Pioneers: A roundtable on Richard Hamming
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
📘「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。
🔍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。
🤔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。
📈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。
🌟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。
🚀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
💡システム工学
💡問題解決
💡研究文化
💡自己評価
💡感情的関与
💡競争
💡オープンサイエンス
💡問題発見
💡コミュニケーション
💡未来予測
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
5.0 / 5 (0 votes)