Pioneers: A roundtable on Richard Hamming

Summary

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。

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

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

three good friends

andy matushak star simpson and michael

nielsen

andy's a software engineer designer and

researcher and he works on technologies

that expand what people

think and do star is a hacker and

founder

she's working on a company called their

craft which uses autonomous

aircraft to enable air freight logistics

michael is a scientist who helps pioneer

quantum computing

and open science movement his focus is

on ideas and tools that help people

think and create

both individually and collectively so

today we're here to talk about one of

our favorite books the art of doing

science and engineering and i'm really

excited because we're all good friends

but we also haven't talked that much

about this particular book together

so we're going to have a lot of fun

diving into

into this book what it means to us and

ideally where we disagree on the

interpretation too so

for starters in the art of doing science

and engineering

the author hamming puts forth a

transcendental narrative

he answers the question of what matters

and something

that i've heard andy say is that

hamming's religion is the unabashed

pursuit of excellence so what does

excellence mean to hamming and what does

it mean to you

hamming has a really specific definition

of of excellence

he's interested in people understanding

fundamental properties of

reality uh more accurately and and

sharing that knowledge with others

one of the things that i think is most

interesting about his view is it's not

even so much

uh excellence or or what he means by

that but the unabashed

side of it i think it's really

interesting to read this book in 2020

an irony laden society or something like

that uh the kind of like earnestness

uh that he brings to his narrative is

really interesting to me yeah he's

he's like well of course you want to do

great things and

since you naturally want to do great

things uh you know here are some

considerations

i think it stands in really stark

contrast

a lot of stances these days

where i i think it's difficult to talk

pursuing excellence seriously and not

either come off

as delusional or as like

self-aggrandizing or

arrogant or just out of touch or

something like that and so i i enjoy

that part of it

what's changed well hamming was part of

a generation

that i think took kind of a shared

project

of progress and understanding

very just among scientists but even

society

kind of grand projects of the mid 20th

century

counterculture movements i i'm

spitballing here

and grunge and

generation x uh um kind of

stereotypical cynicism perhaps or eroded

some of this i i guess i'm not really

sure i'd be curious what others think

well i think hamming was kind of a rare

person

uh and it's not just that he was this

very clear thinker uh he

also had a lot of self-awareness which

is

very unique quality in any person and

furthermore was committed to

communicating about it

right so like each of those things like

himself being an astute observer

and you know being uh self-aware about

what

you know what worked to enable that and

also

being committed to communicating to

others i think are the things that make

hamming you know so unique and his

writing so unique and so genuine

yeah my my instinct is that there's

there are a lot of people who are

very good at science and there are also

a lot of people who are very uh

interested in communicating about

science

but the the overlap isn't necessarily

particularly strong

it felt like with hamming he had these

amazing discoveries did

great mathematics and then he said wow

this is so great that i have to share

both this work and also my process and

the process of great people around me

with people as opposed to sort of

communicating about science for

science's sake

yeah and he was right about you know his

ideas but he was also right about

you know what are the right things to do

uh

it all stacks up you know in such a such

a unique way such an interesting way

it's uh

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

give us the artifacts of his

concepts but also gave us you know what

he had studied along the way

uh to become a person able to discover

concepts that's what i love about the

book

michael what do you think made hamming

special can i come back

uh to andy's uh comment i want to

disagree completely

um which is very unusual for me yeah

andy made this comment

essentially i i would say it's almost

sort of a nostalgic comment

about maybe past generations being more

interested in excellence

i don't think you can conclude that from

hamming at all hamming was at the 99.99

percentile of being interested in

excellence for his own generation

i'm not sure you can actually infer very

much about what was typical for people

yeah i think that's

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

so much that prior generations

i think were more interested in

excellence necessarily but rather that

um i think it was more okay to express

an interest in excellence

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

know if you walk into a bookstore which

of course you can't do at the moment

you know there'll be like masses of

shelves that are basically about nothing

but the pursuit of excellence

in a whole lot of different ways um and

so

yeah and i mean they're routinely some

of the highest selling

uh books i mean some of them are not

framed as excellent exactly

you know being becoming a millionaire

next door or something like that isn't

quite about that but there's certainly i

don't know the seven habits of highly

effective people and there's like a

thousand

titles like like that and they sell

millions of copies

so i think people are pretty interested

and they're pretty willing to

to accept it hamming i do think was

a little bit unusual in you know he has

this very precise articulation

saying that even though a lot of people

are sort of nominally interested in this

they don't actually necessarily take the

specific actions

uh to act on it he makes this comment

about going and talking to some of the

other scientists

at some of the you know at the lunch

tables and saying you know

what are the important problems in your

field and some of them saying well

i don't really know and even if they did

know

you know why you're not working on them

and um

discovering that this made him

apparently at least some of the time not

a very popular lunch companion

and that's i think that's pretty

interesting uh it might be a constant

between his time

and our time i'm not not sure but uh

it's certainly an interesting

observation i think that really speaks

to kind of

what amazes me is the nuts and bolts

level of detail about his advice

can you give us another example well you

know as contrasted to

self-help or self-improvement guidebooks

i think

hamming doesn't put it in the spirit of

like like if you just drank a few more

glasses of water every day you'd like

think more clearly

he really lays out that like it's hard

work

and the thing you need to do more of is

work right

and talk to people he advocates a

program of like studying

past uh eminent discoverers and trying

to like piece apart

what their discovery process had been

for instance like

uh what prior knowledge allowed them to

like make that insight what was it about

their context or their environment that

enabled that

and then trying to like shape his own

environment around that so thinking very

carefully about you know

when and how often to have one's door

open uh how to

piece apart one's work and to kind of

thinking big picture versus like

you know working on very tactical tasks

how to look at a new field that's

emerging uh

and kind of decide when to when to like

jump into it

uh he advocates like thinking very

carefully about all of these things

i i think that's very much right but i

also also think it's quite challenging

to actually

study the context that somebody is in so

there's no lack of

biographies out there and histories but

i always

have this nagging sense when i read a

biography that it's just a just so story

and you're not actually learning much at

all about what really mattered for

having this person succeed sometimes

it's partially about

motivations like people want to tell a

different story that and make it a

little bit smoother because it's cleaner

sometimes it's just people forgot the

details and it just didn't really come

up or didn't seem relevant to the author

but i found personally that like i

started

i've been reading fewer and fewer

biographies in my life and just trying

to spend time with people who i think

are doing good work

because then you can actually see it

firsthand what it is that enables them

to do that and like what their their

patterns of thought are um but that

means you have to like be around

certain types of people and like this is

one of the reasons why i love being

friends with people like you

um but how can you scale that beyond

just

becoming friends with people okay like

what in particular devin

scaling what experience let's say in

high school um

i i did not have access to the kind of

friends that i have now

i didn't know twitter existed i didn't

have the email etiquette that i now have

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

have a driver's license i couldn't get

to the people i wanted to get to

and so i i was kind of stuck with

reading biographies

and so like how how would a 14 year old

get

more of this context so that they can

start learning as opposed to having to

be

in their 20s and living in a great city

or a great

like university something that that is

certainly

yeah a lot of fun is uh uh you know

watching sort of

twitch live streams of people doing

interesting things uh because you know

you're not actually getting their kind

of

reconstructed just those story about how

it is they did what they did

no you're actually seeing them do the

thing

maybe sort of an even more fun uh

example in some ways

i mean you can you can do this um sort

of

i mean with anything that you can see

done for sort of live action

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

name of the the greatest sneaker player

in the world

ronnie o'sullivan um you know he claims

that he put himself to play snooker

basically by watching videos of uh the

previous best player in the world

uh steven hendry uh and just

imitating him at the age of 10 11 12

and that's pretty cool that he can sort

of do that you know self tutorial

uh uh sort of just by searching out well

searching out video

and and watching

so i guess the takeaway is that more

scientists should be on twitch

actually so i i know somebody uh who was

at stanford uh

who did live stream in fact they're you

know a substantial chunk of their phd

um uh which i thought was pretty great

um

and there's yeah there's other things

there's a company what is it called

uh jove the journal of visualized

experiments

who will send a camera crew to your lab

uh and actually show you you know

actually video you

as you know you arrange i don't know

what

what you do you know arrange the perfect

in just the right way to do the

you know the procedure um i think that's

i don't know

it's pretty interesting like you kind of

just learn stuff by seeing people do

things

uh for real in a way that you can't

learn from

i i sort of i don't entirely agree with

you about biographies

but there is definitely a lot left out

there are good biographies but it's

really hard to know

if it's true or not and i think

biographies for me

serve more as sort of inspiration of

people doing great things

and i just get really excited about

doing things in the world when i read

biographies

but it's less of a manual about how to

um usually

um i find often interviews like

especially less

um like highly edited interviews are

often good for

for getting uh somewhat

less just so stories i mean of course

you'll still get them but sometimes

you'll get these little

these little gems where the interviewer

was like how did you think to do that

and the person was like well

you know i i just encountered this other

person who was doing this thing

um it's kind of similar to the twitch

vibe where you kind of like

you see how the stumbling happens i

think another dynamic

you see in biographies is there's often

selection for people who have become

fairly you know noteworthy for whatever

reason and there's a subtle

effect where when you're you know

whatever you want to call it senior

um often folks end up with

others sort of working under their name

you know doing a lot of the

the gumshoe work you know and so i've

seen a lot of

biographies i don't want to single

anyone out particularly but i am

thinking of one where

in the beginning this guy was like i you

know i had to get a like medical

exemption so they didn't send me to war

and so i threw the paperwork off the

side of my motorcycle and like ran over

it a few times to make it look

you know whatever it's like very

tactical you tactile

as well and you know then by the end of

it he's like yeah and then um

we invented you know and he's really

kind of encompassing a few hundred other

people

when you know with that we but like you

know he you sort of

you get the sense that as much as the

vision never faded

um that person stopped having their

fingers you know in the

in the paint um and and hamming's book

is again like particularly noteworthy

because he's so

blunt about the requirements

what's the more examples of the

bluntness class this is referencing what

andy mentioned earlier

where he goes into detail about you know

how often to have your door open you

know to acknowledge

very specifically some people can get

more work done with their doors closed

however

they're more likely to diverge away from

doing like what we collectively think

is like useful and interesting that's

just tactical like

and that's also like a very interesting

thought it's not an idea that i

really heard anybody else address like

to the extent i thought of it on my own

it was really just sort of like

wandering off in my head and it's like

not the kind of thing i would imagine

being able to sort of like

air in a workbook not the average

workplace of like you know so how often

should i have my door open in order to

be most productive it's not like a

not a thing that question you know and

like and then he just went and wrote it

down i enjoy the um

uh he refers to john tukey uh quite

frequently

uh and there's also kind of a similar

slightly in-your-face quality about some

of those references

you can see you know when he was

referring to somebody like shannon who

was a little bit older

you know he admired him but he didn't

really view him as a peer and so it was

kind of more of a

almost sort of a mentor yo or somebody

who he looked up to

but tuki was about the same age and you

could see

that he felt competitive with dookie and

a little bit jealous that tsuki was so

good

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

all that that sort of the

discussion of you know what made took

you so good

and uh there's a a great moment sort of

i think in much the same vein

of just uh i think he goes to talk to

his boss

and he complains how can tooky know so

much and his boss

leans back in his chair and says uh you

too would be surprised if you worked as

hard as john tsuki how much you know

like okay right he makes this great

point from that

about kind of the compounding nature of

knowledge

and that you know kind of small marginal

investments may return

i i'll show like one other kind of blunt

thing i really enjoyed it

i left all the instances where we kind

of complained about his own failure um

and and he has a couple actually where

he talked about essentially

he was going with cached thoughts like

he had come to some conclusion

about uh i think his digital filters uh

based on some

like prior nature of the field and so he

missed

um this opportunity that one of his

colleagues

uh ended up pursuing uh rather than him

and he felt kind of frustrated about

that like i should have gone after that

and the reason that i didn't was that

i'd already decided that that approach

wasn't gonna work and so when the

situation on the ground changed

uh he didn't reconsider and uh he kind

of

exhorts the readers in the in the ai

chapters

uh for instance that you know almost

everybody who's kind of talking about

the future of ai's

is just kind of repeating other people's

conclusions you need to like

sit and like do your own thinking and

update your thinking and otherwise

you're gonna have no idea

uh what's what's gonna come i really

liked that

example of the feedback about john tukey

working just harder

than hamming what was a time in your

careers that

someone gave you pretty harsh advice

like that where you're like oh man

i really gotta think about this uh i

i've got one that

um it was harsh in it in a in a subtle

way

but it still like really

uh kicked me quite hard uh i was

supposed to be responsible for um this

particular gesture interaction

uh on ios and

you know i'd been working on it for a

while and it still wasn't feeling quite

right

it was like triggering at the wrong

times and

after a conversation with my manager

about

possible approaches you know we kind of

come up with some ideas and i said

you know i'm gonna pursue these over the

next coming days and

you know he was clearly kind of

interested in seeing if we could make

progress a little faster

but you know i went home uh it was you

know maybe 7 30 or something

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

been there

like most of the night uh and when i got

there the problem was basically solved

uh

and uh uh

there there was no like criticism really

about not having

carried it forward quite so aggressively

uh

but uh arriving and having the problem

that i'd been wrestling with for quite

some time

kind of just solved uh for me was a

a good kick you never forget that

feeling when it happens i

i associate a couple of those with my

peers in high school

um my best friend in high school and i

were like extremely competitive with

each other

it was probably the most competitive

relationship you could have with someone

and still consider them your friend and

sometimes it did break down

it didn't help that my high school was

tiny and we were like the

two you know we had to be you know we

both had these personalities we had to

be the best and everything

but then by you know the end of high

school you know i was in a calculus

class of four people

it was her and me and like two two

others you know and like

it got it got very narrow at times um

but i just like

you know as hard as it was sometimes i

still really

miss how intense it was

because it was great i mean we went to

school for six years and we were just

like

you know in every way wherever possible

toe to toe

you know it was great when is

competition productive and when is it

more toxic i think i deny the premise of

the question

toxic uh no okay all right let me

let me lean into the question let me let

me accept the remnants of the question

um uh

i mean you can probably all guess that

maybe people listening to this can't

my opinion um mostly you know if you're

on sort of a linear scale

like get off the scale uh go and do

something else

um you know i really enjoy

uh watching actually sport of all kinds

like i love

you know watching people play tennis i

enjoy athletics and whatnot

uh and so i'll admire serena williams

or usain bolt or whoever is just

wonderful

but it's also true that if you know

serena stopped there would be a second

best player in the world

uh who would take her place uh actually

i guess it kind of has been over the

last few years but over the last 20

years

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

player

um and so no it always strikes me

uh somehow you know if there's a

thousand people all competing to do the

same thing

actually probably a lot of them could go

and do other things they could invent

other games

uh to play uh some of which would be

unique games games that only they

in the world were playing uh and it

would be both more meaningful that for

them it would be more meaningful for

their family and for their friends um uh

and just better for the world if they

were to go and do those

those other things um so i don't know

competition

is uh sometimes good

for motivating you but i think you

always want to be in sort of a pool

small enough but it's

actually to some considerable extent

friendly competition

um and you don't feel that the kind of

hate

is when you're getting crowded out and

there's like 17 people

all trying to do exactly the same thing

and it doesn't even feel that important

anyway

um because in fact you know there's kind

of just too many people

trying to do the same sort of thing

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

version

uh i'd rather just you know go and find

uh

uh ideally incredibly meaningful and

important things that you can do

that way you're the only person or one

of a tiny number of people who are

pursuing that end

that's my way nothing about competition

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

i think he was a more competitive kind

of a person he wanted to win

uh quite often even his framing of

you know asking what are the most

important questions in your field what

are the most important problems in your

field and why are you not working on

them

um that seems to me like kind of a silly

framing it's accepting the consensus

social reality of what the field is

when in fact it is much better very

often uh to figure out what are the

problems

that nobody in your field has even you

know has understood are important yet

um sort of trying to invent new problems

and maybe even new fields

um that sort of strikes me as just a

more enjoyable and ultimately more

meaningful

activity

if one is trying to find a new field or

at least find a new set of problems

what should they do differently from

what hamming recommends that they do

so some researchers they find a problem

and the goal is to solve that andrew

wile's working on gemar's last theorem

he knew what the theorem was and that

was very much the objective

and so you're always trying to find

little ways of like you know how can i

get just a little bit more insight in

this direction that direction or whatnot

and people who do uh problem discovery

or even field discovery

i think operate really in quite a

different way um

they are exploring in a general

direction they're trying to find

little bits and pieces of insight they

have some instincts that there's some

big problem

over in this general direction um i

think

maybe a good example is um somebody like

uh turing

in sometimes he was actually kind of

working on a particular problem it was a

fairly esoteric logic problem that david

hilbert

had posed um in some sense he couldn't

work on the problem

of discovering universal computation

because nobody had said what universal

computation was

the the the genius in that paper uh

isn't uh proving that the whole thing

problem is unsolvable which is often

how it's framed it was inventing the

concept of universal computation

um and almost by definition that that's

not a

that's not a problem uh uh yeah that is

a problem that is only evident

after the fact that that's very often

the the

case in in science that the most

interesting discoveries

uh not discoveries you know not not

solutions to problems but rather

actually

identifying that there is a new concept

a new type of thing

in some particular direction and

and that's something that proceeds i

think much more based on sort of

instinct

uh uh an intuition where you're like

there is something here

and i can sort of very vaguely see the

outlines of it

you kind of just keep chiseling away

chiseling away chiseling away trying to

see if there's something actually there

and probably 99 times out of 100 it

turns out it was a mirage and there is

nothing there

and then you know very occasionally

somebody discovers

something like the notion of universal

computation um and really the problem

that turing was working on was always

incidental to that um you know it's

wonderful

that he discovered universal computation

out of it and

the solution to the problem is like a

nice it was kind of it was a way of

getting there it was almost an excuse a

provocation for getting there

i have a question for you michael you're

gonna talk more now

okay which do you think is the better

problem discovery question of the

questions posed which are either

what are the most important problems in

your field or

what are the that you know that others

are thinking about or what are the most

important problems in your field that

nobody's thought of yet

which do you think would be the better

problem discovery

question to ask better being you know

more productive more likely to turn over

actually i think it's it's probably

mostly um

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

what your personality is i'm

not sure you even actually get to decide

um

and and to something that all i'm doing

is relaying my own personality

um i just don't really like working on

fixed problems or i like having sort of

a list of 100 or well

not an actual list but just hundreds of

different problems which i kind of just

turn over and like

you know you sort of consider many many

variations on the same problem sometimes

in a minute um uh uh

but it's really that process of actually

revising the problem

um and sort of looking for things that

seem like insights in some particular

direction

um uh but that's that's a personality

thing

and a thing about what sorts of things i

am comfortable with and what sorts of

things i am uncomfortable with

and i suspect that if you look at

somebody who's much much more problem

oriented

like hamming and like many many uh

scientists and engineers um

they would be comfortable and

uncomfortable with quite a different set

of

set of things but you just said you have

lists of problems so you are aware

yeah but the point is that the problems

from my point of view um they're not

the point exactly they're almost

provocations they're almost like sort of

their steps along the way but they're

not actually they're not they're not the

goal

um uh you know rather

yeah i will tweet the problem a lot i

mean

sometimes literally many many many times

sort of in a minute

just trying to find something where it's

like oh you know if i consider this

variation it seems to connect to this

thing over here and then all of a sudden

it's like oh

you know i can see some ways of making

progress but it's it's the inside

that sort of you know step of connection

that i think is important

um and i'm not sure i could do something

like work on chroma's last theorem it's

just like it seems so fixed

and yeah what i feel like i'm hearing

here is

tell me if this maps to what you mean is

instead of

having solving a particular problem as

your goal is about sort of the process

to solving that problem

builds up this mental model in your head

and that model is the

important thing the problem can help you

get there it can help you

sort of figure things out but sometimes

you might realize actually this is the

wrong way to phrase the problem entirely

actually i can give a really i mean a

really concrete example which kind of

makes sense in

in this context because you're all very

familiar with it and andy helped

discover it we invented this mnemonic

medium over

the last sort of two years and basically

you know

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

a medium that will help people remember

stuff

instead we spent several hundred hours

like just talking about

um a sort of human memory and how it

works

and different strategies for how you

know you can sort of

remember things and what's known about

sort of human memory by cognitive

scientists and so on

and separately in apparently separate

conversations

we were talking a lot about tools for

thought and how media

changed the way people think and all

these kinds of things and in some funny

sense these were

kind of two separate very long

conversations and

eventually they kind of merged into one

conversation where in fact we realized

that you could build a lot of these sort

of memory ideas into some sort of new

medium

and started to sketch that out but it

certainly it didn't come out of a

problem-oriented mindset

at all instead it just came of pursuing

these

two separate very interesting sort of

senses of ideas

sometimes they've kind of come closer to

each other but most of the time they're

very far apart and i i

goodness knows how much time we spent

sort of in those sort of separate

parallel conversations

before they before they merged but there

was no sense of solving a problem

at all it was however definitely a sense

at least for me uh andy can maybe speak

separately of discovering a new type of

thing as a result of these conversations

michael i think you gave a really good

answer to the prompt so just wanted to

say thanks and accept that

um but to draw like what like part b

out if i may as well uh which is it

seems that hamming also did not win

a zero-sum game himself he also

just he turned over things that were not

like you know conservative answers to

questions per se

other than in a broad sense yeah that

seems certainly seems

seems right to me i wonder what extent

um

this problem orientation has to do with

this like

micro nobel approach does that approach

encourage a somewhat more uh

like prop problem solving rather than

problem finding

type mindset it it seems like it would

encourage

you to try to solve a problem that you

can stick a name onto

um which means that you can kind of be

cleanly

put boundaries around otherwise you

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

an entire field in the same way

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

win a nobel

for discovering a field in fact many

people have

uh but it seems like you would focus

your efforts on something that

your name ends up getting very closely

attached to

is it worth refreshing hamming's micro

nobel idea

he has this interesting way of thinking

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

my productivity is gauged in terms of

rate of micro nobels

uh where a micro nobel is like a

small but meaningful substantial

insight uh and that seems to be

his optimization function he refers to

it a couple of times and this seems like

a pretty different approach

from like i want to found a field uh

it's much more like i want some marginal

increment of insight that is original

and important

right so this is a silly observation but

um

uh i have to interject it there hasn't

been enough silliness um

uh the uh john von neumann pointed out

that a micro century

is 50 minutes which is the time period

for uh in fact a typical research talk

um and i'm just thinking you know what

that means is that unfortunately a micro

nobel

you would actually need to have one

every 50 minutes

in order for your entire life that's

what nobel prize was at work

but maybe there's some kind of you know

sort of long tail and

every once in a while you get a little

bit sort of lucky and you know what you

thought was going to be a micro nobel

worth of 15 minutes

actually becomes you know worth

we can't let hamming off the hook for

like being precise

about scale and order of magnitude so

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

ten to the six

micro nerf bells i expect like he knew

what that meant

and he would have been able to draw the

inference between time and

a cruel maybe he was being modest i'm

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

nobel

that's every nobel we've ever awarded

themselves

can i ask a question um of both uh star

and andy and actually devin if you don't

mind the opposition

is this thing that i wonder

as i read the artist of

uh science and engineering okay i hope

i'm getting the title right

uh wrong like every time for whatever

reason it's a hard title to remember i

don't know why

yeah out of doing science and

engineering my god i can't believe them

there's something really interesting

about it which is

so much of that book it's describing

a research culture it's describing a

research culture that i very much

recognize

and there's tons of books about research

culture by all sorts of researchers

and there are many very good ones and

none of them seem to have resonated

with silicon valley's kind of make a do

a

entrepreneur kind of a culture in the

same way

and i'm just curious if you have

thoughts about

why that is the case why do so many

people here

get what do they get out of it that's

really sort of interesting and

and exciting that maybe they don't get

out of some of the other books that have

been

been written about research i find it

really relatable

in a way that many books about research

culture are not because so much of

hamming's

descriptions are they came with the

sleeves rolled up like working with

filter circuits and programming or

trying to direct others to program

and it's true that you know we look at

n-dimensional space

and the error correcting codes which are

arguably his most important work

and that's somewhat less relatable but

there's so much in the book

that feels like my day-to-day experience

that it's very easy for me to connect to

it

so it's just that kind of practical

making aspect almost thing to

for you andy you sort of feel like you

can just recognize

some of the things he's doing as being

similar to you

that's right okay yeah and it feels like

he sort of like grabbed you by the hand

and sort of pulled you in

into his office and then just like watch

me do this and he's starting he's

starting to do it

as opposed to i when i read

other sort of similar types of things

that feels like

there's much more of a description of

the

the problem as opposed to the action of

solving the problem

um yeah and so it's like like just like

what you compared it to with with the

twitch streams it feels much closer to

like a twitch stream

than it does to like a grand science

like this is what we figured out

kind of thing it's also much more about

the like

the setting the environment that will

then help you create

great things which at least for me

resonates very well and i think like for

programmers in general

you're always sort of building yourself

tools that sort of scaffold

yourself to be able to build the next

tool and he's talking about these

these mental tools and these sort of

environmental and contextual tools

that set him up for success right he's

not just kind of considering them sort

of instrumental things i think this is

what i'm taking away from

what both of you are saying but um

and often that's the the the case when

you read

sort of scientists talking about pure

science they sort of regard

sometimes they will regard the tools as

just these purely instrumental things

not sort of interesting in their own

right

and i guess cameron kind of does just

like them for their own right

which is interesting sorry is that what

were you gonna say

it does have that quality of being kind

of pulled by the

you know the the cuff of your you know

into office hours with a professor that

you're sort of intimidated by and really

look up to

and you're like amazed that you get to

have some time and

what he says is okay look we need to

talk and here's how it works

and here's what you need to be doing um

you know very few people are maybe even

brave enough to put that down

and we talked earlier about his like

competitive streak but you know he also

acknowledges you know creativity and

um what i respect about all of that

together is

um you know maybe especially the

competitive nature

right we don't know if maybe played that

part up about himself he might have

right but he really acknowledges that

like um

maybe the very human part of like what

what drives you

uh and in an honest way again that like

you know many books are unwilling to

come close to you know and even for you

know maybe reasons of not wanting to

over generalize

or you know whatever lame reason makes

the book like

not land he gives me the sense of like

a sort of grumpy but brilliant uncle who

really wants what's best for you and

he's gonna tell you the tough stuff

because that's what you need to hear

um in a way that is quite rare

i think um and i don't think that that

answers specifically the systems builder

question

of like you know why does this resonate

with makers but i think it just makes it

resonate more with people in general

because when people speak to you like

you're someone that they care for

and they speak to you like you can go do

great things

um but you can also really screw them up

if you do some dumb stuff

then you take it more seriously if

they're taking you more seriously

can i go in a totally like a direction

we haven't touched so far

there's a there's something i want to

acknowledge about the book that is part

of what makes it so special to me

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

maybe the first or second chapter

hamming starts using you know order of

magnitude

estimation to make predictions about

what the world

is going to do and when you know and to

say okay

in like 50 years this is well beyond

like my career or even my lifetime

here's what i expect will be happening

this is um so

great for so many reasons first of all

it's a pretty bold

bet and he must have been fairly

confident

about you know other calculations having

borne out

to make that call uh and then also to

put it in his book

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

there in the first chapter

um it reminds me of at least one other

place where i've seen that

which is an example that i've come

across recently that i found very

interesting

since reading um hamming's book

which is actually jack northrup who

founded what is now

northrop grumman gave a talk in 1942

saying that basically like modern

aircraft were possible

given uh like an auto sufficiently

advanced autopilot right and

he basically had like gears and linkages

to work with

but he could see like not only that that

direction was

would be possible and that it would be

the right thing to do

if it were like all he needed to make

those airplanes was the right autopilot

i don't know what quality it is that

links that sort of foresight

but hamming has it um and i i

i'm very fascinated with that uh you

know future looking

long-term and like born out ability to

estimate

is that there's a ah a complementary

thing that i i really enjoy i think it's

very much in the same vein

he talks about of course computers for

the through the 40s and 50s were

regarded as these calculating machines

you solve

differential equations on them you could

predict behavior of systems

and then hamming just has this great

discussion

of uh the fact that now actually they

they might be meaning making machines as

well they're not just

um about solving uh numerical problems

and doing calculations

uh they're about uh solving uh

other kinds of meaningful uh human

problems

and again that seems like this i mean

from our point of view

because we live in that world uh it

seems totally obvious

but at the time it must have just been

shocking and seemed so

foreign to people uh that that was sort

of what what computers might actually

ultimately be about

i think that's like another really nice

example of him

kind of getting at the very very heart

of the problem

and then seeing what the world would be

like in 30 years time he has this claim

that we don't understand what computing

is

for yet and uh

and like claims that uh often the

problem seems to be

not computational power or figuring out

how to make the computer do things but

rather you know knowing the question to

ask

and it kind of still seems true today in

many ways it's really interesting to see

what do you think would have surprised

him about the state of computing today

we do so little with so much he saw the

move to vlsi

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

kind of decreasing

core performance per watt trading off

with say multi-core or something like

that and i don't think you'd be

surprised by

like embedded cpus becoming more and

more important

so it's a little hard to say i mean

maybe he'd be surprised

by the the prevalence of

tpus and things like that but i honestly

i don't think so he talks about

specialized

uh specialized silicon uh for

for digital filters in here so i think

specialized silicon for

you know tensor multiplication is

probably not surprising

he would not be surprised by video calls

would he be surprised by the new forms

of

media and expression my guess is he

wouldn't be surprised but he would be

delighted

he would be he wouldn't predict any

specific outcome but then he would be

like very excited to see that people are

playing around

with these things and and um probably

didn't necessarily go down all of the

different tendrils of the pathways

of what things became i'm gonna ask just

one more question

and uh this is for for all of you um

hamming argues that breakthroughs tend

to come from deep emotional involvement

not the stereotypical calm cool and

uninvolved mindset

does this ring true for you and if so or

if not

how did you learn it for yourself i mean

it

obviously it seems obvious to me that

this is true

um i don't think i've worked on anything

that i

didn't end up having strong feelings

about no matter how it began

but as far as like how i came to

discover that

i don't know how to answer that all

right let me take the contrary view

because i've made the argument sort of

in the other direction so many times

norm mccrae wrote a pretty interesting

biography of john von neumann

and in the biography he makes this

observation about veteran russell versus

von neumann

that bertrand russell was utterly

extraordinarily brilliant

but he essentially claims that russell's

main problem was that he was too

emotional he got too involved

in a lot of his work and this is the

reason why he in fact did not do

deeper work ultimately whereas he makes

the claim

that one of von neumann's strengths was

his ability to remain

relatively uninvolved and sort of to be

a

relatively emotionless and

i know i thought a lot about that that

claim there's at least a little bit of

sympathy to it

a problem that can arise when you get

too emotionally involved

in your work is that actually it can

start to interfere with doing it well

you can start to get anxious about how

it's going to come out you can start to

get too stressed

and sometimes it's just better to chill

the hell out and go and do something

else for

you know either a day or in some cases

six months so that's you know

i mean there's some sense in which uh it

is true

but there's kind of a moderation it's

maybe sort of a goldilocks principle

kind of a thing

where you don't want to be too little

involved you don't want to be too much

and

you want to be involved at just the

right level which is the kind of

sentence that's really easy to say

and really hard to act on in practice

i'll echo that

the goldilocks thing really resonates

with me i i don't

i don't really know how to work without

being emotionally involved and stuff but

i've definitely experienced

problems when i've been too emotionally

involved in things and i'll just share

like

one consequence that that has uh

is not stopping soon enough

because most problems you pick up like

probably you should put down

and choosing when to stop work on a

problem is is this really hard thing

that hamming actually talks about some

but but actually i'd love to see more

literature about you know choosing when

to stop working on a thing

i think being emotionally involved

there's several times in my career

where uh i have i've not dropped a

project

soon enough and like many months over

and i

i should have what signs should you have

looked for

that if you were to do it again you

could have known to stop earlier

yeah first order thing to try i think is

is kind of

you know try to try to write the outside

view

uh what did the outside view of this

look like

um i probably would have struggled to

write a compelling outside view for

these projects

i find when i have to start justifying

it to my friends

um that's a that's a sign to be like

appropriately demanding friends that's

great yeah i mean

it's not always the way to go but if you

find yourself a little bashful to be

like ah

i'm still working on this because like

it's important but also there's all

these reasons why it's like i'm not

going to make progress

or you know you're working with people

who are not going to help you with that

um

that's that's a that's an important

important i want to push back against

that

evan i think like some of the most

interesting stuff i've ever done

has been stuff where when i'm talking

about it to friends

i i feel like i have to justify it a lot

maybe it's a different kind of

justification but basically it's like i

don't really know what this is

i mean if you've been working on

problems that always sounded like they

made sense my goodness

like i often have a problem where like

it doesn't make any

like people don't sort of squint and

they say what you know and

you just have to sort of shrug you know

i have a question for michael and andy i

know michael is a marginalia

note taker i think andy is

also where in this book did you make the

most notes

let's flip through and see i mean yeah

unfortunately the sort of trivial boring

answer which is of course

there's the overlap with the famous

essay you and your research

and so yeah it's not a terribly

interesting answer unfortunately

i i have a bunch of margin obviously the

highest density is there for me as well

uh the creativity chapter and systems

engineering chapters which are also

kind of similar themes um also have a

lot of highlights for me as as well as

the orientation chapter which also has

similar themes so i guess like the stuff

that grabbed my attention

most was or at least most densely

was that type of stuff however um i

think some of the biggest

insights from the book or like some of

the points that i most enjoyed are like

scattered in the middle of a chapter on

digital filters you know i'll have like

three stars in the margin or something

like it's like hey pay attention to this

it's in the middle of this otherwise

surprising chapter how about you it's

interesting i i feel like a lot of that

material

is sort of well okay i couldn't say

something critical

i don't entirely believe it it's gonna

say that it's actually kind of similar

to stuff you can find elsewhere

actually that's not even true it's still

kind of interesting because he talks

quite a bit more about

sort of motivation ordinarily it's

embedded deeply in the material

you know i mean so i'm just like looking

for these big stars right now and you

know so one of them

is this short diatribe i referenced

earlier when hamming says you must

struggle with your own beliefs if you

were to make any progress in

understanding the possibilities and

limitations of computers in this

intellectual area talking about ai

now like you know you can read like lots

of essays exhorting you to

do your own thinking form your own

opinions that's fine um the fact that

this follows several thousand words

about like reasoning

prospects for ai makes it much more

useful i'd say for me but actually

the first time i read it um that you get

what you measure

this is i read it a while ago so you get

what you get measure chapter really blew

my mind

and then when i reread it again recently

i had realized that i just

fully internalized all of that and i

thought it was the most boring chapter

it was pretty satisfying actually but

also i kind of like skim through like

okay i get it

i i find that's a very common pattern

for me when i learn something is

things that are most shocking or hardest

for me

often end up then being very integrated

into

my world view and my like abilities in a

way that things that were like

less mind-blowing um early on like i

remember when i first started learning

about logarithms i really did not

get logarithms like it was really quite

a struggle for me

and then i studied them very very hard

because i wanted to understand

and then start like built that intuition

and now it's one of

the pieces of math that i have most

deeply embedded in my reasoning

i have a theory that this is the case

for every idea or book

that was like a foundational step change

if you even go back and read some

classic literature

it seems so boring because so many

derivative works have been created that

you're familiar with it before you come

across it in the first place

yeah like tolkien is this way for me i

actually like i i know that's kind of

heresy i'm sorry

but like lord of the rings when i first

read it

i as a kid i was like this is this is

fine

but i feel like there's a lot of other

like books about elves and

trolls and things like that i don't i

don't really understand why this is such

a big deal

and then i realized oh this is this like

invented those ideas

oh i see it's a big deal there's also a

sense michael

you've alluded to the way that lectures

can have value in a surprising fashion

by

kind of letting you see a person's

thought process

in great detail even if you may not

absorb

kind of detailed information and seeing

their

their value system their their lenses on

the world

play out in the context of detailed

material

is enlightening and i found you know

chapters on digital filters and

simulation

uh to be very much that way do you have

any any final thoughts that

uh you want to close with or final

lightning round questions

maybe let's try this as an experiment uh

if you had to sum

the what you took away from the book in

one sentence what would it be

work hard on problems of interest to the

smartest people you know

it's possible to take very very

seriously

the practices of doing good work

be proud and intentional about creating

a context that allows you to do great

work

i feel we should get gpt 3 to try and

summarize the text

michael doesn't get to get off the hook

though

he's just in putting the text of the

book into gpd3

yeah that's right i'm running it at the

moment give me a minute give me a minute

i'll be inside

uh why i i mean honestly i

i'm not sure i can the things you said

uh really isn't it maybe actually but

research is done by human beings and

having seemed nice and human

all throughout the whole dancing i don't

like that this is a great place to stop

thank you three for for joining

star andy and michael this was super fun

thanks david

you