kind of similar to the twitch

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vibe where you kind of like

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you see how the stumbling happens i

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think another dynamic

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you see in biographies is there's often

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selection for people who have become

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fairly you know noteworthy for whatever

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reason and there's a subtle

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effect where when you're you know

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whatever you want to call it senior

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um often folks end up with

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others sort of working under their name

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you know doing a lot of the

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the gumshoe work you know and so i've

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seen a lot of

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biographies i don't want to single

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anyone out particularly but i am

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thinking of one where

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in the beginning this guy was like i you

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know i had to get a like medical

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exemption so they didn't send me to war

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and so i threw the paperwork off the

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side of my motorcycle and like ran over

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it a few times to make it look

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you know whatever it's like very

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tactical you tactile

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as well and you know then by the end of

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it he's like yeah and then um

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we invented you know and he's really

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kind of encompassing a few hundred other

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people

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when you know with that we but like you

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know he you sort of

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you get the sense that as much as the

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vision never faded

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um that person stopped having their

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fingers you know in the

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in the paint um and and hamming's book

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is again like particularly noteworthy

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because he's so

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blunt about the requirements

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what's the more examples of the

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bluntness class this is referencing what

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andy mentioned earlier

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where he goes into detail about you know

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how often to have your door open you

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know to acknowledge

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very specifically some people can get

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more work done with their doors closed

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however

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they're more likely to diverge away from

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doing like what we collectively think

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is like useful and interesting that's

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just tactical like

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and that's also like a very interesting

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thought it's not an idea that i

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really heard anybody else address like

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to the extent i thought of it on my own

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it was really just sort of like

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wandering off in my head and it's like

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not the kind of thing i would imagine

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being able to sort of like

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air in a workbook not the average

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workplace of like you know so how often

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should i have my door open in order to

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be most productive it's not like a

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not a thing that question you know and

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like and then he just went and wrote it

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down i enjoy the um

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uh he refers to john tukey uh quite

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frequently

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uh and there's also kind of a similar

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slightly in-your-face quality about some

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of those references

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you can see you know when he was

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referring to somebody like shannon who

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was a little bit older

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you know he admired him but he didn't

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really view him as a peer and so it was

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kind of more of a

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almost sort of a mentor yo or somebody

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who he looked up to

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but tuki was about the same age and you

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could see

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that he felt competitive with dookie and

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a little bit jealous that tsuki was so

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good

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and you know there's i don't know just

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all that that sort of the

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discussion of you know what made took

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you so good

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and uh there's a a great moment sort of

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i think in much the same vein

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of just uh i think he goes to talk to

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his boss

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and he complains how can tooky know so

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much and his boss

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leans back in his chair and says uh you

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too would be surprised if you worked as

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hard as john tsuki how much you know

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like okay right he makes this great

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point from that

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about kind of the compounding nature of

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knowledge

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and that you know kind of small marginal

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investments may return

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i i'll show like one other kind of blunt

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thing i really enjoyed it

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i left all the instances where we kind

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of complained about his own failure um

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and and he has a couple actually where

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he talked about essentially

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he was going with cached thoughts like

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he had come to some conclusion

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about uh i think his digital filters uh

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based on some

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like prior nature of the field and so he

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missed

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um this opportunity that one of his

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colleagues

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uh ended up pursuing uh rather than him

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and he felt kind of frustrated about

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that like i should have gone after that

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and the reason that i didn't was that

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i'd already decided that that approach

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wasn't gonna work and so when the

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situation on the ground changed

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uh he didn't reconsider and uh he kind

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of

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exhorts the readers in the in the ai

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chapters

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uh for instance that you know almost

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everybody who's kind of talking about

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the future of ai's

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is just kind of repeating other people's

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conclusions you need to like

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sit and like do your own thinking and

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update your thinking and otherwise

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you're gonna have no idea

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uh what's what's gonna come i really

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liked that

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example of the feedback about john tukey

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working just harder

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than hamming what was a time in your

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careers that

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someone gave you pretty harsh advice

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like that where you're like oh man

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i really gotta think about this uh i

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i've got one that

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um it was harsh in it in a in a subtle

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way

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but it still like really

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uh kicked me quite hard uh i was

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supposed to be responsible for um this

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particular gesture interaction

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uh on ios and

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you know i'd been working on it for a

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while and it still wasn't feeling quite

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right

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it was like triggering at the wrong

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times and

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after a conversation with my manager

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about

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possible approaches you know we kind of

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come up with some ideas and i said

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you know i'm gonna pursue these over the

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next coming days and

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you know he was clearly kind of

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interested in seeing if we could make

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progress a little faster

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but you know i went home uh it was you

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know maybe 7 30 or something

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uh so i get in the next morning and he'd

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been there

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like most of the night uh and when i got

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there the problem was basically solved

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uh

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and uh uh

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there there was no like criticism really

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about not having

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carried it forward quite so aggressively

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uh

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but uh arriving and having the problem

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that i'd been wrestling with for quite

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some time

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kind of just solved uh for me was a

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a good kick you never forget that

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feeling when it happens i

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i associate a couple of those with my

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peers in high school

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um my best friend in high school and i

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were like extremely competitive with

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each other

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it was probably the most competitive

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relationship you could have with someone

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and still consider them your friend and

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sometimes it did break down

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it didn't help that my high school was

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tiny and we were like the

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two you know we had to be you know we

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both had these personalities we had to

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be the best and everything

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but then by you know the end of high

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school you know i was in a calculus

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class of four people

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it was her and me and like two two

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others you know and like

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it got it got very narrow at times um

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but i just like

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you know as hard as it was sometimes i

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still really

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miss how intense it was

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because it was great i mean we went to

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school for six years and we were just

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like

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you know in every way wherever possible

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toe to toe

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you know it was great when is

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competition productive and when is it

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more toxic i think i deny the premise of

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the question

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toxic uh no okay all right let me

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let me lean into the question let me let

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me accept the remnants of the question

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um uh

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i mean you can probably all guess that

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maybe people listening to this can't

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my opinion um mostly you know if you're

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on sort of a linear scale

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like get off the scale uh go and do

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something else

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um you know i really enjoy

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uh watching actually sport of all kinds

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like i love

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you know watching people play tennis i

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enjoy athletics and whatnot

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uh and so i'll admire serena williams

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or usain bolt or whoever is just

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wonderful

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but it's also true that if you know

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serena stopped there would be a second

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best player in the world

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uh who would take her place uh actually

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i guess it kind of has been over the

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last few years but over the last 20

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years

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she's been by far in a way that the best

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player

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um and so no it always strikes me

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uh somehow you know if there's a

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thousand people all competing to do the

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same thing

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actually probably a lot of them could go

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and do other things they could invent

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other games

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uh to play uh some of which would be

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unique games games that only they

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in the world were playing uh and it

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would be both more meaningful that for

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them it would be more meaningful for

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their family and for their friends um uh

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and just better for the world if they

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were to go and do those

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those other things um so i don't know

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competition

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is uh sometimes good

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for motivating you but i think you

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always want to be in sort of a pool

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small enough but it's

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actually to some considerable extent

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friendly competition

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um and you don't feel that the kind of

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hate

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is when you're getting crowded out and

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there's like 17 people

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all trying to do exactly the same thing

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and it doesn't even feel that important

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anyway

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um because in fact you know there's kind

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of just too many people

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trying to do the same sort of thing

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that's that's that's sort of the toxic

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version

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uh i'd rather just you know go and find

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uh

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uh ideally incredibly meaningful and

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important things that you can do

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that way you're the only person or one

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of a tiny number of people who are

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pursuing that end

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that's my way nothing about competition

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it's not a very hemingway i don't think

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i think he was a more competitive kind

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of a person he wanted to win

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uh quite often even his framing of

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you know asking what are the most

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important questions in your field what

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are the most important problems in your

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field and why are you not working on

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them

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um that seems to me like kind of a silly

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framing it's accepting the consensus

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social reality of what the field is

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when in fact it is much better very

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often uh to figure out what are the

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problems

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that nobody in your field has even you

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know has understood are important yet

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um sort of trying to invent new problems

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and maybe even new fields

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um that sort of strikes me as just a

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more enjoyable and ultimately more

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meaningful

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activity

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if one is trying to find a new field or

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at least find a new set of problems

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what should they do differently from

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what hamming recommends that they do

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so some researchers they find a problem

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and the goal is to solve that andrew

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wile's working on gemar's last theorem

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he knew what the theorem was and that

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was very much the objective

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and so you're always trying to find

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little ways of like you know how can i

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get just a little bit more insight in

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this direction that direction or whatnot

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and people who do uh problem discovery

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or even field discovery

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i think operate really in quite a

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different way um

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they are exploring in a general

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direction they're trying to find

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little bits and pieces of insight they

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have some instincts that there's some

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big problem

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over in this general direction um i

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think

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maybe a good example is um somebody like

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uh turing

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in sometimes he was actually kind of

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working on a particular problem it was a

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fairly esoteric logic problem that david

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hilbert

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had posed um in some sense he couldn't

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work on the problem

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of discovering universal computation

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because nobody had said what universal

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computation was

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the the the genius in that paper uh

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isn't uh proving that the whole thing

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problem is unsolvable which is often

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how it's framed it was inventing the

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concept of universal computation

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um and almost by definition that that's

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not a

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that's not a problem uh uh yeah that is

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a problem that is only evident

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after the fact that that's very often

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the the

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case in in science that the most

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interesting discoveries

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uh not discoveries you know not not

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solutions to problems but rather

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actually

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identifying that there is a new concept

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a new type of thing

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in some particular direction and

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and that's something that proceeds i

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think much more based on sort of

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instinct

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uh uh an intuition where you're like

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there is something here

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and i can sort of very vaguely see the

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outlines of it

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you kind of just keep chiseling away

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chiseling away chiseling away trying to

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see if there's something actually there

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and probably 99 times out of 100 it

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turns out it was a mirage and there is

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nothing there

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and then you know very occasionally

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somebody discovers

play24:19

something like the notion of universal

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computation um and really the problem

play24:23

that turing was working on was always

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incidental to that um you know it's

play24:28

wonderful

play24:29

that he discovered universal computation

play24:30

out of it and

play24:32

the solution to the problem is like a

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nice it was kind of it was a way of

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getting there it was almost an excuse a

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provocation for getting there

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i have a question for you michael you're

play24:43

gonna talk more now

play24:46

okay which do you think is the better

play24:51

problem discovery question of the

play24:55

questions posed which are either

play24:58

what are the most important problems in

play25:00

your field or

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what are the that you know that others

play25:03

are thinking about or what are the most

play25:04

important problems in your field that

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nobody's thought of yet

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which do you think would be the better

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problem discovery

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question to ask better being you know

play25:12

more productive more likely to turn over

play25:15

actually i think it's it's probably

play25:17

mostly um

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to some extent it's a it's a question of

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what your personality is i'm

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not sure you even actually get to decide

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um

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and and to something that all i'm doing

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is relaying my own personality

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um i just don't really like working on

play25:32

fixed problems or i like having sort of

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a list of 100 or well

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not an actual list but just hundreds of

play25:38

different problems which i kind of just

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turn over and like

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you know you sort of consider many many

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variations on the same problem sometimes

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in a minute um uh uh

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but it's really that process of actually

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revising the problem

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um and sort of looking for things that

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seem like insights in some particular

play25:55

direction

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um uh but that's that's a personality

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thing

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and a thing about what sorts of things i

play26:02

am comfortable with and what sorts of

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things i am uncomfortable with

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and i suspect that if you look at

play26:07

somebody who's much much more problem

play26:08

oriented

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like hamming and like many many uh

play26:12

scientists and engineers um

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they would be comfortable and

play26:17

uncomfortable with quite a different set

play26:18

of

play26:19

set of things but you just said you have

play26:22

lists of problems so you are aware

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yeah but the point is that the problems

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from my point of view um they're not

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the point exactly they're almost

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provocations they're almost like sort of

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their steps along the way but they're

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not actually they're not they're not the

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goal

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um uh you know rather

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yeah i will tweet the problem a lot i

play26:47

mean

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sometimes literally many many many times

play26:51

sort of in a minute

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just trying to find something where it's

play26:54

like oh you know if i consider this

play26:55

variation it seems to connect to this

play26:57

thing over here and then all of a sudden

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it's like oh

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you know i can see some ways of making

play27:01

progress but it's it's the inside

play27:03

that sort of you know step of connection

play27:04

that i think is important

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um and i'm not sure i could do something

play27:08

like work on chroma's last theorem it's

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just like it seems so fixed

play27:11

and yeah what i feel like i'm hearing

play27:14

here is

play27:15

tell me if this maps to what you mean is

play27:18

instead of

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having solving a particular problem as

play27:21

your goal is about sort of the process

play27:23

to solving that problem

play27:24

builds up this mental model in your head

play27:26

and that model is the

play27:27

important thing the problem can help you

play27:29

get there it can help you

play27:31

sort of figure things out but sometimes

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you might realize actually this is the

play27:34

wrong way to phrase the problem entirely

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actually i can give a really i mean a

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really concrete example which kind of

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makes sense in

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in this context because you're all very

play27:42

familiar with it and andy helped

play27:44

discover it we invented this mnemonic

play27:46

medium over

play27:47

the last sort of two years and basically

play27:50

you know

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we didn't think let's set out to invent

play27:53

a medium that will help people remember

play27:54

stuff

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instead we spent several hundred hours

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like just talking about

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um a sort of human memory and how it

play28:02

works

play28:02

and different strategies for how you

play28:04

know you can sort of

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remember things and what's known about

play28:07

sort of human memory by cognitive

play28:09

scientists and so on

play28:10

and separately in apparently separate

play28:12

conversations

play28:13

we were talking a lot about tools for

play28:15

thought and how media

play28:17

changed the way people think and all

play28:18

these kinds of things and in some funny

play28:20

sense these were

play28:21

kind of two separate very long

play28:23

conversations and

play28:25

eventually they kind of merged into one

play28:27

conversation where in fact we realized

play28:29

that you could build a lot of these sort

play28:30

of memory ideas into some sort of new

play28:32

medium

play28:33

and started to sketch that out but it

play28:35

certainly it didn't come out of a

play28:36

problem-oriented mindset

play28:38

at all instead it just came of pursuing

play28:41

these

play28:41

two separate very interesting sort of

play28:43

senses of ideas

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sometimes they've kind of come closer to

play28:46

each other but most of the time they're

play28:48

very far apart and i i

play28:51

goodness knows how much time we spent

play28:53

sort of in those sort of separate

play28:54

parallel conversations

play28:55

before they before they merged but there

play28:57

was no sense of solving a problem

play28:59

at all it was however definitely a sense

play29:02

at least for me uh andy can maybe speak

play29:04

separately of discovering a new type of

play29:06

thing as a result of these conversations

play29:09

michael i think you gave a really good

play29:10

answer to the prompt so just wanted to

play29:12

say thanks and accept that

play29:13

um but to draw like what like part b

play29:16

out if i may as well uh which is it

play29:19

seems that hamming also did not win

play29:21

a zero-sum game himself he also

play29:25

just he turned over things that were not

play29:26

like you know conservative answers to

play29:28

questions per se

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other than in a broad sense yeah that

play29:32

seems certainly seems

play29:33

seems right to me i wonder what extent

play29:36

um

play29:37

this problem orientation has to do with

play29:40

this like

play29:40

micro nobel approach does that approach

play29:44

encourage a somewhat more uh

play29:48

like prop problem solving rather than

play29:51

problem finding

play29:52

type mindset it it seems like it would

play29:54

encourage

play29:55

you to try to solve a problem that you

play29:57

can stick a name onto

play29:59

um which means that you can kind of be

play30:01

cleanly

play30:02

put boundaries around otherwise you

play30:05

can't you can't like put your name to

play30:07

an entire field in the same way

play30:10

um now it doesn't mean that you couldn't

play30:13

win a nobel

play30:14

for discovering a field in fact many

play30:17

people have

play30:18

uh but it seems like you would focus

play30:20

your efforts on something that

play30:22

your name ends up getting very closely

play30:24

attached to

play30:26

is it worth refreshing hamming's micro

play30:27

nobel idea

play30:29

he has this interesting way of thinking

play30:30

about he's he's wondering what's my

play30:34

my productivity is gauged in terms of

play30:36

rate of micro nobels

play30:38

uh where a micro nobel is like a

play30:42

small but meaningful substantial

play30:45

insight uh and that seems to be

play30:48

his optimization function he refers to

play30:49

it a couple of times and this seems like

play30:51

a pretty different approach

play30:52

from like i want to found a field uh

play30:55

it's much more like i want some marginal

play30:58

increment of insight that is original

play31:00

and important

play31:01

right so this is a silly observation but

play31:03

um

play31:04

uh i have to interject it there hasn't

play31:05

been enough silliness um

play31:07

uh the uh john von neumann pointed out

play31:11

that a micro century

play31:13

is 50 minutes which is the time period

play31:17

for uh in fact a typical research talk

play31:20

um and i'm just thinking you know what

play31:23

that means is that unfortunately a micro

play31:24

nobel

play31:25

you would actually need to have one

play31:27

every 50 minutes

play31:28

in order for your entire life that's

play31:31

what nobel prize was at work

play31:33

but maybe there's some kind of you know

play31:35

sort of long tail and

play31:37

every once in a while you get a little

play31:38

bit sort of lucky and you know what you

play31:40

thought was going to be a micro nobel

play31:42

worth of 15 minutes

play31:43

actually becomes you know worth

play31:47

we can't let hamming off the hook for

play31:49

like being precise

play31:51

about scale and order of magnitude so

play31:55

we can't no it's not like he didn't find

play31:58

ten to the six

play31:58

micro nerf bells i expect like he knew

play32:01

what that meant

play32:02

and he would have been able to draw the

play32:04

inference between time and

play32:06

a cruel maybe he was being modest i'm

play32:09

also very curious what's a what's a mega

play32:12

nobel

play32:14

that's every nobel we've ever awarded

play32:16

themselves

play32:19

can i ask a question um of both uh star

play32:23

and andy and actually devin if you don't

play32:25

mind the opposition

play32:26

is this thing that i wonder

play32:29

as i read the artist of

play32:32

uh science and engineering okay i hope

play32:34

i'm getting the title right

play32:36

uh wrong like every time for whatever

play32:38

reason it's a hard title to remember i

play32:39

don't know why

play32:40

yeah out of doing science and

play32:42

engineering my god i can't believe them

play32:45

there's something really interesting

play32:46

about it which is

play32:49

so much of that book it's describing

play32:53

a research culture it's describing a

play32:55

research culture that i very much

play32:56

recognize

play32:57

and there's tons of books about research

play33:00

culture by all sorts of researchers

play33:03

and there are many very good ones and

play33:06

none of them seem to have resonated

play33:08

with silicon valley's kind of make a do

play33:11

a

play33:12

entrepreneur kind of a culture in the

play33:15

same way

play33:17

and i'm just curious if you have

play33:19

thoughts about

play33:20

why that is the case why do so many

play33:23

people here

play33:24

get what do they get out of it that's

play33:26

really sort of interesting and

play33:27

and exciting that maybe they don't get

play33:29

out of some of the other books that have

play33:31

been

play33:31

been written about research i find it

play33:33

really relatable

play33:34

in a way that many books about research

play33:36

culture are not because so much of

play33:38

hamming's

play33:39

descriptions are they came with the

play33:40

sleeves rolled up like working with

play33:43

filter circuits and programming or

play33:46

trying to direct others to program

play33:47

and it's true that you know we look at

play33:49

n-dimensional space

play33:51

and the error correcting codes which are

play33:53

arguably his most important work

play33:55

and that's somewhat less relatable but

play33:57

there's so much in the book

play33:58

that feels like my day-to-day experience

play34:00

that it's very easy for me to connect to

play34:02

it

play34:03

so it's just that kind of practical

play34:04

making aspect almost thing to

play34:07

for you andy you sort of feel like you

play34:08

can just recognize

play34:10

some of the things he's doing as being

play34:12

similar to you

play34:13

that's right okay yeah and it feels like

play34:15

he sort of like grabbed you by the hand

play34:17

and sort of pulled you in

play34:18

into his office and then just like watch

play34:20

me do this and he's starting he's

play34:21

starting to do it

play34:22

as opposed to i when i read

play34:26

other sort of similar types of things

play34:29

that feels like

play34:30

there's much more of a description of

play34:33

the

play34:34

the problem as opposed to the action of

play34:37

solving the problem

play34:39

um yeah and so it's like like just like

play34:41

what you compared it to with with the

play34:43

twitch streams it feels much closer to

play34:45

like a twitch stream

play34:46

than it does to like a grand science

play34:49

like this is what we figured out

play34:50

kind of thing it's also much more about

play34:53

the like

play34:54

the setting the environment that will

play34:55

then help you create

play34:57

great things which at least for me

play34:59

resonates very well and i think like for

play35:01

programmers in general

play35:03

you're always sort of building yourself

play35:04

tools that sort of scaffold

play35:06

yourself to be able to build the next

play35:07

tool and he's talking about these

play35:10

these mental tools and these sort of

play35:11

environmental and contextual tools

play35:13

that set him up for success right he's

play35:16

not just kind of considering them sort

play35:17

of instrumental things i think this is

play35:19

what i'm taking away from

play35:20

what both of you are saying but um

play35:23

and often that's the the the case when

play35:26

you read

play35:27

sort of scientists talking about pure

play35:29

science they sort of regard

play35:31

sometimes they will regard the tools as

play35:33

just these purely instrumental things

play35:35

not sort of interesting in their own

play35:37

right

play35:37

and i guess cameron kind of does just

play35:40

like them for their own right

play35:43

which is interesting sorry is that what

play35:45

were you gonna say

play35:47

it does have that quality of being kind

play35:49

of pulled by the

play35:51

you know the the cuff of your you know

play35:53

into office hours with a professor that

play35:55

you're sort of intimidated by and really

play35:56

look up to

play35:57

and you're like amazed that you get to

play35:59

have some time and

play36:00

what he says is okay look we need to

play36:02

talk and here's how it works

play36:04

and here's what you need to be doing um

play36:08

you know very few people are maybe even

play36:11

brave enough to put that down

play36:14

and we talked earlier about his like

play36:16

competitive streak but you know he also

play36:18

acknowledges you know creativity and

play36:22

um what i respect about all of that

play36:25

together is

play36:26

um you know maybe especially the

play36:29

competitive nature

play36:30

right we don't know if maybe played that

play36:31

part up about himself he might have

play36:33

right but he really acknowledges that

play36:35

like um

play36:36

maybe the very human part of like what

play36:39

what drives you

play36:40

uh and in an honest way again that like

play36:44

you know many books are unwilling to

play36:47

come close to you know and even for you

play36:49

know maybe reasons of not wanting to

play36:50

over generalize

play36:51

or you know whatever lame reason makes

play36:54

the book like

play36:55

not land he gives me the sense of like

play36:58

a sort of grumpy but brilliant uncle who

play37:01

really wants what's best for you and

play37:04

he's gonna tell you the tough stuff

play37:05

because that's what you need to hear

play37:07

um in a way that is quite rare

play37:11

i think um and i don't think that that

play37:13

answers specifically the systems builder

play37:15

question

play37:15

of like you know why does this resonate

play37:17

with makers but i think it just makes it

play37:18

resonate more with people in general

play37:20

because when people speak to you like

play37:22

you're someone that they care for

play37:24

and they speak to you like you can go do

play37:26

great things

play37:27

um but you can also really screw them up

play37:28

if you do some dumb stuff

play37:30

then you take it more seriously if

play37:32

they're taking you more seriously

play37:34

can i go in a totally like a direction

play37:36

we haven't touched so far

play37:38

there's a there's something i want to

play37:40

acknowledge about the book that is part

play37:42

of what makes it so special to me

play37:44

and i think it's i think it's even in

play37:46

maybe the first or second chapter

play37:49

hamming starts using you know order of

play37:51

magnitude

play37:52

estimation to make predictions about

play37:55

what the world

play37:56

is going to do and when you know and to

play37:59

say okay

play38:00

in like 50 years this is well beyond

play38:02

like my career or even my lifetime

play38:04

here's what i expect will be happening

play38:07

this is um so

play38:11

great for so many reasons first of all

play38:14

it's a pretty bold

play38:14

bet and he must have been fairly

play38:17

confident

play38:18

about you know other calculations having

play38:20

borne out

play38:21

to make that call uh and then also to

play38:24

put it in his book

play38:26

um and it's it's very upfront it's right

play38:28

there in the first chapter

play38:29

um it reminds me of at least one other

play38:32

place where i've seen that

play38:33

which is an example that i've come

play38:34

across recently that i found very

play38:36

interesting

play38:37

since reading um hamming's book

play38:41

which is actually jack northrup who

play38:43

founded what is now

play38:44

northrop grumman gave a talk in 1942

play38:50

saying that basically like modern

play38:52

aircraft were possible

play38:54

given uh like an auto sufficiently

play38:57

advanced autopilot right and

play39:00

he basically had like gears and linkages

play39:02

to work with

play39:03

but he could see like not only that that

play39:06

direction was

play39:07

would be possible and that it would be

play39:09

the right thing to do

play39:10

if it were like all he needed to make

play39:12

those airplanes was the right autopilot

play39:15

i don't know what quality it is that

play39:17

links that sort of foresight

play39:18

but hamming has it um and i i

play39:22

i'm very fascinated with that uh you

play39:24

know future looking

play39:25

long-term and like born out ability to

play39:28

estimate

play39:30

is that there's a ah a complementary

play39:33

thing that i i really enjoy i think it's

play39:35

very much in the same vein

play39:36

he talks about of course computers for

play39:39

the through the 40s and 50s were

play39:40

regarded as these calculating machines

play39:42

you solve

play39:43

differential equations on them you could

play39:45

predict behavior of systems

play39:47

and then hamming just has this great

play39:49

discussion

play39:50

of uh the fact that now actually they

play39:54

they might be meaning making machines as

play39:56

well they're not just

play39:57

um about solving uh numerical problems

play40:00

and doing calculations

play40:01

uh they're about uh solving uh

play40:05

other kinds of meaningful uh human

play40:08

problems

play40:08

and again that seems like this i mean

play40:11

from our point of view

play40:12

because we live in that world uh it

play40:14

seems totally obvious

play40:16

but at the time it must have just been

play40:18

shocking and seemed so

play40:19

foreign to people uh that that was sort

play40:22

of what what computers might actually

play40:23

ultimately be about

play40:25

i think that's like another really nice

play40:27

example of him

play40:28

kind of getting at the very very heart

play40:30

of the problem

play40:31

and then seeing what the world would be

play40:33

like in 30 years time he has this claim

play40:35

that we don't understand what computing

play40:36

is

play40:36

for yet and uh

play40:39

and like claims that uh often the

play40:42

problem seems to be

play40:43

not computational power or figuring out

play40:45

how to make the computer do things but

play40:47

rather you know knowing the question to

play40:48

ask

play40:49

and it kind of still seems true today in

play40:51

many ways it's really interesting to see

play40:53

what do you think would have surprised

play40:54

him about the state of computing today

play40:57

we do so little with so much he saw the

play40:59

move to vlsi

play41:00

so i don't think he'd be surprised by

play41:02

kind of decreasing

play41:04

core performance per watt trading off

play41:06

with say multi-core or something like

play41:08

that and i don't think you'd be

play41:09

surprised by

play41:10

like embedded cpus becoming more and

play41:12

more important

play41:14

so it's a little hard to say i mean

play41:15

maybe he'd be surprised

play41:17

by the the prevalence of

play41:21

tpus and things like that but i honestly

play41:22

i don't think so he talks about

play41:24

specialized

play41:24

uh specialized silicon uh for

play41:27

for digital filters in here so i think

play41:30

specialized silicon for

play41:32

you know tensor multiplication is

play41:34

probably not surprising

play41:35

he would not be surprised by video calls

play41:39

would he be surprised by the new forms

play41:42

of

play41:42

media and expression my guess is he

play41:45

wouldn't be surprised but he would be

play41:46

delighted

play41:48

he would be he wouldn't predict any

play41:50

specific outcome but then he would be

play41:52

like very excited to see that people are

play41:54

playing around

play41:55

with these things and and um probably

play41:58

didn't necessarily go down all of the

play42:00

different tendrils of the pathways

play42:02

of what things became i'm gonna ask just

play42:04

one more question

play42:06

and uh this is for for all of you um

play42:09

hamming argues that breakthroughs tend