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From YouTube: What Cloud Computing Can Learn from Neuroscience: How the Brain Architects 'Cloud Applications'
Description
What Cloud Computing Can Learn from Neuroscience: How the Brain Architects 'Cloud Applications' [I] - David Flanders, University of Melbourne, Australia
"The wisest and noblest teacher is nature... one who loves practice without theory is like the sailor who boards the ship without a rudder and compass and never knows where one may cast." (Leonardo da Vinci).
All great science begins in nature, and it is often this simple metaphor we forget about when attempting to explain the code we want to spend months (if not years) building for our users.
This presentation asks a simple question: what can cloud computing learn from the architecture of the brain (neuroscience). An overview of recent neuroscience will be provided as a metaphor for how we build cloud applications. Like any good scientific theory it will ask more questions than provide answers.
About David Flanders
Computer scientist and neuroscience, exploring what we can learn from millennia of lessons the brains' evolutionary architecture has for building cloud applications.
Join us for KubeCon + CloudNativeCon in Barcelona May 20 - 23, Shanghai June 24 - 26, and San Diego November 18 - 21! Learn more at https://kubecon.io. The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy and all of the other CNCF-hosted projects.
A
It
was
developed
with
f-16
fighter
pilots
and
what
you
do
is
you
hold
your
breath
and
then
they
say
it's
bear
down,
but
really
you
pretend
you're
having
a
poo
and
what
that
does
is
it'll
push
oxygen
up
into
your
brain,
so
just
hold
your
breath
and
then
just
pretend
you're
pushing
down
on
your
lower
stomach
and
that
will
help
push
oxygen
up
into
your
brain,
so
not
a
bad
thing
to
do
after
a
long
set
of
conferences
and
all
the
rest
of
it.
So
maybe
you
have
a
goal
of
that
real,
quick
all
right.
A
A
Nonetheless,
Who
am
I
I'm,
David
Flanders,
most
people
call
me
Flanders,
thanks
to
some
television
show.
The
thing
you
kind
of
get
it
you
need
to
know
about
me
is
I've,
been
working
in
the
past
15
years,
I've
been
working
inside
of
universities
in
UK
and
Portugal,
and
the
u.s.
currently
in
Australia
and
getting
to
work
with
really
cool
scientists
and
doing
stuff.
A
So
in
fact,
recently
I
I
gotta
work
I've
been
working
for
the
past
five
years,
with
neuro
scientists
with
functional
magnetic
resonance
imaging
machines
at
seven
Tesla
machine
which,
if
you
don't
know,
is
a
magnet,
it's
so
powerful.
It
can
pull
cars
off
the
road.
So
we
have
to
line
the
entire
thing
in
topper
I'm
going
to
pass
this
around
because
it
actually
shows
the
parts
of
the
brain
that
I'm
going
to
be
talking
about
today.
This
is
my
brain,
so
please
be
careful
with
it
and
I
apologize.
I
have.
A
I
have
done
a
little
bit
of
operations
on
that,
so
there
there's
a
couple
of
problems
inside
that.
So
what
I'm
going
to
show
you
today
is
actually
a
proposed
architecture,
so
I've
been
trying
to
think
about
how
to
build
applications
for
some
neuro
scientists,
a
simulation
and
so
I'm
kind
of
putting
it
out
to
all
of
you.
You're
the
experts
you're
you're,
the
just
quickly
to
check
who
are
operators
in
the
room
DevOps,
who
are
application
developers
in
the
room?
A
Excellent,
so
I
really
want
feedback.
So
at
the
party
tonight
I'll
buy
you
some
beers,
let's
have
a
chat
and
goodness
the
beers
are
free.
Please
come
talk
to
me
because
I
would
really
like
guidance
on
that
I
work
currently
at
the
OpenStack
foundation,
I'm
on
secondment
there
so
glad
to
talk
about
OpenStack
stuff
as
well.
A
If
you
want
guidance
on
that,
so
to
get
us
going
to
play
a
little
game,
I'm
going
to
take
us
up
really
high
level
and
then
I'm
going
to
work
our
way
down
and
then
we'll
come
back
up
and
to
do
that
I'm
going
to
play
just
a
quick
game
here,
so
I've
got
some
swag.
These
events
are
all
about
the
swag
I've
discovered
and
the
game
is
quite
simple.
As
trying
to
identify
these
vocabulary,
words
of
these
metaphors,
we
use
so
obviously
pods
cube
node
and
clusters
q
burnetii.
A
Can
anybody
tell
me
what
engine
client
hub
and
damen
might
be?
Yes?
Yes,
could
you
come
claim
your
prize?
Who
else
said
docker?
Would
you
like
a
hat
or
a
next
one,
the
bucket
traffic
and
charts?
Anyone
know
it
when
that
one
is
what
nope
close
Deus.
It
has
a
lot
of
people
on
this
project,
helm
and
then
the
last
one.
Did
you
want
this
this
instead
open
static,
cast
Sean
anyone
want
the
extra
one
I
don't
need
to
take
it
home,
okay,
so
I
think
we
all
know
this.
A
So
to
go
back
in
time.
We
can
all
remember
our
fearless
leader
of
infrastructure
who
pioneered
the
cause,
Al
Gore
with
information
superhighway
that
gets
signed
into
a
presidential
act
and
it's
all
a
very
important
thing.
Now.
The
question
is,
is
if
there's
validity
behind
this-
and
there
is
some
validity
of
cited
some
research
behind
it,
which
is
the
fact
that
over
time
infrastructure
there
is,
there
is
a
precedent
for
it
canals
railways,
Telegraph's
pipelines.
They
all
have
this
adoption
curve.
A
So,
on
the
vertical
there,
you
have
the
percentage
in
the
United
States
of
those
infrastructure
being
adopted,
and
then
the
year
on.
The
horizontal,
of
course,
keep
in
mind
that
in
1800
there
wasn't
50
states,
there
was
less
than
number
of
states.
Hence
why
it's
percentage
on
that
side
and
to
tell
you
the
truth?
The
internet
really
is
no
different.
A
It
is
a
very
common
infrastructure,
which
is
an
important
point
because
we're
at
about
forty
three
percent
we're
actually
over
that
now,
which
is
about
that
median
range
of
adoption
of
infrastructure
and
things
happen
to
infrastructure.
Once
you
get
past
that
median
range
and
that's
kind
of
the
question
I
have,
is
whether
or
not
we've
solved
the
what
Bezos
called
the
undifferentiated
heavy
lifting
problem
and
kerber
Nettie's
is
amazing.
It's
it's.
It's
that
ability
to
say
we're
no
longer
need
going
to
need
to
worry
about
the
heavy
lifting
problem.
A
The
machine
is
going
to
take
care
of
that.
For
us,
it's
all
going
to
be
automated,
so
the
question
to
you
that
I
have
is:
do
we
need
to
switch
metaphors?
Do
we
need
to
be
thinking
about
if
this
is
truly
an
application
developer
community
about
enabling
the
next
level
of
applications?
What
the
next
metaphor,
that's
going
to
lead
us
on,
so
like
any
good
researcher,
I'm
going
to
ask
more
problems
than
I'm
going
to
provide
solutions,
but
this
is
one
that
I
will
push
you
on.
A
A
So
the
thing
that
I
want
to
explore
with
you
and
talk
about
is
a
new
metaphor.
Is
this
idea
of
neurobehavioral
theory
of
computational
intelligence,
so
principles
of
intelligence
and
I'm
sure
all
of
you
have
seen
the
AI
Fox
I'm
not
talking
about
hard
AI,
I'm
not
talking
about
turing-complete
AI
I'm,
actually
talking
about
what
most
would
call
soft,
narrow
or
weak
AI.
A
So
my
metaphor,
for
you
is
this-
is
that
just
like
Leonardo
da
Vinci
tried
to
figure
out
the
principles
of
flight,
so
do
we
need
to
figure
out
the
principles
of
intelligence
if
we're
going
to
build
the
next
level
of
application
and,
of
course,
the
principles
of
flight
being
lift
weight,
gravity,
thrust
and
drag.
So
the
fundamental
question
is
what
are
the
principles
of
intelligence
so
that
we
can
start
to
build
applications
that
have
intelligence
in
them
so
that
they
can
fundamentally
replace
jobs
and
automate
those
parts
of
our
lives?
A
So
again,
some
further
research
in
this
is
that
there's
some
good
work
done
by
Gardner
and
83
trying
to
die
at
what
are
the
different
types
of
intelligences
I'm.
Sure
many
of
you
have
seen
this
and
how
important
that
is,
and
one
of
the
really
fundamental
questions
here
is
which
of
these
intelligences
will
be
the
ones
that
we
need
to
replace?
A
What
are
the
things
that
what
are
the
applications
which
are
going
to
be
able
to
do
this
and
is
the
infrastructure
that
we
currently
have
the
architects
and
the
metaphors
that
we
currently
have
for
building
this
stuff?
That
corrects
the
correct
ones,
the
big
money
symbol
there
in
the
middle
is
because
I
do
believe
this
will
probably
come
down
to
what
saves
us
the
money
the
fastest.
So
there
will
be
a
big
push
in
being
able
to
achieve
that.
A
Another
just
quick
note:
the
current
AI
we
have,
and
we've
been
through
a
couple
of
these
AI
winters
I
was
part
of
the
Semantic
Web
movements.
Anyone
remember
Semantic,
Web
back
in
the
day.
Hauler
is
that
we
do
go
through
these
AI
winters
in
the
right.
Ai
is
really
there's
nothing
special
about
it.
We're
still
using
the
same
algorithms
that
were
used
were
invented
in
the
80s
and
90s.
A
It's
just
that
we
have
more
data
to
work
with
now,
so
the
compute
in
the
data
changes
and
that's
really
what
is
exciting
about
coober
Nettie's,
in
my
opinion,
for
them.
Okay,
so
I've
gone
high
up
and
given
you
all
fluffy
thoughts
to
think
about
now,
I'm
going
to
drop
down
and
try
to
come
from
the
bottom
up
and
talk
a
little
bit
about
the
way
we
could
potentially
build
applications
around
this.
This
space,
so
part
1,
I'm
going
to
talk
about
the
neuropsychology
circuit,
so
just
to
give
you
a
really
fun
simple
overview.
A
Any
neuro
scientists
in
the
room
by
champs
come
correct
me
if
I'm
wrong
on
all
of
these
things.
I
am
I,
am
neither
a
good
computer
scientist
nor
a
good
neuroscientist,
so
I'm
always
looking
for
feedback
in
part.
Two
will
actually
kind
of
conduct
a
little
experiment
and
look
at
the
way
we
could
actually
architect
what
is
known
as
an
addiction
circuit.
A
The
addiction
rewards
ticket
in
addiction,
reward
circuit
in
Coober,
Nettie's
and
openstack,
and
then
finally,
we'll
again
ask
some
big
fluffy
questions
since
it's
late
in
the
afternoon,
and
I've
only
got
30
minutes
to
go
through
this.
So
it's
very
hard
to
get
through
any
of
these
things
in
in
a
30
minute
lecture,
let
alone
at
least
an
hour
and
a
half
lecture.
Normally.
So,
okay,
let's
dive
in
but
before
we
dive
in
I,
am
going
to
need
to
give
you
all
a
little
bit
of
a
crash
course
in
neuroscience.
A
So
I
need
you
all
to
hold
up
your
hand
please,
and
we're
basically
going
to
go
through
the
way
that
our
brain
is
layered
architected,
so
down
here
is
actually
your
central
nervous
system.
What
is
your
spine,
which
is
connected
to
your
peripheral
nervous
systems?
Your
six
senses?
Yes,
we
have
six
senses,
then
down
here
right
here
on
the
soft
part
of
your
hand.
Here
this
will
be
your
cerebellum
and
your
brain
stem.
A
I'll
also
just
quickly
note,
orcas
and
dolphins
actually
have
another
layer
sitting
on
top
of
that,
which
is
pretty
cool,
if
you
actually
think
about
it
and
then,
most
importantly,
the
reason
why
the
ice
cream
cone
is
there
is
because
evolutionarily
those
have
all
kind
of
melted
together.
That's
how
they've
evolved,
those
are
the
layers
and
then
they've
kind
of
compacted
down.
So
that
is
your
30-second
crash
course
in
neuroscience,
now
I'm
going
to
go
down
and
actually
talk
about
the
way
a
circuit
works
inside
the
brain,
so
there's
actually
really
great.
A
Research
has
been
going
on
to
the
1900s
about
dissecting,
the
brain
and
looking
at
the
way
the
neurons
are
mapped
and
how
neurons
are
connected.
So
these
addiction
circuit
is
really
well
is
really
well
understood
and
there's
a
lot
of
research
on
it.
So,
first
off,
though,
we
can't
forget,
there's
actually
a
big
problem
in
the
neuroscience
community
and
that
we
separate
the
behavior
away
from
the
circuit,
we're
so
obsessed
with
the
genetics
and
the
chemicals
and
what's
actually
happening
inside
the
circuitry
of
the
brain.
A
We
forget
that
the
whole
point
of
this
is
to
produce
behavior
to
actually
get.
It
helps
people
to
do
things
so
I,
don't
want
you
to
forget
about
this.
What
we're
really
talking
about
here
is
trying
to
understand
the
way
that
we
do
have
these
behaviors,
so
obviously
tonight
we're
all
waiting
for
the
party
tonight.
So
we
have
this
preoccupation
and
anticipation
for
having
some
beers
tonight.
A
Then
tonight
we're
going
to
all,
enjoy
and
get
intoxicated
and
have
a
couple
of
chaste
and
you're
going
to
come
talk
to
me
about
how
I
can
better
architect
this
solution
and
then
tomorrow
morning,
without
those
chemicals
in
our
brain,
we're
going
to
have
a
little
bit
of
withdrawal
now
what's
cool
about
this
circuit?
Is
that
because
of
things
like
the
the
neocortex
and
all
the
rest
of
it,
we
can
actually
hack
the
circuit
right.
A
So
we've
actually
got
some
executive
function
in
the
form
of
being
able
to,
you
know
actually
say
no
I,
don't
want
to
drink
tonight
or
I'm,
not
going
to
drink
in
excess
and
so
forth,
and
so
on.
So
there's
neuro
adaption.
So
algorithms
and
executive
functions
interventions
things
like
actually
taking
other
drugs
which
will
counteract
to
the
drugs
that
we've
taken
or
behaviors.
We
have
or
interventions,
also
like
therapy
actually
sitting
down
with
a
psychologist
and
figuring
out.
A
So
I'm
going
to
walk
you
through
the
circuit
of
the
way
that
the
addiction
reward
brain
circuit
works.
So
what
we
start
as
we
start
in
the
peripheral
nervous
system.
So
I'm
standing
here,
I'm
picking
up
the
senses
and
everything,
and
so,
if
I
decide
to
smoke
or
if
I
decide
to
have
a
drink,
that's
going
to
put
chemicals
into
my
digestive
system
and
what's
cool
is
that
you,
the
first
place
is
going
to
actually
hit.
A
Is
the
ventral
tegmental
area,
so
the
ventral
tegmental
area
is
down
there
in
the
core
part
of
the
reptilian
part
of
the
brain.
So
it's
it's!
It's
a
child!
Really
it's
going
to
get
excited
and
say:
oh
I,
like
that
I,
like
all
of
these
things
and
what's
interesting,
then,
is
that
ventral
tegmental.
It
loves
to
fire
off
a
lot
of
dopamine.
So
a
bunch
of
signals
right
and
I
am
going
to
start
to
already
get
into
Kuber
Nettie's
talk
here,
so
think
of
the
ventral
tegmental
area
as
a
micro
service.
A
That's
that's
kind
of
a
fundamental
core
hypothesis
of
the
system.
I
want
to
build
so
that
ventral
tegmental
area
it
fires
off
a
bunch
of
dopamine
to
the
nucleus
accumbens.
The
nucleus
accumbens
sits
up
there
more
in
the
in
the
midbrain.
It's
it's
just
on
the
lateral
end
of
the
stri,
adam
thats.
Try
Adam
is
connected
to
the
hippocampus
and
amygdala
store
the
parts
of
the
brain
which
care
about
memory
and
all
the
rest
of
it,
and
even
though
I'm
walking
this
through
as
a
linear
sequence.
A
Please
remember
these
are
neural
networks,
so
there's
chemicals
and
signals
going
all
over
the
place
in
in
text
speak.
You
know,
there's
API
is
being
pointed
every
which
way-
and
it's
all
talking
to
one
another
in
different
ways.
So
the
nucleus
accumbens,
it
sits
there
and
it
says
I
got
to
think
about
this
right.
I'm,
going
to
make
a
decision
about
whether
or
not
I
should
be
acting
on
all
this
dopamine
and
what's
kind
of
cool
about
the
brain
is.
A
It
is
binary
in
the
sense
that
a
synapse
in
Iran
will
not
fire
until
it
feels
it's
reached
its
action
potential.
So
there
is
a
kind
of
natural
equation
that
we
can
put
between
micros
services.
Ap
is
and
the
way
that
they
talk
with
one
another.
So
once
the
nucleus
accumbens
says,
I
got
to
think
about
that.
It'll
actually,
then
send
additional
signals
over
to
the
orbital
or
the
orbital
frontal
cortex
and
the
orbital
frontal
cortex,
because
it
fits
on
that
advanced
part
of
our
brain.
That's
where
we
can
actually
start
to
make
decisions
now.
A
What's
really
cool
and
I
love
this
bit?
Is
that
once
from
here
this
area
down
here
in
the
substantial
or
started
the
ventral
tegmental
area?
That's
point
zero,
two
seconds
for
our
bodies
to
pick
up
that,
so
I
can
hit
shawn
and
he's
going
to
pick
that
up
right
down
there
in
the
lower
part
of
his
brain
and
it
won't
get
to
his
prefrontal
cortex
up
until
two
seconds
later.
So
the
idea
of
counting
to
ten
is
not
a
bad
idea.
Actually,
when
you're,
when
you're
trying
to
hack
your
own
addiction
circuit.
A
So
finally
from
the
orbital
frontal
cortex,
it
sends
out
all
kinds
of
signals
up
around
the
prefrontal
cortex
and
that's
where
the
decision
is
made
and,
of
course,
that
all
is
feeding
back
into
the
amygdala
and
hippocampus,
where
the
data
store
is,
and
so
what's
really
interesting.
In
cases
like
heroin,
you've
got
the
heroin
is
such
a
powerful
indicator
into
the
hippocampus
and
the
amygdala
that
it
overrides
the
circuit
and
you
actually
don't
access
your
orbital
frontal
cortex
or
your
prefrontal
cortex.
A
You
kick
back
into
like
this
closed
search
of
the
circuit,
where
all
you
can
think
about.
Is
it
feels
so
good?
It
feels
so
good.
It
feels
so
good,
so
you
actually
are
rewiring
your
brain.
Hence
why
you
then
have
to
have
interventions
to
be
able
to
hack
the
circuit
that
packs
the
circuit
so
that
you
can
actually
restrain
'then
just
restrain
'then
the
pathways
Nowra
might
keep
in
mind.
This,
isn't
all
bad.
You
know
rewards
addiction
can
also
be.
A
You
can
also
reverse
it
to
have
good
things
you
know
watching
television
is
a
form
of
addiction.
Coding
is
a
formative
addiction
with
all
of
these
circuits.
This
circuit
is
involved
in
everything
that
we
like
to
repetitiously.
Do.
Okay,
so
I
get
very
excited
about
this
stuff,
because
I
find
it
really
cool
I
do
want
to
just
make
out
one
other
point
about
the
brain
architecture
so
that
you
guys
can
understand
it.
A
A
So
I
was
trying
to
think
of
a
metaphor
for
this,
but
you
know
it's
like
having
so
pressed
you
know
and
several
other
different
rgr
PC
and
several
other
different
protocols
which
are
talking
to
all
your
different
micro
services
and
all
the
rest
of
it,
which
is
a
really
hard
part
to
model,
but
we'll
go
back
to
that
later.
So,
let's
go
into
the
idea
of
you
know
what
would
this
actually
look
like
if
we
tried
to
model
it,
and
this
is
really
a
version,
what
I
would
call
a
version?
You
know
0.
A
It
was
a
0.01
but
being
able
to
be
at
this
conference
and
go
around
and
listen
to
you
all
and
try
to
figure
out
all
these
things.
I
keep
updating
my
my
architecture
diagram
to
see
if
I'm
thinking
about
this
all
the
right
way,
but
it
to
be
honest.
It's
been
really
difficult
as
an
application
developer
to
understand
how
or
where
to
get
the
best
advice
and
guidance
for
this.
A
So
I
think
this
community
really
needs
to
think
about
how
application
developers
can
bring
problems
like
this
and
sit
down
with
dev,
ops
or
application
or
network
engineers
or
system
engineers.
So
we
can
figure
out
how
these
things
work
and
that's
really
how
we're
only
going
to
be
able
to
achieve
these
next
level
of
intelligence
applications
is
through
cross-disciplinary
efforts.
We're
not
we're
not
going
to
do
this
with.
You
know
a
front
end
and
a
back-end
dev
in
a
garage.
That's
just
not
the
way
we're
going
to
we're
going
to
build
these
next
level
applications.
A
So,
as
any
scientist,
you
got
to
put
forward
a
hypothesis.
Basically
it's
a
very
simple
hypothesis.
If
we
model
the
neuro
behaviors
of
addiction
as
microservices,
then
the
computer
will
be
able
to
simulate
computational
signs
of
becoming
addicted.
I
should
say,
but,
as
I
show
this
architecture,
this
architecture
is
somewhat
based
on
climate
science
and
the
way
climate
scientists
do
simulations
or
what
they
look
at
is
they're
able
to
put
data
into
their
models.
So
they
can
say
you
know
for
the
weather
patterns
or
water
patterns
or
barometric
patterns
so
forth,
and
so
on.
A
They're
able
to
input
that
data
and
then
be
able
to
understand
how
it
works.
So
the
key
part
of
this
some,
the
key
part
of
this
diagram
is,
of
course,
being
able
to
have
these
pods
modeled
on
the
different
parts
of
the
brain,
the
prefrontal
cortex,
the
orbital
frontal,
the
nucleus
accumbens
and
the
ventricular
lateral.
So
each
one
of
these
that's
what
makes
up
the
core
of
the
pod,
but
then
trying
to
figure
out
how
all
these
work
is
where
it
gets
tough,
so
up
here
at
the
top
for
all
the
researchers.
A
So
what
I
find
most
exciting
in
this
community
is
not
so
much
the
pods
or
the
automation,
it's
actually
the
cic
d
stuff.
Can
we
get
researchers
to
work
in
parallel
to
be
able
to
update
this
simulation
system,
to
be
able
to
do
things
together?
I'll
go
into
that
more,
but
we
need
to
be
able
to
actually
change.
A
So
there
needs
to
be
some
effort
in
that.
Last
but
not
least,
I
did
add
this
layer,
which
is
maybe
we
do
need
some
kind
of
paths
or
cast
to
enable
researchers
to
get
involved
so
that
they
can
have
a
way
of
understanding
how
to
pull
out
these
pods,
adjust
them
and
do
new
things,
and
then,
of
course,
we
have
to
have
the
ops
and
app
dev
involved,
because
most
of
these
researchers
have
no
idea
how
to
do
some
of
this
stuff.
A
Barely
can
I
get
them
to
use
github
and
understand
why
github
is
a
valuable
tool,
let
alone
why
why
coober,
Nettie's
or
containers
or
anything
else
should
matter
to
them.
So
it
really
is
about
having
that
full
set
of
people.
Also,
a
registry
there's
a
lot
of
questions
here
about
you
know
if
we
add
an
SQL
database
or
we
need
a
another
form
of
data
form
that
sits
inside
of
these
pods.
That's
a
big
question
for
me
as
well.
A
Last
but
not
least,
I'll
just
kind
of
show
this.
This
is
why
I
think
that
Kuber
Nettie's
offers
a
really
exciting
new
potential
for
research.
Scientists
be
able
to
model
this
stuff
so
having
a
brain
region
such
as
the
nucleus
accumbens,
being
able
to
have
the
different
synapse
receptors
in
there,
so
actually
being
able
to
say
here's
the
dopamine
receptor
pathways
that
we'll
be
able
to
talk
between
these
things
and
finally
being
able
to
load
different
algorithms.
A
So
last
but
not
least,
you've
always
got
to
justify
to
government
when
you're
spending
research
money.
You
know
what
its
potential
applications
are.
So
you
know
that
a
lot
of
these
are
made
up,
but
it
would
be
cool
to
have
something
like
a
reward
addiction
as
a
service.
You
could
indeed,
so
you
could
imagine
something
like
hue
bulbs
coming
along
and
actually
being
able
to
try
to
model
changing
your
addiction
behavior
for
falling
asleep.
A
A
lot
of
developers
sit
somewhere
on
the
continuum
either
depressed
or
have
you
know,
ADHD
or
I
have
a
bit
of
ADHD
myself,
as
you
can
tell
or
autism,
so
it's
hard
for
us
to
sometimes
define
normal
sleeping
patterns.
So
maybe
you
know
our
I
RT
devices
could
actually
help
us
modify
the
way
our
brains
work
and
actually
they
help
us
to
have
good
sleeping
patterns,
which
we
know
will
lead
to.
You
know
more
productivity,
better
efforts
and
so
forth
and
so
on,
and
then
just
on
the
whole.
A
It
really
is
about
a
platform
that
enables
researchers
to
come
together
and
simulate
what
they're
seeing
inside
of
whether
they're
using
fMRI
or
whether
they're
using
a
pet-ct
or
even
time,
series
data
on
the
way
the
brain
works
so
a
place
for
all
that
data
to
go
and,
most
importantly,
a
place
where
it's
being
done
with
commodity
computing,
because
HPC
is
very
expensive
to
do.
It's
not
easy
for
people
to
get
access
to
that.
A
Last
but
not
least,
I
just
want
to
kind
of
make
the
point
that
we
we
really
do
need
to
think
about
how
to
integrate
crew,
brunette
ease
with
other
systems.
It's
it's
really
cool.
When
we
get
this
new
technology,
I
get
really
excited,
and
my
poor
wife
had
to
hear
about
this.
You
know
why
Cooper
Nettie's
was
really
going
to
help
change
the
way
researchers
did
things,
and
yet
there
are.
A
There
are
sticks
in
the
mud
that
just
aren't
going
to
change
the
phrase
you
know
the
rate
of
progress
will
be
as
fast
as
coffins
going
into
the
ground
is
very
true.
There
are
certain
researchers
who
are
not
going
to
move
on
and
even
though
we
get
excited
by
the
new
technology,
there
are
still
old
technologies
which
are
very
real
and
we
need
them.
There's
a
good
reason
why
we
don't
move
on
quickly
and
to
end
on
a
on
a
on
a
somber.
It's
not
depressing
note.
A
I'll
take
us
back
up,
which
is
the
idea
that
you
are
all
involved
in
in
the
job
of
replacing
other
people's
jobs
right
automating
these
things
and
how
many
people
saw
of
what
was
my
name
of
the
film.
The
big
like
I
can't
even
remember
the
big
short,
so
there
is
actual
and
there's
that
famous
scene
in
the
casino
where
he
talks
about
that
you
shouldn't
be
celebrating
by
bidding
against
people
losing
their
jobs,
and
there
actually
is
decent
research
to
show
that
you
know
for
every
one
percent
of
the
population
in
the
u.s.
A
15th
there
is,
there
is
an
increase
in
death,
now
be
careful
in
science
with
cause
and
causation
right.
We
all
know
that,
but
it
is
worthwhile
just
recognizing
that,
for
example,
twenty
percent
of
the
world's
jobs
are
in
transportation
if
we
actually
use
artificial
intelligence
and
its
perception
ability
to
start
to
replace
people
who
drive
to
actually
have
transport
jobs.
We're
talking
about
one
of
the
largest
genocides
in
history.
So
there's
a
good
reason.
Why
I
would
ask
you
all
to
think
about?
Maybe
it's
worthwhile
not
changing
too
quickly.
A
Maybe
there
is
a
reason
why
we
need
to
have
a
steady
hand
and
change
at
a
good
speed
and,
most
importantly-
and
this
is
kind
of
one
of
the
key
messages-
I
really
want
you
all
to
walk
away
with
as
developers
you
sit
at
the
last
line
of
defense
for
ethics
right,
you
know.
In
science
we
have
an
ethics
board,
we've
got
to
go
to
and
make
sure
that
this
is.
This
is
permissible
and
we
can
go
ahead
and
they
get
that
wrong
all
the
time
right.
A
A
This
is
my
fault
that
I
don't
know,
but
it's
amazing
how
that
gender
divide
has
occurred
and
our
need
for
actually
having
a
balanced
inside
of
this.
So
the
final
message
is,
you
know
the
friend,
a
neuro
scientist
or
a
psychologist.
They
are
working
in
the
same
field
as
you
believe
it,
or
not
the
field
of
intelligence
and
they're
trying
to
figure
out
these
problems.
So
I
can
say
this
confidently,
because
you'll
probably
notice
that
the
last
one
has
a
similar
name
to
me.
A
That's
that's
my
wife
she's
a
psychologist
in
a
neuroscientist,
and
we
love
talking
about
this
stuff
and
it
really
does
offer
really
exciting,
put
possibilities
and
help
further
for
for
Humanity
and
being
able
to
change
things
rather
than
just
make
money.
So
that's
that's
kind
of
my
final
message.
Please,
please,
please,
come
and
share
a
beer
with
me
tonight.
Enjoy
the
addiction
circuit
a
little
bit
with
me
and
come
tell
me
how
I
can
fix
this,
how
it
can
be
better?