Kind: captions
Language: en
so what have you learned about the human
abstractions from individual functional
human units to the broader organization
what does it take to create something
special well most people don't think
simple enough all right so do you know
the difference between a recipe and
understanding there's probably a
philosophical description of this so
imagine you're gonna make a loaf of
bread yeah the recipe says get some
flour add some water add some yeast mix
it up let it rise put it in a pan put it
in the oven it's a recipe right
understanding bread you can understand
biology supply chains
you know grain grinders yeast physics
you know thermodynamics like there's so
many levels of understanding there and
then when people build and design things
they frequently are executing some stack
of recipes right and the problem with
that is the recipes all have a limited
scope look if you have a really good
recipe book for making bread it won't
tell you anything about how to make an
omelet right right but if you have a
deep understanding of cooking right then
bread omelets you know sandwich you know
there's there's a different you know way
of viewing everything and most people
when you get to be an expert at
something you know you're you're hoping
to achieve deeper understanding not just
a large set of recipes to go execute and
it's interesting the walk groups of
people because executing reps apiece is
unbelievably efficient if it's what you
want to do if it's not what you want to
do you're really stuck and and that
difference is crucial and ever and
everybody has a balance of let's say
deeper understanding recipes and some
people are really good at recognizing
when the problem is to understand
something DP deeply that make sense it
totally makes sense does it every stage
of development deep on understanding
the team needed oh this goes back to the
art versus science question sure if you
constantly unpacked everything for
deeper understanding you never get
anything done right and if you don't
unpack understanding when you need to
you'll do the wrong thing and then at
every juncture like human beings are
these really weird things because
everything you tell them has a million
possible outputs all right and then they
all interact in a hilarious way and then
having some intuition about what do you
tell them what do you do when do you
intervene when do you thought it's it's
complicated all right so it's you know
essentially computationally unsolvable
yeah it's an intractable problem sure
humans are a mess but with deep
understanding do you mean also sort of
fundamental questions of things like
what is a computer or why like think the
why question is why are we even building
this like of purpose or do you mean more
like going towards the fundamental
limits of physics sort of really getting
into the core of the sighs well in terms
of building a computer think simple
think a little simpler so common
practice is you build a computer and
then when somebody says I want to make a
10% faster you'll go in and say all
right I need to make this buffer bigger
and maybe I'll add an ad unit or you
know I have this thing that's three
instructions wide I'm going to make it
four instructions wide and what you see
is each piece gets incrementally more
complicated right and then at some point
you hit this limit like adding another
feature or buffer doesn't seem to make
it any faster and then people say well
that's because it's a fundamental limit
and then somebody else to look at it and
say well actually the way you divided
the problem up and the way that
different features are interacting is
limiting you and it has to be rethought
rewritten right so then you refactor it
and rewrite it and what people commonly
find is the rewrite is not only faster
but half is complicated
from scratch yes so how often in your
career
just have you seen as needed maybe more
generally to just throw the whole out
everything out this is where I'm on one
end of it every three to five years
which end are you on like rewrite more
often right and three to five years is
so if you want to really make a lot of
progress on computer architecture every
five years you should do one from
scratch so where does the x86 64 Center
come in or what how often do you I wrote
the I was the co-author that's back in
98 that's 20 years ago yeah so that's
still around the instruction set itself
has been extended quite a few times yes
and instruction sets are less
interesting and the implementation
underneath there's been on x86
architecture Intel's designed a few aims
is designed a few very different
architectures and I don't want to go
into too much of the detail about how
often but it's there's a tendency to
rewrite it every you know 10 years and
it really should be every 5 so you're
saying you're an outlier in that sense
in really more often we write more often
well in here isn't that scary yeah of
course
well scary - who - everybody involved
because like you said repeating the
recipe is efficient companies want to
make money well no in the individual
juniors want to succeed so you want to
incrementally improve increase the
buffer from three to four well we get
into the diminishing return curves I
think Steve Jobs said this right so
every you have a project and you start
here and it goes up and they have
Domitian return and to get to the next
level you have to do a new one in the
initial starting point will be lower
than the old optimization point but
it'll get higher so now you have two
kinds of here
short-term disaster and long-term
disaster and your your ops right like
you know people with a quarter by
quarter business objective are terrified
about changing everything yeah and
people who are trying to run a business
or build a computer for a long-term
objective know that the short-term
limitations block them from the
long-term success so if you look at
leaders of companies that had really
good long-term success every time they
saw that they had to redo something they
did and so somebody has to speak up or
you do multiple projects in parallel
like you optimize the old one what
you've built a new one and but the
marketing guys they're always like make
promise me that the new computer is
faster on every single thing and the
computer architect says well the new
computer will be faster on the average
but there's a distribution or results in
performance and you'll have some
outliers that are slower and that's very
hard because they have one customer
cares about that one
you