►
Description
Juan Benet is the founder of Protocol Labs (YC S14). They’re working on IPFS, Filecoin, and CoinList - https://twitter.com/juanbenet
Dalton Caldwell is a Partner at YC - https://twitter.com/daltonc
Read the transcript: http://blog.ycombinator.com/ipfs-coinlist-and-the-filecoin-ico-with-juan-benet-and-dalton-caldwell/
YC's podcast is hosted by Craig Cannon - http://twitter.com/craigcannon
A
A
If
you're
just
getting
into
cryptocurrency
I
highly
recommend
listening
to
episode,
244
of
Tim
Ferriss
podcast,
which
does
a
pretty
good
job
of
covering
all
the
terms
and
explaining
how
they
all
connect
to
each
other
and
before
we
get
started
I
want
to
let
you
know
that
this
is
a
really
long
episode,
so
it's
pretty
much
broken
up
into
three
parts.
Part
one
starts
right
after
this
and
it's
ones
explanation
of
ipfs
and
file
coin.
Part
two
is
our
conversation
with
Dalton,
and
that
starts
around
minute.
11
and
part.
A
B
Protocol
Labs
is
a
research
development
and
deployment
lab
for
networks
that
I
started
to
really
build
the
IPS
ops
project
and
build
file
coin
and
create
a
place
where
we
could
create
the
kinds
of
projects
that
you
know
could
turn
into
something
like
a
faster
file
coin
or
other
other
things.
I
really
wanted
to
build.
An
organization
that
you
know
someone
like
Satoshi
could
have
seen
as
a
way
to
to
build
a
project
through
it
be
like.
Oh.
B
Of
doing
this,
on
my
own
anonymity,
I
could
go
and
like
the
open
protocol
apps
and
it
is
born
out
of
a
you,
know,
personal
frustration
where,
when
I
was
starting,
that
defense
project
I
didn't
have
such
an
organization
that
I
could
go
to
and
go
and
build
a
project.
They're
really
asking
is
the
only
option
was
either
university
or
Google
and
in
the
university
case
it
would
have
been
killed
and,
in
the
you
know,
publisher
perished
world
where,
like
hey.
B
So
it's
not
that
that
probably
shouldn't
have
been
funded
or,
in
you
know,
direct
control
by
Google
and
it's
the
kind
of
stuff
that
that
I,
that
has
the
potential
to
to
really
rebalance
power
on
the
on
the
internet,
and
so
you
know,
figured
I
would
I
would
start
an
organizational
separate
in
the
protocol.
Apps
is
really
a
group
that
is
trying
to
create
a
number
of
these.
You
know
projects
and
protocols
around
things
that
we
think
are
broken
on
the
internet
and
kind
of
like
we,
the
charge
that
we
have
for
ourselves.
B
The
mission
that
we
have
is
to
you
know,
go
and
improve
and
upgrade
a
whole
bunch
of
the
the
software
and
protocol
machinery
that
we
have
running
the
internet.
Both
you
know
in
low-level
actually
internet
part
or
like
the
web
and
like
more
more
users
user
facing
pieces,
and
we
have
a
very
open-ended
kind
of
perspective
of
like
hey.
We
just
want
to
improve
computing
in
general
and
improve
the
pipeline
of
going
from
research
to
to
a
product
that
people
use.
B
It
just
happens
that
so
now,
and
for
the
next
few
years,
we're
super
focused
on
on
how
information
moves
around
the
internet,
how
how
to
distribute
it
better.
How
to
you
know,
change
and
rebalance
power,
associated
information,
give
people
sovereignty
of
data,
give
people
and
just
make
the
inner
more
efficient
to
make
it.
You
know
route
around
things
like
you
know,
attacker
and
hostile
censorship
make
it
so
that
you
know
information
has
more
permanence,
a
whole
bunch
of
questions
around
this,
and
you
know
the
two
projects
there
are.
You
know
one
of
them
is
hype.
C
B
You
know
the
it's
a
protocol,
it's
a
peer-to-peer
protocol
for
moving
around
anything
any
kind
of
content
files
data.
You
know
hyper
media
whatever
in
a
peer-to-peer
way,
and
you
know
with
proper
content
dressing
and
your
cryptographic,
verification
and
all
this
kind
of
stuff
and
a
whole
bunch
of
tooling
around
the
guts
of
making.
B
People
want
to
address
things
by
what
they
are,
not
where
they
are
like
it's
really
time.
It's
kind
of
like
it's
time
for
the
internet,
to
move
from
location,
addressing
to
content
dressing
and
in
a
big
way,
we've
been
I,
guess
appointed
to
do
so
and
we
have
to
slog
through
the
really
hard
work.
That
is,
that
is
doing
that
and
we're
doing
it
and
it's
great
and
we're
committing.
But
you
know,
there's
more
to
go.
There's
a
lot
more
to
go
with.
B
A
making
human
readable
names
yeah
so
yeah,
so
human
readable
names
are
an
interesting
question.
Human
readable
names
should
map
to
content
and
people
should
use
them
when
they
know
and
are
aware.
That
name
is
now
subject
to
a
consensus.
Protocol
right
like
in
a
way
human
readable
names
either
require
a
consensus.
B
So
you
know
it
kind
of
Maps
more
to
how
humans
think
about
names
were
like
you
know,
I
might
call
a
friend,
Jeremy
and
I
know
him
as
Jeremy,
but
in
you
know
he
actually
might
have
last
name
as
well,
and
he
might
have
other
names
that
he
goes
by
on
the
internet
and
and
other
people
call
other
people
Jeremy
right
and
so
gns.
It's
an
interesting
or
the
approach
of
using
trust,
graphs
and
and
so
on,
or
social
networks
to
name
people.
B
And
so
you
know
you
really
are
stuck
with
consensus,
and
so,
when
you
construct
with
consensus,
you
either
have
something
hierarchical
like
DNS
and
so
on,
or
you
have
something
like
watching
naming
so
like
namecoin
or
ENS,
or
blocks
acts,
and
you
you
have
a
situation
where
human
real
naming
is
important
for
people
to
type,
but
I
think
we
have
like
its
massive
addiction
in
human
readable
naming
where
it
shouldn't
be
used
in
a
lot
of
places
because
it
brings
in
a
whole
bunch
of
baggage
around
hey.
Now
you
need
a
consensus
system.
B
Now
you
need,
like
a
network
stack
now.
You
need,
like
a
whole
bunch
of
things
that
normally
you
shouldn't
need
to
just
address
or
point
to
some
information,
and
so
you
know
we
still
want
hashes
to
be
the
main
thing
that
people
used
to
link
to
things
just
may
be.
You
know
allow
human
readability
as
an
entry
point
to
all
of
that.
Okay,.
C
B
B
You
know,
provide
storage
and
provide
a
valuable
service,
and
so,
in
the
you
know,
old
peer-to-peer
tradition,
people
would
just
resource,
sharing
and
kind
of
try
and
hope
to
achieve
like
a
right
balance.
It's
ensuring
that
that
works
for
some
use
cases,
but
doesn't
work
for
others
and
what
was
really
missing.
There
was
like
understanding
that
this
is
actually
a
spectrum
where,
on
one
end,
some
people
contribute
massive
amounts
of
storage
and
I'm.
Not-
and
you
know,
don't
really
need
to
use
the
than
I
would
very
much
on
the
other
end.
B
That
also
causes
a
valuable
side
effect
and
that
valuable
side
effect
is
hey?
You
have
to
store
a
whole
bunch
of
files
in
order
to
you
know,
have
power
in
the
consensus,
and
so
a
way
of
framing
it
is
that
the
file
coin
consensus,
if
you
want
to
participate
in
the
faculty
consensus
and
maintain
the
pass
on
blockchain.
What
what's
counted
is
not
your
CPU
Rob
power
as
your
as
your
influence
over
the
consensus,
but
rather
the
amount
of
storage
you
are
providing
to
the
rest
of
the
network,
and
so
for
that
we
use.
B
B
You
know,
independently
in,
like
you
know,
doesn't
mean
like
different
physical
hardware,
but
rather
it
means
that
a
different
array
of
bytes
somewhere
is
being
used
to
sort
of
this,
and
you
can't
duplicate
that
and
that
you
can't
cheat
it
in
that,
like
you
can't
generate
like
you,
can't
pre
generate
a
lot
of
the
the
content
and
cheat
this.
We
have
a
very
specific
problem,
but
but
a
the
thing
there
is
following
with
this:
different
work
function
can
organize
massive
amounts
of
storage
to
then
sell
in
the
network.
B
So
you
get
a
lot
of
people
to
mine
the
currency
and
in
you
know,
you
have
a
very
strong
incentive
to
mind
the
currency,
and
then
you
can
sell
all
the
storage
that
supply
that
comes
on
just
to
users
and
select
up
to
you
know,
mediate
this
this.
It's
a
blocking,
empower,
decentralized,
storage
network
is
the
way
that
we
can
think
about
it.
C
B
Good
and
so
it's
probably
2013
late,
2013
or
so
I've
been
working
on
a
whole
bunch
of
knowledge
tools.
So
this
means
software
tools
that
can
help
you
learn
faster
or
help
scientists
under
like
figure
out
what's
in
papers
and
so
on.
Better
and
I
found.
This
really
annoying
problem,
which
is
datasets
like
scientific
data
sets,
were
not
well
versioned,
we're
not
well
managed,
and
so
on
and
there's
a
whole
bunch
to
that
problem.
B
And
so
what
really
seem
to
be
missing
was
the
sort
of
combination
of
getting
BitTorrent
that
would
enable
these
datasets
to
be
distributed
worldwide,
well,
versioned
and
so
on,
and
so
that
sent
me
on
a
on
a
on
a
path
of
ree-ree,
engaging
with
a
whole
bunch
of
stuff
that
I'd
been
thinking
about
prior,
like
many
years
before
a
lot
of
peer-to-peer
stuff.
So
I
did
my
background,
is
in
industry,
assistance
and
networking
I
studied
at
a
Stanford
and
so
at
the
time.
B
C
A
C
One
thing
that
we
noticed
is
how
hard
it
was
for
users
to
get
the
negative
side
effects
of
having
something
just
having
something
that
is
peer-to-peer.
Bittorrent
works
pretty
well,
but
even
Skype
Skype
kept
it
really.
You
didn't
know
there
was
unless
you're,
unless
you're
upstream
bandwidth
with
saturating,
and
it
got
a
nasty
letter
from
your
ISP
or
something
you
had
no
knowledge
as
a
user
and
so
sort
of
my
takeaway
during
that
era.
Was
that
usability
always
trumped
the
elegance
of
peer-to-peer
models
and
then,
when
I
saw
YouTube
take
off.
C
Youtube
is
exactly
the
sort
of
thing
you
would
expect
to
be
built
on
top
of
BitTorrent,
but
in
fact
it
was
entirely
centralized
and
they
were
streaming
everything
themselves,
but
holy
cow,
because
it
worked
so
well
in
flash
video
work
so
well.
The
culmination
of
those
events
happened,
and
so
my
kind
of
knowledge
going
into
this
of
even
for
the
you
know,
going
back
to
your
story
in
a
second
is
usability
to
me
as
such
as
a
such.
An
important
concept
to
have
these
distributed
systems
get
used
by
end-users.
Absolutely.
B
Mean
very
I
think
famously
I
think
drew.
Houston
has
even
pointed
out
how
there
were
a
whole
bunch
of
clunky
sync
file-sharing:
sync
things
that
that,
like
really
just
did
not
work
and
the
big
you
know
the
big
thrust
of
Dropbox
for
a
while
was
just
get
usability
right,
get
the
user
experience
flawless
and
it
almost
as
a
matter
what
you
do
underneath
the
hood
as
long
as
you,
as
you
make
sure
the.
C
B
Then
there's
like
this
other
fundamental
difference,
which
is
that
yes,
absolutely
building
these
systems
is
hard
and
you
have
to
pay
attention
to
the
UX,
but
there's
a
whole
bunch
of
places
where
economically,
it
makes
a
ton
of
sense
to
do
something
better
and
to
do
something
that
has
a
different
arrangement.
I
think
there
were
a
whole
bunch
of
prop
like
there
was
a
period
of
time,
basically
from
2003
to
2009
or
so
we're
pure
appear
was
sort
of
dead
and
I
sort
of
call
it
like
a
peer-to-peer
winter
similar
to
the
AI
winter.
B
Like
you
know,
there's
been
a
series
of
AI
winters
that
was
kind
of
like
the
peer-to-peer
winter
and
there's
probably
was
where
more
peer-to-peer
went
just
before,
because
peer-to-peer
is
actually
pretty
old
concept.
A
lot
of
people
have
been
been
struggling
with
the
differences
between
making
things
with
peer-to-peer
or
centralized
since
the
beginning
of
the
internet.
So
I
think
there's
a
whole
bunch
of
reasons
why
a
lot
of
the
companies
failed
that
were
getting
built
around
that
time
were
products
failed
and
why
they
were
very
few
success
stories,
so
I
think
Skype.
B
In
return,
probably
the
biggest
success
stories
were
from
that
entire
time
and
yeah
I
think
Skype.
You
know,
didn't
really
talk
about
peer-to-peer
very
much
yeah
and
BitTorrent.
You
know
slide
from
Blizzard
and
a
few
others
like
it
was
mostly
used
for
for
moving
around
a
lot
of
you
know,
movies
and
so
I
think.
B
What
are
the
underlying
you
know
from
like
a
research
and
theory
perspective
like
what
is
the
theoretical
difference
between
between
doing
one
thing,
one
way
or
another
like
between
centralized
models
or
decentralized
models
between
doing
things,
peer-to-peer
or
doing
things
in
a
hierarchical
like
well,
structured
way
and
and
those
different
properties
can
give
you
a
different
range
of
opportunities.
Now
peer-to-peer
is
a
lot
harder
to
build
with,
because
you
don't
have
a
lot
of
control
when
you
build
centralized
things.
It's
a
lot
easier
for
people
to
get
going.
A
B
B
It
was
create
a
whole
bunch
of
oh,
create
a
huge
toolkit
that
people
can
use
to
build
applications
in
peer
to
peer
land
without
having
to
like
reinvent
everything
from
scratch.
It
was
like
this
really
huge.
Frustration
for
us
was
like
okay,
great,
like
it's
2,000
13:14
at
the
time,
and
we
have
to
go
back
and
like
rewrite
tons
of
normal
peer-to-peer
stuff
that
was,
you
know,
could
have
been
written
ten
years
before,
mostly
because
you
know
the
language
and
tooling
have
changed.
B
B
You
know
things
like
assuming
that
you
are
going
to
be
working
on
top
of
TCP
and
and
the
port
that
you
have
is
a
TTP
port
and
that
it's
not
a
UDP
port
or
whatever,
or
even
that
you
don't
have
some
other
transport
right
away,
can
make
library
completely
unusable
for
a
project
like
yours
on
the
road
I.
Remember.
C
B
Loads
that
go
in
line
there,
I
applied
to
I,
see
with
with
the
plan
of
doing
you,
know
this
building,
both
ipfs
and
sock
line
and
a
company
called
proto
collapse.
I
mean
it
was
right
away
from
the
beginning.
It
was
like
this
large-scale
plan
of
going
to
do
build
a
whole
bunch
of
different
things,
all
around
distributed
peer-to-peer
systems
all
of
odd
centralization
and
with
the
business
model
of
taking
a
portion
of
currency,
and
this
was
in
2014
when
this
was
a
very
new
thing.
People
weren't
doing
this.
B
There
was
basically
aetherium
and
a
couple
other
groups
that
had
also
gotten
to
the
same
conclusion
and
I
mean
it
aside
from
a
few
side
projects
that
we
started
and
so
on
and
like
basically
like
delaying
our
timelines
in
terms
of
like
software,
taking
a
lot
longer
to
build
an
unexpected.
We
pretty
much
followed
the
plan
in
that
it.
You
know
from
the
beginning,
we
had
both
ipfs
NFL
coin
and
the
the
you
know,
I
guess,
connecting
to
to
what
I
was
saying
earlier.
B
So
I
had
this
problem
around
datasets
and
versioning
and
so
on,
and
that
led
down
the
rabbit
hole
of
like
really
thinking
through
how
information
moves
in
and
then
I
worked.
How
information
moves
on
the
Internet
in
the
first
place?
How
does
addressing?
How
does
it?
How
do
we
do
addressing
in
general?
It
turns
out
like
with
HTTP
and
so
on.
B
C
C
B
It
was
a
great
era
you
had
you
had
in
the
beginning
of
you
know.
Kadena
has
been
you
know.
The
first
major
large-scale
DHD
had
been
deployed.
You
had
a
bunch
of
people
building
peer-to-peer
networks
like
because
I,
which
then
turn
into
into
Skype
and
a
whole
bunch
of
other
things
and
yeah
like
it
was.
It
was
very
promising.
It
was
like
the
moment
where
everyone
was
getting
connected
to
the
Internet.
B
Another
thing
was:
it
was
right
around
the
same
time
of
the
rise
of
the
normal
cloud,
so
Google
had
been
Google
and
other
companies
were
investing
very
deeply
into
building
like
large-scale
addition.
Resistance-
and
you
know
out
of
you
know
they
were
building
hierarchical
structures
and
they
ended
up
funding
and
ton
of
work
down
the
road
in
a
bunch
of
labs.
B
So
a
lot
of
the
labs
that
we're
doing
fear
if
your
research
switch
entirely
to
doing
cloud
infrastructure
research,
and
so
you
know
that's
another
Avenue
another
point
and
then
I
think
probably
third
or
fourth,
where
third
was.
There
was
no
digital
currency,
so
you
couldn't
actually
pay
people
correctly.
Like
you
had
abroad,
have
trusted
you.
You
have
the
beginnings
of
kripacharya.
B
Illiterate,
so
you
had
the
beginnings
of
digital
currencies,
but
they
were
still
very
unproven
and
still
I
think
rely
on
on
significant
trust
in
the
places.
So
you
didn't
have
the
same
same
fungibility
that
you
sorry
the
same
level
of
trust
with
nastain
and
you
didn't
have
yeah
it's.
The
properties
were
not
quite
there
yet
with
digital
currencies,
I
think
another
one
was
just
the
the
hardware.
B
The
hardware
around
that
people
had
yeah
did
not
warrant
a
peer-to-peer
structure
yet
meaning
it
made
sense
for
a
number
of
use
cases,
but
a
different
set
of
use
cases
like
didn't
make
that
much
sense
like
it's
interesting
to
think
about.
You
know
computing
and
normal
computing
problems
this
way,
because
a
lot
of
people
always
get
hung
up
on
on
how
things
scale.
B
But
when
you
actually
think
about
the
total
magnitude
of
data
in
a
problem,
sometimes
you
realize
oh
yeah,
like
just
throw
that
in
into
one
server
and
like
you
have
one
server
and
whether
you
replicate
that
to
like
you
have
five
servers
that
are
all
full
copies
of
the
index
and
like
you're
done
right
like
you,
don't
have
to
build
a
very
complicated
server
system
to
deal
with
this,
because
your
total
amount
of
data
is
way
smaller
than
like.
The
latest
discs
right.
So,
like
whatever
I.
Don't.
C
Think
about
this
just
to
put
this
in
context
in
a
lot
of
ways.
History
is
repeating
itself
and
the
same
ideas
cycle
back
of
her
Marc.
Andreessen
say
this
before
that
you
know
Webvan.
You
know
how
keep
funding
ideas
that
didn't
work
over
and
over
again,
because
eventually
it'll
work,
so
instacart
a
web
man.
So
it
seems
like
a
lot
of
these
ideas
are
well
known
to
researchers
and
computer
scientists,
we're
trying
them
again
and
there's
a
bunch
of
things
that
are
different.
C
B
Okay,
well,
it's
not
just
Moore's
law
because
you
have
to
account
so
it's
yeah,
so
you
have
accelerating
returns
in
you,
know
computing
and
storage
and
and
so
on,
and
not
so
much
in
bandwidth
right
so
another.
So
an
interesting
point
to
compare
is
like
realizing
that
store
decreasing
cost
super
rapidly,
whereas
been
with
us
not
and
been
with.
You
know.
It
always
feels
like
the
Internet
is
really
slow,
because
we
continue
building
larger
and
larger
applications
from
larger
media.
But
then
we
can't
get
to
yeah.
We
can
get
to
the
moving
around
moving.
B
As
sorry
wait
say
that
again
we
have
so
there's
a
straight
up
between
certain
bandwidth,
where
storages
is
significantly
image.
It's
getting
cheaper
at
a
really
rapid
rate,
where
it's
an
with
us,
not
and
because
of
that.
What
you
end
up
with
is
like
the
feeling
that
constantly
you're
saturating
your
pipe
and
that
constantly
the
internet
is
slow
and
so
on,
but
you're
just
putting
a
lot
more
data
through
it.
Yeah.
B
B
That's
right,
like
that's
a
yeah,
so
if
you
have
fiber
elite
yeah,
if
you
have
like
some
really
fast,
you
know
uplink
or
you
know
some
really
fast
link,
not
really
an
uplink,
because
you're
in
the
core.
You
were
the
test
link
between
two
data
centers
and
then
yeah,
but
like
for
simple,
if
you're
a
company
you're
trying
to
put
us
on
a
data
into
Amazon,
that
was
a
little
say:
hey
like
to
ship
with
a
hard
drive
and
we'll
put
it
on
for
you.
So
there's
like
a
so
this
packet.
C
B
C
B
C
B
B
There
were
definitely
a
lot
of
people
already
thinking
about
the
things
that
we're
doing
now,
but
nowhere
close
to
doing
them,
and
so
there's
a
one
big
difference
between
this
wave
and
the
last
wave
is
that
is
that
the
being
able
to
access
a
range
of
applications
that
were
kind
of
dreams
and
ideas
back
then,
but
we're
we're
kind
of
far
away,
makes
this
wave
actually
quite
different
in
goals.
Right
like
when
you,
when
you
think
about
few
appearances
and
one,
you
don't
think
about
mojo
that
much
you
think
about
Napster.
B
You
think
about
Kazaa,
you
think
about.
You,
know
those
systems
that
you
know
BitTorrent,
maybe
was
like
the
you
know.
It
was
actually
no
tailor
and
like
I
turn,
God
massive
and
so
on,
but
they
was
like
they're
right
as
a
whole,
bunch
of
the
other
ones
we're
failing
in
going
away,
and
so
when
people
think
about
peer-to-peer
and
what
was
working
really
well
with
peer-to-peer
networks
at
the
time
it
was
mostly
pretty
simple
period
appear
structures
that
you
know
that
definitely
they
were
like
people
using
DHCS.
B
You
know
a
computer
effectively
that
allows
you
to
run
some
very
expensive
but
but
trust
less
code.
Right
like
you,
you
don't
have
to
trust
the
the
the
computers
running
this
this
this
code
on
their
output
right
and
like
you
have
a
way
to
verify
that
all
the
computation
with
them
correctly
and
you
call
this
concept.
Let's.
C
Try
to
use
the
same
thought
experiment
there
was
in
there's
infinite
demand
for
free
music.
Like
I,
remember,
I
was
I'm
exactly
the
right
age.
I
was
in
college
with
Napster
cough
everyone.
There
was
a
product
that
everyone
wanted.
Yes,
it
was
illegal,
but
there
was
infinite
demand
for
that.
What
is
the
closest
analog
for
the
current
generation
of
things
that
you
think
there's
inherent
and
consumer
demand
for
that
can
drive?
They
can
be
equivalent
I
think
it
pushes
this
wave
so.
B
There's
a
lot
there
because,
first
of
all,
it's
not
about
consumers,
ok,
peer-to-peer
wave
and
the
reason
why
it's
massive
is
not
because
consumer
is
using
it
and
I.
Think
that's
one
of
the
things
that
Silicon
Valley
has
failed
to
understand,
I,
think
in
2013
and
14.
A
lot
of
the
blockchain
tech
was
being
built
in
New,
York
and
Europe
and
far
ahead
of
Silicon
Valley
and
remember
we're
having
a
lot
of
conversations.
B
People
here
in
New,
York
and
Europe,
and
just
the
level
of
thought
outside
of
Silicon
Valley
was
vastly
superior,
and
it
was
very
surprising
and
annoying
to
me
because
I'm
like
wait.
I
was
supposed
to
be
the
place
where,
like
all
of
the
tech
gets
developed
and
so
on,
and
the
reality
is
that
it
is
not
that
there
was
more
thinking
and
that
certainly
people
in
Silicon
Valley
understood
all
of
that
and
have
thought
about
it
and
so
on.
But
the
understanding
about
what
businesses
or
what
value
propositions
might
actually
be
useful.
B
In
Silicon,
Valley
was
dramatically
centered
around
consumers
and,
in
reality,
what
what
Bitcoin
and
the
theorem
did
was
allow
you
to
create
any
kind
of
you
know
financial
instrument
extremely
cheaply
and,
with
you
know,
almost
free
verification
of
correct
proceeding
of
this
financial
instrument,
which
is
not
normally
a
consumer,
need.
Ok,.
C
C
B
It,
and,
in
fact,
when
it's
not
representative
of
the
entire
industry
right
like
popcorn,
is
one
example
with
all
coin
the
the
point
is
being
able
to
so.
This
is
a
whole
different
argument
that
I
think
is
is
make
sense,
with
or
without
a
peer-to-peer
winter
or
summer.
Like
the
fact.
The
thoughts
around
popcorn
are
about
thinking
about
the
massive
latent
source,
that's
out
there
and
putting
it
to
good
use
right
like
there's,
there's
exabytes
of
Surak.
B
They
are
not
in
use
right
now
and
that,
if
you
were
to
add
them
to
the
to
the
market,
you
would
drive
the
price
down
significantly
and
so
I
think
like
trying
to
end
up
strew
whether
or
not
there
is
currently
a
peer-to-peer
wave
or
whether
or
not
people
are
excited
about
peer-to-peer
in
any
way
or
decentralization.
And
now,
there's
there's
a
point
that
you
can
build
a
network
like
PowerPoint
that
can
use
the
centralization
and
can
use
financial
assets
created
cryptographically
to
then
organize
a
massive
group
of
people
are
on
the
planet.
B
B
You
can
organize
this
massive
massive
network
as
well,
and
you
can
put
all
of
that
Lane
source
that
already
is
there
and
depreciating
and
going
to
waste
into
valuable
use,
and
so
so
far
kinds
of
business
around
you
have
to
think
about
these.
These
networks
are
as
services
and
businesses
that
are
solving
some
set
of
problems,
but
it's
not
a
which
is
one
problem.
That's
a
thing
fundamentally
different
about
this,
this
type
of
saying
than
normal
consumer
products.
C
C
B
Why
somebody
would
add,
storage
the
network?
The
primary
motivator
will
be
money.
That's
what's
going
to
drive
this
massive
amount
of
storage.
Now,
a
secondary
and
very
important
motivator
is
also
the
fact
that,
like
data
is
completely
centralizing,
the
whole
bunch
of
providers-
and
we
get
a
lot
of
businesses
and-
and
people
highly
concerned
about
this-
that
we
want
to
distribute
our
data
across
a
number
of
providers
and
one
stronger
guarantee.
They
want
a
different
set
of
features,
but
you
don't
necessarily
need
the
peer
to
peer
to
to
achieve
that.
B
That
just
happens
to
come
with
the
package
right
and
so
I.
Think
for
for
you
think
about
Bitcoin
miners,
and
you
can.
You
can
think
about
the
the
motivations
of
Bitcoin
miners
are
not
you
know,
fundamentally
about
just
enabling
peer-to-peer
and
so
on
there,
the
huge
motivator
there
is
money.
Now
it
that's
not
true
of
the
early
Bitcoin
miners
right
the
early
become
miners.
B
A
lot
of
them
were
were
primarily
motivated
by
building
a
digital
currency
that
was
not
controlled
by
any
government,
and
that's
something
very
different
than
what
we
have
today
we
have
today
is
is
a
structure
where
it's
a
massive
business
and
people
are
like
going
for
it
and
select.
Ups,
that's
you
know,
I
think
fundamentally
different,
but
but
it
doesn't
make
sense
to
try
and
like
box
it
in
to
say,
like
hey,
there's
one
thing
that
the
entire
industry
is
trying
to
do
like,
in
fact,
when
it's
like
completely
different
than
the
entire
inch.
B
It's
like
we're
using
things
from
the
industry
to
create
a
very
powerful
service
but,
and
the
reason
I
mentioned.
Financial
instruments
is
because
that
is
the
fundamental
information
innovation
that
both
pay
for
interfere
might
reduce
the
ability
to
create
financial
instruments
extremely
cheaply
without
spending
tens
to
hundreds
of
thousands
of
dollars.
Instead,
you
know,
writing
a
few
lines
of
code,
and
you
don't
have
to
litigate
this
in
court.
B
If
it
goes
wrong,
it
just
automatically
automatically
settles
in
a
computer,
and
so
it's
with
what
happened
with
what
the
blocking
stuff
is
that
software
began
to
eat
finance
and
law
in
a
way
that
had
never
happened
before
there
were
a
whole
bunch
of
things
that
we're
kind
of
waiting
or
like
a
lot
of
ideas
that
people
had
had
for
for
a
long
time.
Some
of
them.
You
know
a
few
years,
some
of
them
decades
that
got
knocked
loose
by
the
existence
of
a
digital
currency.
B
That
was
ludicrous
and
suddenly
a
ton
of
these
applications
were
being
able
to
be
built.
So
it's
it's
a
very
different
thing
than
than
than
the
early
peer-to-peer
time.
The
fact
that
that
ipfs
platform
happened
to
relate
a
lot
to
the
early
period
of
pure
goals
is
a
side
effect.
The
majority
of
the
watching
world
does
not
care
at
all
about
those
early
goals.
They
care
about
different
goals.
They
care
about
a
different
kind
of
the
central
decision,
the
centralization
of
power,
not
of
resources,
so
fast.
B
A
C
C
C
People
spent
a
lot
of
time
doing
blackhat
stuff
to
try
to
earn
more
like
it
was
very
fun
yeah
to
try
to
get
more
yeah
I.
Think
a
lot
of
people
like
I
used
to
read
the
commit
list
and
a
lot
of
people
a
lot
of
what
they
had
to
write
was
anti
hacking
stuff.
What
you
would
expect
you
know
good
someone
with
a
hacking
brain
whenever
they
see
new
stuff,
it's
always
fun
to
try
to
take
advantage
of
it.
Yeah.
B
C
So
what
do
you?
What
do
you
think
this
is
sort
of
an
aside
but
I
read
I,
read
YC
applications
for
all
this
stuff
and
I
I'm
trying
to
understand
what
the
best
use?
What
do
you
wear
do?
Smart
contracts
help
you
it's
a
founder.
This
is
a
little
bit
outside
of
the
ipfs
thing,
but
what
is
the
use
case
that,
in
its
current
state,
are
most
useful
for
smart
contracts,
because
I
see
a
lot
of
people
applying
with
these
and
I've
yet
to
see
one
with
a
non
conceptual
use
case?
B
Can
think
of
popcorn
as
a
smart
contract,
whether
or
not
it's
implemented
as
a
smart
contract
on
top
of
the
theorem
or
not
yeah,
you
can
think
of
the
idea
of
a
protocol
declaring
what
the
rules
of
a
financial
transaction
it's
going
to
be
and
a
very
clear
cryptographic
way
of
you
know
proceeding
through
that
transaction
and
verifying
it
at
the
end.
Like
that's
effectively
it's
my
contract,
it
might
not
be
whether
you
you
know
you
can
think
of
Bitcoin
the
whole
thing
as
a
smart.
C
B
You're
seeing
you're
seeing
you
know
super
you
can
go
today
and
start
writing
a
something
that
behaves
like
equity
or
something
that
is
derivative
or
you
know
all
of
these
kinds
of
financial
instruments.
That
would
take
you
a
ton
of
time
to
kind
of
think
about
and
reason
about
it
and
like
inject
into
into
the
jurisdiction.
B
You
know
any
kind
of
legal
jurisdiction
in
the
world
and
you're
now
able
to
do
that
in
a
totally
different
way,
with
a
whole
bunch
of
assets
of
represent
real
value,
and
so,
like
I,
think
that
there's
a
ton
of
these
that
have
very
direct
use
cases
and
applications,
but
they're,
not
they're,
not
consumer,
and-
and
so
that's
that's.
Why
you're
seeing
a
wave
of
things
that
seem
weird
to
Silicon
Valley?
B
You
can
then
turn
that
into
into
like
single
dollars,
right
of
like
running
transaction
fees
and
like
is,
that
is
a
massive
shift
and
we
haven't
even
begun
to
see
the
the
options
of
that
like
there's
in
the
beginning.
So
there's
like
you,
can
you
see
a
ton
of
assets
being
creator
in
ethereum
that
have
a
bunch
of
different
kinds
of
properties
but
they're
they're
fundamental,
like
these
kinds
of
assets?
B
You
know
it's
actively
like
you
get
to
create
any
kind
of
financial
instrument
you
want
as
long
as
you
can
reason
about
how
to
program
it
and
you
can
deploy
it
into
the
network,
and
so
you
can
solve
a
whole
bunch
of
these
kind
of
problems.
One
interesting
example
is
insurance
right
so,
like
you
can
do
insurance
trivially
on
top
of
a
theorem,
like
there's
I,
think
a
really
fun
one
that
you
know
I've
get
used
it
because,
like
I,
my
perception
on
a
lot
of
these
things,
like
maybe
insurance,
is
an
interesting
consumer
one.
B
Actually.
So
an
insurance
policy
is
a
very
simple
idea:
there's
a
whole
bunch
of
regulation
in
the
regular.
You
know
jurisdictions
when
you
think
about
how
to
insurance
quality's
work,
but
you
can
definitely
create
structures
and
financial
structures
around
ensuring
some
activity,
and
so
there's
a
contract
out
there,
where
you
can
tell
it
your
flight
and
you
can
buy
an
insurance
policy
for
a
few
either
and
it
pays
out
like
if
you,
if
you,
if
you
miss
a
flight,
gets
delayed,
then
it
pays.
You
up
pay
some
out
some
amount.
B
B
And
how
do
you
collect
and
things
and
like
just
all
of
that
madness
go
the
way
completely
by
replacing
it
with
where
the
same
smart,
contract,
right
and
so
I
think
those
are
the
kinds
of
things
to
start.
Seeing
and
there's
a
big
bottleneck
right
now,
which
is
that
you
know
the
fundamental
innovation
is
one
around
so
that
let
me
rephrase
this
because
it
only
gets
characteristic
of
the
entire
entire
space.
One
of
the
fundamental
innovations
have
something
like
aetherium
is
this
decreasing?
B
What
you're
going
to
start
seeing
in
the
near
term
is
that
there's
this
blocker
around
user
experience
where
right
now,
nobody
can
use
these
blocks.
Ian's
systems
from
normal
consumer
devices
and
with
the
same
kind
of
UX
that
people
expect
so
there's
a
massive
barrier
there,
where
a
ton
of
applications
that
can
be
geared
towards
consumers
right
like
so
so,
instead
of
starting
from
a
consumer
need,
or
rather
instead
of
like
the
entire
space
solving
consumer
needs.
B
Thinking
about
the
the
UX
of
the
users
like
one
great
example
of
this
is
open
Bazaar,
a
great
project
like
you're
building
like
it
is
completely
decentralized,
eBay
type
thing,
and
they
allow
buyers
and
sellers
to
come
in
and
and,
and
you
know,
buy
and
sell
things,
and
so
when
the
project
started,
they
had
to
build
all
their
peer-to-peer
stack,
we'd
like
from
from
the
ground
up
and
like
that
was
a
huge
undertaking
for
them.
Then
they
found
you
know.
B
At
the
same
time,
we
were
building
IPO,
fastnesses
atonic
profess,
and
you
know
it
made
a
lot
of
sense
for
them
to
switch
over
to
epic
hudson
and
they
did
that
and
so
like
that,
hopefully
saved
it'll
save
them
a
lot
of
time
in
the
lower
layers,
but
then
they
have
to
go
and
build
all
of
the
UX
side
of
things,
and
so
they
had
an
application
that
you
can
download
and
locally.
But
then
you
know
think
about
thinking
about
mobile.
B
You
now
have
to
think
and
build
a
mobile
application
and
get
people
the
same
kind
of
utility
like
that.
That
is
yet
another
massive
undertaking
and
they're
doing
it
like
it's
I'm
super
impressed
like
we
have
this.
This
awesome
mobile,
app
that
you
know
I,
think
I,
don't
know
if
it's
out
yet,
but
it's
going
to
it's
super
exciting,
like
like
I,
think
it's
one
of
the
very
first
things
in
the
entire
space
that
like
gives
you
like
the
really
nice.
B
You
know
normal
us,
you
would
expect
in
normal
product,
and
you
know
the
entire
space
has
to
catch
up.
So
I
think
it's
going
to
take
about
a
year
or
two
before
you
start
seeing
these
things
get
mainstream
consumer
use,
it
could
happen
faster
without
a
lot
of
these
things.
You
know.
Maybe
it's
one
library
white
right,
like
somebody,
writes
a
really
solid
library,
that
kind
of
solves
a
bunch
of
the
problems,
and
then
everything
gets
easy,
but
you
know
just
because
you
you're
not
seeing
a
ton
of
consumers.
Consumer
use
things
yet.
A
A
That's
what
I
wanted
to
focus
on
before,
because
you
kind
of
you
kind
of
like
just
juxtaposed
like
2013
2014,
like
people
not
really
getting
it
here,
things
not
being
built
here.
Obviously,
in
2017,
things
have
changed
right,
like
what
has
changed
in
like
what's
motivating
people
now
to
start
building
these
things
because
I
wonder,
like
you
know,
we
have
a
lot
of
founders.
Listening
and
they're
like
trying
to
figure
out
the
ideas
like
what's
needed.
What
what
change
to
make
this
possible.
A
B
B
Nobody
really
cares
about
trust.
Nobody
really
cares
about
just
like
running
these
kinds
of
transactions.
Everyone
has,
you
know
some
easy
way
to
to
use
a
mobile
app.
Everyone
trusts,
Google,
Facebook,
Apple,
Amazon,
everyone
B
or
whatever,
and
it's
really
just
about
convenience,
and
if
you
don't
have
something,
that's
convenient
screw
it,
it
doesn't
design
ever
going
to
work
and-
and
that
was
like
just
false,
like
I.
Think
that
perspective,
you
know,
I
don't
mean
to
characterize
entire
valley.
B
Seeing
projects
emerging
that
are
about
building
large-scale
infrastructure
that
might
take
years
to
build
out
before
the
utility
is
shown,
and
that's
just
something
that
normal
VC
can't
entertain
like
VC,
is
not
built
for
long
term.
Investments
in
things
that
are
extremely
high
risk
and
building
some
deep
foundational
technology.
Vc
is
tuned
for
ten-year
returns,
which
means
that
in
two
three
years
you
have
to
like
show
very
strong.
B
Like
part
part
of
what's
beautiful,
about
tcp/ip
a
DNS
like
that
whole
era
of
protocols
was
that
people
worked
super
hard
for
months
and
years
at
a
time
to
think
about
the
interfaces
and
refine
it
so
that
you
could
end
up
with
something
sufficiently
abstract
to
support
us
on
that
use
cases
and
sufficiently
concrete
to
actually
work
today
and
that
kind
of
development
is
not
super
fast
and
takes
a
lot
of
work
and
takes
a
lot
of
money.
And!
That's
not
something
that
you
know:
VC
funds,
VC
funds,
clear
applications.
B
A
B
C
B
C
C
C
C
B
And
here
you
know
you,
that
is
a
clear
example
of
something
that
is.
You
know
it's
basically,
maybe
not
directly.
You
know
consumer
perspective,
but
Tesla.
Definitely
right
like
definitely
it's
a
very
consumer
oriented
thing,
but
it
was
extremely
difficult.
It
was
a
large-scale
long-term
project
that,
just
you
know,
scared
the
hell
out
of
VC,
with
good
reason,
like
it's
extremely
unlikely
that
you
would
get
any
of
that
to
work.
But
what
I'm
highlighting
is
not
that
necessarily
BC
has
to
fund
this.
A
B
And
so,
but
I
think
something
a
bit
different.
I
want
to
draw
an
analogy
between
what
happened
at
the
labs
in
Google
brain,
so
Bell
Labs
was
about
constructing
massive
cost
reductions
for
Bell.
So
the
reason
that
labs
got
to
thrive
as
an
organization
was
because
it
represented
a
very
strong
financial
interest
for
this
massive
monopoly
that
had
an
enormous
business,
and
so
they
had
deep
pockets
to
just
invest
deeply
into
into
things
that
we're
going
to
save
them.
B
A
lot
of
money
later
and
so
bail
could
look
at
things
like
oh
wow,
you
know,
vacuum
tubes
are
really
inefficient
or
vacuum
tubes
break
a
lot
and
it's
a
huge
pain
to
repair
them.
Wouldn't
it
be
great
if
we
had
something
better
and
it
basically
took
something
like
20
years,
I
think
it's
like
10
to
20
years
before
before
the
transistor
right
and
it's
something
like
I
might
be
wrong
in
those
states.
But
the
point
is
Bell
Labs
understood
the
need
Bell
Labs
of
this
massive
cost
reduction.
B
But
that
was
an
innovation
that
happened
over.
You
know,
decades
and
timescales,
and
primarily
motivated
by
cost
reductions
on
the
large
scale
Bell
front,
and
so
the
the
funding
that
Bell
could
feed
into
funding
tens
to
hundreds
of
researchers.
Thinking
about
all
these
problem,
the
specific
problem
on
it
on
a
ten
year
time
horizon
to
try
and
get
that
kind
of
like
cost
reduction,
is
something
that
only
massive
monopolies
today
have
been
able
to
fund
it's
like
basically
massive
monopolies,
either
in
business
or
in
touring
or
in
power
right.
B
B
B
And
yet
the
labs
was
able
to
like
reliably
get
a
whole
bunch
of
researchers
to
to
achieve
these
kinds
of
innovations,
and
so
that,
unfortunately,
like
the
model
of
why
Bell
Labs,
the
question
is
around
why
the
labs
ultimately
failed
and
fell.
Apart,
have
to
do
more
with
the
surrounding
ecosystem,
like
its
funding
source
cuz.
B
Right
so
so,
breaking
bail
apart
effectively
cycles
and
killed,
Bell
Bell
Labs.
So
a
few
things
happened.
One
was
the
rise
of
Silicon
Valley
and
the
great
invention
or
invention,
but
like
the
great
use
of
stock
options
or
just
giving
stock
to
to
everyone
in
the
company
working
on
something
cause.
A
ton
of
people
working
on
very
you
know,
research
fee,
oriented
things
at
the
time
to
become
quite
wealthy
right
or
like
get.
B
You
know
very
significant
personal
returns
and
that,
coupled
with
the
excitement
around
all
of
the
stuff
that
was
happening
in
Silicon
Valley
in
the
50s
and
60s
with
you
know,
a
number
of
people
kind
of
moving
out
and
then
coming
back
and
talking
about
all
the
great
and
exciting
things
that
were
happening
in
the
West
started
to
drain
a
lot
of
people
out
of
the
labs
and
out
of
Boston.
And
so
this
you
know
known
as
it's
like
brain
drain
and
part
of
that.
What
what
happened?
B
There
was
not
only
were
people
leaving
and
going
and
creating
other
research
organizations
that
had
different
funding
models,
but
that
also
started
getting
broken
up,
and
this
is
more
like
the
80's
90's
I
forget,
except
the
exact
date
on
this,
but
when,
when
Bell
got
broken
up,
Bell
Labs
had
to
find
a
way
to
like
charge.
The
you
know
new
separate
entities
for
all
of
its
work
and
it
just
became
infeasible
to
fund
and
maintain
a
massive
organization
like
that,
and
so
I
don't
end
up
breaking
apart.
B
I
wanted
to
have
million
so
yeah
I
was
like
yeah
all
right,
so
I
was
like
tours
minded
off
so
exceda,
something
like
10
to
100.
That's
a
lot
better
that
it's
a
lot
cheaper
than
than
what
I
expected
like
foundational
research
due
to
cost,
but
that's
still
massive
right
like
being
able
to
I
guess
on
the
on
the
scale
of
10
years,
like
yeah,
that's
10
billion
right!
Ok,
you!
You
have
to
have
10
to
50
billion
and
ready
to
commit
them
for
like
two
decades
to
be
able
to
undertake
some
of
these
projects.
B
C
B
Ladies
I
think
I
think
something
like
Google
brain
is
a
clear
example
of
this
kind
of
thing
happening
again
where,
where
Google
saw
massive
advancements
in
machine
learning,
we
want
to
apply
all
of
those
massive
advancements
to
image,
to
machine
learning
into
a
whole
bunch
of
the
normal
Google
applications,
and
we
want
all
of
our
applications
to
get
better,
faster,
stronger
and
so
on
and
reduce
costs.
And
not
only
are
we
going
to
be
able
to
do
a
whole
bunch
of
new
things
and
cool
things,
but
we're
also
going
to
be
able
to
do
them.
B
B
Different
organizations
I
think
that
the
Google
brain
and
acts
are
are
much
more
focused
on
on
shorter
term
valuable
things
than
the
labs
I
think
both
brain
and
X
can't
yet
afford
to
innovate
on
the
multi
decade,
timescale
they're,
they're,
innovating
in
like
single
decade,
time
scales,
their
own
I,
wouldn't
I.
Think
that
you
know,
if
you
look
around
the
planet,
there's
a
closest
thing,
probably
you
know
very
cut,
they're,
still
kind
of
far
away
and
I
think
it'll
take.
B
B
Yeah,
where
you
see
it,
the
budget
of
a
of
a
Google
run
physics
lab,
have
a
you
know,
budget
for
a
decade
or
more
and
like
50,
plus
researchers-
and
you
know
you
start
seeing
some
noble
prices,
one
out
of
Google
like
then
then
we're
talking
about
the
same
thing,
but
we're
far
away
from
that
and
I
think
the
the
I
don't
think.
Well,
we
don't
necessarily
to
recreate
the
same
kind
of
structure.
I
think
what
we
can
do
is
is
look
at
a
different
thing.
B
That's
going
on
and
look
at
how
innovation
happens
in
a
very
different
open-ended
way
in
in
the
internet,
so
the
Internet
has
a
lot
of
similarities
with
the
research
culture
of
that
labs.
In
that
it's
extremely
open.
You
get
a
lot
of
people
thinking
about
problems,
you
you
have
a
lot
of
people
talking
about
problems
and
discuss
not
only
talking
about
potential
solutions,
but
trying
them
out
and
so
on,
and
so
the
people,
sharing
knowledge
and
ideas
for
the
internet
and
working
and
open
in
other
groups
has
been
able
to
have
very
important
results
achieved.
B
B
The
Linux
kernel
is
an
awesome
example.
I
think,
like
you,
have
the
ability
to
to
undertake
these
major
major
infrastructure
projects
and,
like
things
that
take
a
long
time
to
to
create
a
mature
on
the
internet
and
a
whole
other
interesting
Avenue.
Here
is
how
do
you
fund
these
things
like?
How
do
you?
B
So
because
we
were
creating
this
token.
We
can
take
some
of
that
token
and
give
it
to
the
people
building
the
protocol,
which
then
helps
you
know
they
can
sell
it
for
dollars
or
whatever
to
then
feed
themselves,
and
then
that
way
they
can
like
actually
fund
the
development
of
the
project,
and
this
is
effectively.
B
What
would
a
theorem
did
right,
so
that
kind
of
funding
model
allows
people
to
remain
very
close
to
the
the
actual
protocol
layer
and
to
think
deeply
about
the
protocol
itself
and
his
concerns
without
having
to
think
about
a
product
or
a
service
on
top.
So
this
is
precisely
what
protocol
app
is.
Business
model
is,
and.
A
C
Like,
let's
like
well,
that's
like
drill
down
to,
because
that's
a
great
point
we're
just
talking
about
it.
What's
the
tenure
like
how
do
you
you
have
to
keep
selling
bits,
not
you
personally,
but
if
you're
one
of
these
folks
do
you
have
to
keep
constantly
reissuing
tokens
to
keep
feeding
yourself,
I
mean.
A
B
You
saw
this
happening
with
Bitcoin
I
mean
there
are
people.
There
were
some
people
that
were
early
to
bitcoins
that
are
are
now.
You
know
they
have
their
their
personal
wealth
at
a
point
where
you
know,
unless
it
wasn't
major
crashing
their
asses
like
they
don't
have
to
work
again.
Yeah-
and
you
know
they
kind
of
ten
years
old,
now,
almost
right,
so
it's
sort
in
2008
doesn't
that.
B
And
so,
like
you
know,
it's
roughly
ten
years
old
and
yeah
I
mean
I,
think
I
think
maybe
you
could
claim
that
the
origins
of
Bitcoin
happened
through
the
sacrament
lesson,
motor
nation
and
all
these
other
things
and
all
those
discussions.
And
so
that
was
like
long-term
innovation.
That
happens
and
then.
C
B
Was
getting
funded
afterwards,
so
it's
like
you,
know,
very
different
approach
than
say
the
Bell
Labs.
You
know
centralized
perspective,
but
yeah
I
think
the
funding
of
these
things
it's
going
to
depend
entirely
on
whether
these
things
are
continued
to
be
useful
right.
So
if
here
we
continue
to
be
useful.
Five,
ten
years
from
now
you're
going
to
have
and
continues
to
accrue,
goodies
to
grow
right
to
the
etherium
becomes
more
and
more
successful
continues
to
solve
a
whole
bunch
of
problems.
B
Then
an
ether
is
going
to
be
worth
a
ton
more
and
as
that
ether
is
worth
a
lot
more
yet
you're
now
going
to
have
you
know
tens
of
thousands
of
people
that
right
now
are
crypto
millionaires.
Turning
into
you
know,
ten
million
they're
going
to
have
10
million
100
million,
potentially
billionaires.
Who
knows
right,
like
I,
don't
know,
I.
Think
at
that
point,
like
you,
the
valuation
of
something
like
material
gets.
B
But
you
know
you
have
this
very
different
way
of
building
a
service
where
you
take
a
share
of
the
worth
of
the
service
in
a
sense
like
having
ether,
it's
kind
of
having
a
share
of
the
worth
of
network.
There's
not
the
worth
of
the
network
totally.
The
network
is
worth
more
than
that,
but
it
is
a
subset
of
that
and
then
you
can.
B
C
Know
the
during
the
dot-com
bubble,
everyone
was
a
day
trader
and
everyone
mate,
you
couldn't
lose
it
actually.
If
you
would
have
bought
and
held
to
this
day-
and
you
were
lucky
enough
to
have
enough
exposure
to
what
like
Apple
and
Google
it
actually
would've
been
okay,
but
if
back
in
a
your
day
trading-
and
you
didn't
have
one
of
those
big
winners
or
if
you
just
lost
all
your
money
in
the
early
days,
you
know.
A
C
B
B
A
B
More
important
thing
that's
going
on
deeper,
which
is
that
a
whole
bunch
of
important
things
are
getting
built
and
you
can,
if
you
find
them,
you
can
fund
them
and
you
can
be
part
of
them
and
can
help
create
them
and
create
massive
massive
value
and
the
people
that
do
that
are
going
to
get
greatly
rewarded
and
I.
Think
that
goes
along
with
diligence
like
you
can't
just
approach.
I
think
my
perspective
on
this
and
the
way
that
I
look
a
lot
of
the
spaces.
B
Is
that
I
think
deeply
about
each
of
these
pieces
of
the
penalty
and
I
approach
it
much
more
like
investing
into
into
a
startup
or
investing
into
a
project
that
I
think
it's
worthwhile
and
should
happen
even
if
I
lose
out
all
money
that
I
invest
in
it
and
I
think
about
the
underlying
value,
that's
being
created
like
what?
What
is
this
thing
going
to
enable
in
two
five
ten
years
from
now,
you
know
I
think
within
the
craft
of
space
you
you
don't
even
need
to
think
to
in
ten
years.
C
I,
just
you
do
a
resigner
question
that
that's
a
little
different,
though
than
basic
research
like.
Is
it
part
of
basic
research?
You
don't
want.
You
want
to
believe
that
the
researchers
are
good,
but
you
don't
actually
want
to
worry
about
what
they're
working
on,
because
they're
going
to
do
great
stuff.
Do
you
know
I'm
saying
this
isn't
mean
I
go
through
when
I'm?
Looking
at
these?
It's
like
you
want
to
understand
that
it's
a
good
team
and
you
believe
in
their
vision.
But
if
you
get
too
in
the
details
yet
you'll
like
miss
the.
B
Boat
right,
okay
and
then
think
alike,
so
we're
making
mixing
so
many
we're
basically
so
many
different
topics
which
is
awesome
by
the
way
I
rarely
get
to
get
to
get
this
deep
into
into
a
lot
of
conversation,
a
lot
it
I,
just
I,
don't
mean
to
imply
Bitcoin
or
theorem,
is
like
that
laughs.
It's
like
a
different
thing.
It's
like
a
different
thing
that
that
is
showing
off
that
or
what
you
get
out
of
it
is.
B
So,
when
I
think
about
structuring
Vella
sorry
when
I
think
of
structuring
about
protocol
labs,
you
know
we
think
about
flatpoint
as
a
specific
service
and
business
that
has
a
much
shorter
term
perspective.
It's
like
Lachlan
has
to
work
and
be
successful
and
valuable
in
two
three
years,
not
five
or
ten,
and
we're
nowhere
near
close
to
be
able
to
clear.
B
That's
applied
on
top
to
a
subset
of
those
transactions,
and
so
it's
all
sort
of
those
protections
are
the
going
to
be
the
platform
transactions
and
now
we're
building
out
we're
setting
off
and
doing
all
this
work.
So
it's
a
yes
I,
think
I
think
you
know
it
really
started
the
clock
on
on
Falcone
and
we've
had
a
whole
bunch
of
like
detours
right
like
we've
had
you
know,
we
ended
up
building
this
whole
platform
called
coin
lists,
so
you
can.
B
And
then,
when
you,
when
people
first
saw
it
has
solves
a
whole
bunch
of
important
problems
and
we
had
for
a
brief
period
of
like
you
know
a
month
and
a
half
something
akin
to
like
a
Bell
Labs
feel
of
like
four
or
five
people
in
a
house
doing
nothing
but
reading
papers
and
working
on
on
card
research
problems
and
reading
the
papers
of
like
Turing,
Award
winners
and
then
like
being
a
step
ahead
of
some
of
them
and
being
like.
Oh
wow.
B
They
just
published
this
thing
and,
like
that's
a
problem
that
we
talked
like
well
ago
or
something,
and
that
was
like
a
you
get
like
glimpses
of
this
happening
right
and,
like
you,
can
think
of
someone
like
metallic
as
operating
entirely
in
that
in
that
space.
Where
he's
just
thinking
about
large-scale
problems
in
the
5
10
year,
time
horizon
to
creators,
Aryan
yeah
but
I
like
Batali
the
creator
of
etherium
and
he
he
is
managed
to
build
for
himself
a
lab
similar
to
one.
B
B
Like
here's
a
you
know
your
researcher
and
you-
and
you
want
to
think
about
like
not
just
starting
businesses
and
starting
companies
and
so
on,
but
like
really
think
deeply
about
what
what
kind
of
problems
do
we
help
them
today
would
have
would
create
like
enormous
value
for
humanity
worldwide?
There's
a
very
specific
problem
in
in
this.
Like
an
economics
problem,
it's
the
it's
also
an
AI
problem.
B
It's
the
credit
assignment
problem,
which
is
that
if
you
have
a
set
of
agents
that
are
participating
in
a
set
of
endeavors
and
those
endeavors
either
create
or
destroy
value.
How
do
you
correctly
propagate
reward
back
to
the
agents,
meaning
you
know
if
you
have
a
number
of
people
working
on
a
start-up
and
you
create
a
whole
bunch
of
value
in
the
startup
and
that
ends
up.
You
know
can't
you
capture
some
of
that
as
a
reward.
How
do
you
propagate
the
reward
back
effectively?
This
is
equity.
B
What
is
the
credit
assignment
on
something
like
the
Linux
kernel
right,
I
mean
Linux
has
done
an
enormous
amount
of
work
and-
and
you
know,
created
a
huge
fraction
of
the
value
from
the
Linux
kernel,
but
so
have
a
ton
of
other
people
that
have
been.
You
know,
slogging
and
waiting
through
major
major
issues
and
the
majority
of
those
people
that
are
building
this
huge
foundational
thing
that
is
now
on.
B
Like
you
know,
a
huge
fraction
of
the
computers
in
the
planet
did
not
see
any
kind
of
kind
of
reward
attributed
to
them
on
the
scale
of
the
companies
that
came
after
that
user
technology
and
captured
value
right.
So
you
can
see
something
like
Android
as
capturing
massive
amounts
of
value
that
went
into
the
Android
business
and
Google,
and-
and
you
know
all
of
those
those
groups
that
completely
rode
on
the
on
the
value
created
by
the
Linux
Linux
kernel
group,
and
you
can
think
about
this
across
every
single
business.
B
Every
single
business
that
runs
computers
in
a
large
scale,
like
has
been,
he
has
gotten
value
out
of
the
Linux
kernel,
grip
and
I
mean
how
can
we
just
like
propagate
reward
back
so
that
you
know
all
of
those
people
now
no
longer
have
to
like
worry
about,
like
other
data
I
think
you
know
like
really
just
focus
on
this
thing,
but
can
you
do
this
in
a
you
know
in
a
big
scale
across
all
possible?
You
know
projects
right.
B
So
we
are
super
interested
in
solving
this
problem
because
we
think
if
we
solve
this
problem,
you
know.
Even
if
we
have
like
a
bit
of
a
good
answer
to
this
problem,
then
we
can
fundamentally
change
how
open-source
gets
built
in
that
it
would
be
great
if
people
that
are
working
on
work
on
projects
and
open
source
can
just
do
that
without
having
to
have
a
day
job
that
that
they
don't
like
or
whatever
there's
a
lot
of
people.
B
I
know
that
operating
in
that
landscape,
where
they
have
some
job,
that's
kind
of
interesting,
and
they
do
it
because
you
know
they
have
options
like
they
could.
You
know,
there's
nothing
like
work
on
something
that
completely
don't
like
a
whatever,
and
although
there
are
a
lot
of
people
like
that
are
in
that
position,
but
at
the
same
time
it's
not
what
they
will.
B
They
love
the
most
and
it's
what
will
pay
their
bills
and,
in
the
same
time,
they're
creating
a
ton
of
value
by
working
on
a
whole
bunch
of
interesting,
open
source
projects,
but
there's
no
easy
way
for
them
to
get
rewarded
by
the
value.
That's
captured
many
many
layers
deep
after
so
my
claim,
and
this
is
a
complete-
you
know
guess,
and
that
could
be
totally
wrong
about
this.
B
But
I
claim
that
if
we
solve
that
problem
in
a
way
that
we
have
a
function
like
I
could
run
a
function
over
all
of
the
people
on
github
that
have
contributed
to
all
of
the
projects
that
protocol
apps
runs
and
all
of
the
projects
that
protocol
labs
projects
use.
So
like
we're
talking
about
not
only
the
community,
that's
working
on
one
project,
but
also
the
community
other
communities.
B
B
C
B
I
think
it's
fine
to
feed
in
human
intervention
along
the
way.
You
know,
there's
interesting
research
done
on
large
companies
and
governments
where
you
have
all
these.
You
know
peer
reviews,
and
you
know
kind
of
like
and
manager
reviews
and
and
all
this
kind
of
you
know,
360
review
counter
perspective,
and
out
of
that,
you
can
get
a
good
signal
right
like
otherwise.
If
we
didn't
we're
getting
good
signal,
then
there's
no
hope
for
you
before
any
kind
of
companies
that
looks
large
right
and
so
surely
something's
working
and
there's
good
research.
B
That
is
extremely
difficult
to
game,
because
you
know
again,
that's
if
you,
if
you
get
people
quickl
people
will
quickly
learn
that
they
can
just
like
give
each
other
really
hydrating
into
that
will
have
the
translate
really
big,
boosts
and
promotions,
and
so
on
or,
like
you
know,
greater
rewards.
You
have
to
get
something
that
doesn't
like
it's
not
easy
to
game,
but
then
further.
B
If
you
take
people
out
of
the
equation
in
the
choosing
part
at
the
very
top,
like
all
of
those
feedback,
all
that
feedback
always
propagates
all
the
way
to
the
top
and
it's
ultimately
people
making
decisions
that
you
know
kind
of
like
compensation
and
all
this
kind
of
stuff
in
this
is
in
companies.
But
in
in
science,
it's
like
grant
funding
like
the
people
that
actually
choose
who
to
give
grants
to
and
what
research
to
fund
or
in
open
source.
B
It's
like
hey
a
company,
decided
to
invest
deeply
into
this
project
because
they
thought
it
was
like
super
valuable
and
like
the
allocated
engineers
to
just
work
on
that,
but
like
they're,
not
directly
just
giving
money
to
everyone
in
that
project.
If
we
just
take
humans
how
to
loop
in
that
decision
process
and
put
an
algorithm
that
people
can
have
confidence
over
that,
this
is
going
to
be
a
correct
and
fair.
B
They
can
then
turn
that
contribution
into
eating
right,
like
there's
this
we're
headed
for
like
a
very
big
economic
problem
and
we're
already
kind
of
in
the
middle
of
it,
but
we're
going
to
have
bigger
problems
that
ass
automation
comes
in,
AI
comes
in
and
all
this
kind
of
stuff
it's
got
a
challenger
from
our
basic
notions
of
of
worth
in
value.
In
you
know,
economic
terms,
right
like
we
live
in
a
world,
that's
centered,
very,
very
rigidly
around
the
perspective
of
hey.
B
You
have
you
get
a
job
and
you
work
and
you
contribute
value
to
an
endeavor
and
you
get
back
some
pay
and
you
turn
that
pay
into
food.
And
so
if
you
want
food
and
shelter
and
survival,
and
if
you
want
nice
things-
and
if
you
want
to
like
be
able
to
like
you
know,
not
only
survive
and
have
good
things
and
so
on,
but
like
you
want
to
leave,
you
know
be
able
to
afford
school
for
your
kids
or
healthcare,
and
so
on.
B
You
have
to
have
a
job,
and
this
job
is
mediated
by
you
know
kind
of
like
a
whole
bunch
of
external
forces,
and
it
prevents
a
ton
of
people
from
allocating
their
work
to
what
they
think
is
actually
most
fundamentally
valuable
and
I
claim.
It
doesn't
do
as
good
of
a
job
as
it
should
in
correctly
rewarding
major
contributions.
B
We
see
people
with
noah
prizes
and
turing
prizes
that
have
made
massive
contribution
to
the
world
and,
have
you
know
not
net
worths
similar
to
groups
that,
like
ended
up
doing
like
terrible
things
for
the
course
and
and
managed
to
get
away
with
it
right,
and
so.
The
claim
here
is
one
that
this
on
the
small
scale
could
improve
dramatically
something
like
open,
source
and
and
potentially
like
companies
on
how
you
allocate
composition
there.
B
But
in
a
big
scale,
a
really
good
answer
to
this
problem
could
be
a
new
economic
model
like
it
could
be
like
the
a
new
version
of
capitalism,
or
it
could
be
something
else.
It's
not
called
capitalism.
It
could
be
something
around
like
just
like
correct
M&O,
like
it's
a
whole
new
world
right,
so
I
think
it's.
C
That's
super
interesting
and
we've
had
a
lot
of
discussions
internally
around
basic
income,
I
think
yeah,
where
I
get
hung
up
on
this.
Is
that
let's
pretend
that
we
did
healthy
hour,
let's
pretend
someone
to
the
research
and
they
found
a
fair
way
to
allocate
worth.
Would
anyone
accept
it
like?
Essentially,
the
tricky
part
is
not
the
technical
challenge.
It's
getting
people
to
ever
believe
a
computer
is
fair
or
ever
like
what
if
the
algorithm
said,
actually
you're
not
worth
very
much.
B
Ideally
so
that's
where
I
think
I
mean
I
think
for
this
to
work
correctly.
You
have
to
have
markets
involved
and
you
have
to
have
this
kind
of
algorithm
either
working
in
a
market
yeah.
You
can
turn
an
algorithm
into
a
market
right
and
then,
ideally,
you
wouldn't
have
one
one
computer
that
like
decides
what
you're
worth
right,
but
rather
you
have
an
entire
like
large-scale
system
and
relative
worth
is
being
ascribed
by
other
groups
where,
like
you,
have
a
lot
of
cases
where
one
group
thinks
something
is
really
bad
one.
B
Another
group
doesn't
think
so
and
that's
fine,
it's
just
like
they
have.
They
themselves
are
occurring
value
and
worth
in
whatever
ways
and
they
can
propagate
it
or,
however,
they
want
you
know
similar
to,
like
you
know,
companies
going
in
opposite
directions
or
whatever,
and
yes,
it's
going
to
call
into
question
a
bunch
of
hard
things
as
like.
You
know,
here's
like
your.
What
your
contribution
is
really
worth,
but
my
claim
is
right
now
we
we
have
in
much
work.
This
is
kind
of
I
kind
of
describe.
This
is
similar
to
the
self-driving
car
problem.
B
B
This
is
like
the
first
plans
to
do
this
up
here,
but
now
we
have
computers
that
write
better
than
humans
and
pretty
soon
they're
going
to
start
getting
deployed
and
we're
going
to
start
writing
in
them
and
so
on,
and
people
will
see
that
this
is.
This
is
going
to
save
us
out
of
lives
compared
comparatively,
and
so
my
claim
is,
is
you
can
create
something?
That's
fair
and
you
can
create
something
that
it's
also
provably
her.
B
So
one
of
the
things
here
about
algorithms
is:
you
can
have
a
computational
screwable
that
actually
runs
over
the
whole
thing
and
can
produce
a
cryptographically
verifiable
proof
that
it
was
done
correctly
and
like
that
was
correctly
assigning
the
right
thing
and
it
could
give
you
a
trace
of,
like
all
of
the
violation
and
like
here's,
here's
the
argument
as
to
why
this
determination
was
made
and
and
I
think
like.
That
would
be
a
much
better
place
to
be
than
where
we
are
now,
where
it's
extremely
fuzzy.
B
You
can
then
position
yourself
on
maneuver
yourself
to
expose
yourselves
to
things
that
that
generated
a
lot
of
capital
and
wealth
that
don't
necessarily
generate
or
create
a
lot
of
value
right.
There's,
a
very
big
difference
between
capital
and
value
that
is
not
correctly
on,
like
the
value
of
a
dollar
today
does
not
equate
to
like
just
raw
fundamental
value
right,
and
so
we
use
an
approximation,
and
we
think
that
it's
a
good
enough
approximation
that
continue
using
it.
But
in
a
lot
of
ways
you
can
see
things
that
are
worth
massive
amounts
of
money.
B
There's
tons
of
companies
I'd
like
to
get
a
lot
of
value
by
like
dumping,
a
bunch
of
crap
into
the
ocean
and
like
wrecking
you
know,
there's
a
whole
bunch
of
externalities
that
we
cannot
properly
calculate
and
account
in
those
in
those
situations
and
ultimately
there's
at
least
in
in
most
countries
in
here
in
in
the
world.
You
have
groups
of
people
that
are
making
those
decisions
at
the
very
top
and
deciding
what
are
the
outcomes
of
major
bad
actors
like
actors
that
have
made
serious
mistakes.
B
Like
you
know
the
2008
crisis
like
major
mistakes,
and
they
seem
like
well
yeah.
All
these
were
major
mistakes.
All
of
these
things
should
fail,
but
if
they
fail
we're
going
to
be
in
deeper
trouble,
so
let's
just
bail
them
out
and
continue
as
if
nothing
has
happened
to
some
degree,
not
quite
but
to
some
degree
and
a
ton
of
the
people
walked
away
scot-free
right
like
and
got
away
with
in
made
in
some
cases
it
actually
making
money
through
the
financial
crisis.
B
In
you
know,
people
that
were
directly
responsible
for
the
problem
ended
up
with
returns
and
like
this
is
like
screwed
up
right
now.
I
think
like
this
is
something
extremely
far
away
for
my
correct
and
fair
distribution
of
value
and
and-
and
you
know,
and
so
I
think
you
know-
that's
I,
think
an
open
problem
of
the
kind
of
like
pre
companies
for
pre
capitalism,
or
this
kind
of
thing
like.
B
B
B
C
B
A
Feelings
when
you
go
then
well
I
mean
think.
Conversely,
think
of
it,
like
you
just
happen
to
you,
know
luck
into
being
one
of
the
first
10
employees
at
a
giant
company
of
the
25th
person
is
the
person
who
actually
created
the
value,
and
their
allocation
is
much
less
than
yours.
Yes,
like
that
model
is
not
figured
out
yet.
I
am.
B
B
C
C
B
Yeah
I'm
kind
of
bothered
by
that
I'm
kind
of
bothered
by
the
fact
that
in
crypto
right
now,
you're
seeing
the
normal
issues
with
capital
flood
in
which
is
that,
if
you're,
a
specular
that
has
a
lot
of
capital,
you
can
afford
to
get
much
greater
rewards
than
the
people
that
actually
build
the
thing
and,
and
that
to
me
is
again
another
frustrating
thing.
That
is
why.
B
But
you
know
if
this
works
well,
we
could
do
the
you
know.
We
can
do
that
in
even
deeper
way
across
projects
that
contribute
value
to
us
and
we're
going
to
issue
this
token.
And
then
we
either
are
going
to
do
things
like
issue
dividends
or
buyback
and
create
a
way
for
us
to
directly
share
a
fraction
of
the
value
that
Farrokh
labs
creates
with
the
people
that
helped
make
create
a
value,
and
it
is
a
huge
experiment
right.
You
can
go
completely
wrong.
B
I,
don't
want
to
do
anything
that,
like
what
would
cause
that,
because
I
think
open
source
like
it's
an
amazing
place
where
people
are
motivated
to
to
work
for
the
projects
because
of
what
you
believe
in
and
like
that's
super
important
like
yeah
I,
would
hate
it
if,
whatever
kind
of
experiment
in
this
direction
kills
the
fact
that
the
Linux
kernel
is
build
by
applying
to
people
that
really
cared
deeply
about
the
problems
and
are
fixing
them
and
so
like
it
has
to
be
done
carefully.
But
I
think
we
can
start
running
some
experiments
right.
A
B
So
I
mean
they
are
ideas
we
are
thinking
about.
These
are
not
being
wrapped
into
into
coin
lists
or
other
things
just
yet.
You
know
there's
a
lot
of
things
that
we
have
to
carefully.
Consider
I
mean
the
thing
about
intent
of
engineering.
Is
that
it's
hard
I
mean
this
is
why
this
problem
is
an
open
problem
and
you
know
I.
B
You
know
if
you're
listening
to
this
and
you're
researcher
and
you
care
about
this
like
get
in
touch,
because
I'm
probably
going
to
start
a
small
like
research
group
to
to
to
solve
this
problem,
but
I
don't
expected
as
a
successful
thing
in
years,
like
I
think
this
is
a
long
term
thing.
I
think
this
is.
This
is
like
a
the
kind
of
research
project
that
protocol
apps
could
fund.
B
That
is
one
of
those
long
term
innovation
things
and
we
actually
don't
think
we
need
that
many
people
I
think,
like
probably
the
right
10
people
can
solve
it
wrong,
maybe
even
less.
Maybe
it's
like
a
singular
person
that,
like
actually
figures
it
out
with,
as
has
happened
in
a
ton
of
other
cases
in
history,
but
I
think
we
can
start
at
the
very
least
collecting
some
data
to
assist
the
theory
and
that
data
that
might
come
with
some
of
these
experiments,
and
we
are
thinking
about
the
significance.
I
mostly
want
a
reward
right
now.
B
I
mostly
want
to
reward
a
lot
of
the
people
that
were
very
early
to
the
I
profess
project
that
saw
the
value
created
and
said
wow.
This
is
an
awesome
project
and
we
want
to
make
this.
You
know
a
reality
and
and
so
on,
and
you
know:
we've
been
slogging
through
a
ton
of
hard
work
for
the
last
three
years.
We're
like
it
right
now.
I
guess:
go
at
the
FS
turn
three
years
old.
B
Yet
like
two
days
ago,
the
protocol
itself
is
a
little
bit
older,
but
that
would
like
you
know
the
code
base
and
there's
a
ton
of
people
that
came
in
and
helped
out
tremendously.
Some
of
them,
who
you
know
didn't
make
sense
for
us
to
hire
into
protocol
labs.
Some
of
the
people
like,
for
whatever
reason
some
of
those
cases
are
like
academics.
B
And
it's
amazing
like
it's
like
it
should
not
be
undervalued.
Like
that's
I,
it's
extremely
difficult
to
find
communities
where
not
only
is
that
valued
by
everyone
around,
but
it's
also
greatly
rewarded
right
and
like
that.
That's
I
think
is
an
example
in
the
right
direction
and
I
think
one
that
we
can.
We
can
build
on
and
create
more
of,
and
if
this
gets
to
be,
you
know,
I
think
it's
etherium
and
popcorn,
and
these
networks
got
to
be
massive
and
end
up
like
being
at
the
same
degree
and
scale
as
a
whole.
B
And
it's
awesome,
like
that's
fantastic,
like
that.
That
is
a
great
example
of
a
correct
application
of
the
reward
problem
like
right.
There,
like
the
people
that
generated
massive
amount
of
value
by
slogging
through
really
hard
teary
problems
for
years
and
came
up
with
a
right
solution,
and
so
on
are
now
able
to
like
correctly
make
contributions
in
some
cases.
Like
short
time,
signed
contributions.
Again,
knowledge
work
is
really
hard
to
measure
in
hours.
You
can't
you
can't
measure
knowledge
working
hours.
B
This
develop,
and
you
know
we're
like
thinking
about
things
like
that,
like
how
do
we
build
vertical
ABS,
an
organization
that
can
do
deep
research,
a
bunch
of
different
directions
with
a
bunch
of
collaborators
around
the
planet
in
a
bunch
of
different
organizations?
And
how
can
we
structure
things
in
such
a
way
that
if
those
things
we
collaborate
on
succeed
greatly,
everyone
gets
rewarded.
Everyone
who
contributed
to
that
thing
gets
rewarded
fairly.
Like
that's,
you
know
super
hard
to
to
try
and
solve,
but
you
know
we
want
to
want
to
do
that.
So.
A
C
A
B
B
One
of
them
is
IP
is
by
nature
what
I
like
to
call
it
fully
distributed,
or
logically
decentralized,
italic
allsup,
which
is
that
the
the
nodes
in
the
exercise
network
and
continue
talking
to
each
other,
even
if
the
rest
of
the
network
disappears
and
so
file
coin,
because
it
used
ipfs
and
so
on,
thought
the
nodes
will
be
able
to
talk
to
each
other,
even
if
they
can't
talk
to
the
rest
of
the
network.
Now,
there's
a
question
they're
like
how
can
you
clear
transactions
and
like
that?
B
That's
the
thing
that
we
have
active
and
deep
research
on.
We
want
to
have
a
network
that
can
shard
and
where
you
can
have
a
subset
of
the
path
or
network
operating,
even
if
it
can't
talk
to
the
rest
of
network
and
clear
transactions
to
the
heart
problem.
The
first
iteration
of
of
the
talk
and
I
where
that
goes
live,
won't
quite
do
that,
but
the
way
it'll
be
in
so
there's
like
you
know.
B
If
you
get
isolated
from
the
wrestle
Network
you,
you
may
not
be
able
to
clear
transactions,
but
you
might
be
able
to
distribute
files
up
where
at
least
for
some
period
of
time,
and
then,
if
you
are
in
the
rest
of
network
but
then
like
how
it
disappears
because
of
some
huge
natural
disaster,
I
guess
slightly
less
than
1/2
+
n
/
2.
We
can
survive
those
failures
because
when
people
add
data
to
the
network,
it
gets
split
up
into
pieces,
get
erasure
coded.
B
So
you
can
get
like
this
really
nice
replication
factor
where
without
adding
too
much
overhead,
we're
like
the
replication
factor
does
not
add
massive
overhead.
You
can
get
a
huge
resilience
factor
where
you
know
you
can.
You
can
survive
huge
numbers
of
failures
and
your
data
can
still
be
there.
The
exact
numbers
on
this,
like
will,
will
come
up
with
and
publish
the
exact
details
on
those
down
the
road,
but
it's
going
to
get
tunable
parameter.
So
you
can
like
crank
up
the
the
level
of
erasure
coded
as
effectively
that
you
want
and.
B
If
you
have
a
megabyte
of
data,
that's
really
important.
You
just
like
crank
up
the
replication
factor
and,
like
the
you
know
that
originally
splitting
into
pieces
and
erasure
coding,
so
that
you
have
like
hundreds
of
these
and
like
now,
you
and
they
go
all
go
out
to
a
whole
bunch
of
different
miners.
And
so
now
you
are
in
a
much
better
position
than
then.
If
you
know,
only
three
people
were
like
we're.
Storing
this
set
gets
one
one
photo
in
circa.
C
B
B
There's
the
reason
for
for
that,
though,
we
can't
announce
an
exact
date
yet
is
that
we
there
are
a
few
like
things,
especially
on
around
there's
a
couple
of
processes
that
are
running
right
now
that
we
have
kind
of
like
a
date
that
they
were
going
to
finish,
and
that's
ideally
a
week
or
two
weeks
out,
but
if
there's
a
little
bit
of
unpredictability
yet
there
so
I
want
to
be
able
to
do
the
sale
as
soon
as
possible.
But
you
know,
subject
to
that
so
really
like
weeks,
but
expect
news
very
very
soon.
B
Coin
list,
which
is
another
project
that
that
protocol
app
started.
This
is
a
and
this
is
an
internship
with
angellist,
and
this
is
a
token
sale
platform.
That
kind
of
will
allow
token
project
creators
to
launch
their
networks
and
run
token
sales
without
having
to
slog
through
the
hundreds
of
hours
that
we
spent
both
building
this
kind
of
platform
and
going
to
legal
and
so
on
and
pointless
works
with
the
shaft
it
colas
will
have.
We
worked
with
a
lot
of
sales
that
are
both
include
assassins.
B
Others
don't,
but
basically
like
there's
this
important
piece
that
if
you
want
to
run
a
token
sale
in
the
US,
you
want
to
there's
like
a
question
there
around
whether
or
not
you're
selling
a
security.
And
if
you,
if
you
think,
you're
indeed
selling
a
security,
then
you
should
limit
it
limit
the
sale
of
that
security
to
accredited
investors,
at
least
in
the
US,
and
when
you,
when
you
do
that,
then
Cornelis
makes
that
easy
and
you
can
accredit
in
the
same
way
that
you
would
accredit
to
through
AngelList.
B
But
you
know
that
does
not
even
like
the
main
selling
point
Aquinas.
The
main
selling
point,
of
course,
will
be
decreasing
the
amount
of
work
for
token
co-creators
and
creating
a
network
that
is,
that
focuses
on
finding
really
high
signal
projects
right.
So
there's
a
ton
of
projects
in
the
space
and
the
one
of
the
things
that
we
care
a
lot
about
is
how
do
you?
How
do
you
find
really
really
good
projects
and
and
help
those
gain
attention
and
kind
of
like
stick
out
and
and
how
can
you
help
them?
B
Prove
it
right
like
it's
one
thing
for
that
project
to
kind
of
like
convey
a
lot
of
things,
but
it
becomes
really
useful
when
you
have
third
parties
that
are
independent,
think
about
those
projects
and
and
and
kind
of
have
fun
yeah
we're
very
interested
in
solving
that
signal
problem.
How
do
you,
how
do
you
correctly
figure
out
what
other
really
solid
and
outstanding
projects,
and
so
we
think
that's
going
to
be
an
important
value
proposition
from
Coyle,
I
stuff
like
really
finding
the
best
things
around
that.
B
So
we've
got
a
you
know,
a
ton
of
applications
and
it's
a
lot
of
interesting
stuff
is
it's
coming
down
the
pipeline.
Some
live
really
really
cool
stuff.
We've
also
seen
you
know
some
some
scams,
like
we
we've
actually
like
seen
some
applications
that
are
like
outright
outright
scams.
I
think
you
know
we
don't
want
to
be
in
a
position
of
being
like
effectively
gatekeepers
that
prevent
really
good
ideas
from
from.
B
If
we
don't
understand
something
we
shouldn't
be
kind
of
like
gay
people,
gay
keepers
that
we
have
to
convince,
but
on
the
flip
side
we
also
don't
want
things
that
we
can
tell
are
outright
scams
on
a
platform
and
we
want
at
least
you
know
some
layer
of
like
barriers
there
to
make
sure
that
the
projects
that
do
get
listed
on
coin
list
pass
a
certain
bar
of
quality.
Now
there
could
be
some
very
cleverly
engineered
and
designed
scams
or
whatever
that
that
fool,
even
us
or
whatever.
B
So
you
know
anyone
investing
through
any
kind
of
a
management
platform.
It's
ultimately,
you
know
responsible
for
doing
their
own
diligence,
but
at
the
very
least,
we're
going
to
think
cut
out
a
huge
fraction
of
a
lot
of
those
things
and
we're
working
on
ways
of
helping
project
creators
highlight
their
technical
strengths
and
their.
B
You
know
the
the
create
the
value
they
propose
in
ways
that,
like
let
them
shine
against
other
projects
that
could
probably
spend
a
whole
bunch
of
money
on
marketing
and
so
on,
but
actually
really
have
no
important
technical
depth
underneath
the
hood,
and
so
that's
a
whole
bunch
of
interesting
problems
that
we
want
to.
We
want
to
help
stop
the
process.
Okay,.
B
Part
of
that
yeah,
yeah
and
I
think
a
Korean
investor
is
kind
of
weighing
in
on
things.
It's
an
important
part,
although
I
would
say
you
know,
I
think
this
is
an
important
piece
or
we're
gonna
have
the
message
is
better
in
that
not
all
sales
that
will
go
through
points
are
going
to
be
only
for
credit
investors.
There
will
be
some
sales
that
are
not
securities
and
then
you
know
people
can
can
buy
normally,
and
there
also
will
be
the
case
that
some
sales
might
want
to
do.
B
Our
reg
reg
D
506
C,
offering
in
the
u.s.,
so
that's
accredited
investors
only
but
are
able
to
do
a
reg,
S
funding
to
the
rest
of
the
world
and
do
and
figure
out
things
outside.
So
this
is
kind
of
similar
to
what
blocking
capital
did
so
we're
looking
deeply
into
that,
and
we
want
to
lend
up
we
want
to
we.
We
expect
that
number
of
tokens
we'll
be
able
to
do
that.
B
I
can't
definitively
say
that
they
will
certainly
be
able
to
do
that
because
there's
some
thousand
legal
questions
there
that
we
need
to
solve,
and
additionally,
we
want
to
involve
crowdfunding
as
well.
We
think
that
it's
very
important
that
people
in
the
US
that
are
not
accredited
but
that
understand
the
tech
really
well
and
are
able
to
make
investments
like
that.
It's
just
the
the
burden
on
on
doing
crowdfunding
is
quite
quite
large
and
there's
you
know
those
questions
is
like:
how
does
that
combine
with
your
currency?
B
There
were
a
lot
of
people
investing
things
that
had
a
lot
of
money
and
could
lose
it
on
things
that
didn't
work
out
and
a
lot
of
people
that
understood
that
something
like
a
theorem
was
gonna
be
really
valuable.
So
we
want
to.
We
want
to
enable
people
to
come
into
these
things
like
this,
and
so
we're
looking
at
crowdfunding
we're
also
looking
at
other
ways
of
potentially
involving
people
that
you
know,
for
whatever
reason
they
can't
directly
invest
in
the
presale,
but
maybe
we're
perhaps
they
can.
B
They
can
come
in
when
the
token
goes
live
in
an
actual
token
sale,
broader
in
in
like
live
exchanges
at
a
discount
at
some
sort
of
discount
that
that
puts
them
into
it
in
a
good
position,
but
it's
like
sometimes
that
can
be
done
by
instead
of
it
coming
in
and
investing
early
rather
helping
the
network
right.
So
one
of
the
big
parts
of
get
gathering
investors
to
network
like
this
is
is
gathering
people
that
are
really
well
aligned
with
the
network
and
want
to
help
it
grow
and,
like
that's
that's
what
investors
should
be.
B
Investors
should
not
be
just
like
random
speculators
that,
like
are
just
trying
to
make
a
quick
buck.
We
are
interested
in
helping
create
large-scale
communities
that
have
like
really
strong
buy-in
from
people
that
want
to.
You
know,
help
create
them,
and
you
know
see
the
promise,
and
so
one
of
the
things
that
we're
talking
about
like
okay,
great,
like
there's
a
lot
of
people
that
you
know
maybe
are
unfortunately
limited
by
the
laws
around
accreditation.
However,
they
probably
have
the
ability
to
get
in
law
actually
involved
directly
with
the
projects
and
contributing
in
another
way.
A
A
B
And
I
mean
Falcone
is
not
to
be
seen
as
a
drop
box
replacement,
although
there
will
be
drop
box
like
things
that
build
on
build
on
top
of
point,
I
think
you
should
think
about
Falcone
as
as
replacing
cloud
storage.
So
it's
something
that
Dropbox
would
use.
So
so
a
company
like
Dropbox
should
would
think
about
like
oh,
do
we
run
our
own
managed
infrastructure,
or
do
we
use
AWS
or
do
we
use
something
like
five
point?
And
so
that's
where
the
the
economic
improvement
comes
with
like
it
was.
B
B
One
is
like
another
provider,
think
about
power
point
as
a
market,
so
some
five-point
is
a
market
layers
across
all
providers
and
enables
a
whole
bunch
of
providers
that
right
now
are
not
selling
data
in
the
world
to
come
in
and
sell
it
so
think
about
how
much
storage
there
is
on
the
planet.
That
right
now
is
not
being
sold
to
other
people
and
that
if
that
storage
came
online,
it
would
drive
the
price
down
in
the
storage.
That
right
now
is
depreciating.
B
A
lot
of
people
have
invested
huge
amount
of
money
in
having
massive
arrays
of
hard
drives
that
are
not
giving
them
any
money,
and
you
know
losing
money
on
those
investments
and
to
think
about
creating
a
market
that
enables
anybody
to
then
sell
all
that
storage
to
the
rest
of
the
world
and
make
a
you
know
for
profit,
and
you
know
there's
a
whole
bunch
of
questions
that
are
like
wow.
Can
you
really
achieve
you
know
economies
of
scale
with
a
network
like
this?
Can
you
really,
you
know,
get
a
better
unit
economics
of
like?
B
Can
you
can
you
provide
bytes
cheaper
than
something
like
Google
cloud
or
Amazon
or
whatever,
and
our
bet
there
is
that,
yes,
that
there's
a
whole
bunch
of
places
and
cases
where
certain
individuals
or
groups
in
the
world
have
access
to
either
really
cheap
storage
or
storage?
That's
positioned
well
in
the
network
that
is
kind
of
like
you
know,
somewhere
between
the
backbone
and
like
a
whole
bunch
of
consumers,
and
if
they
become
falkland,
miners
and
search
nodes,
they
could
actually
be
in
a
better
optimization
point
than
even
something
like
Amazon.
B
And
so
that's
you
know,
that's
the
bet,
and
we
think
it's
it's
right
and
like
that
on
its
own
is
like
an
interesting
interesting
reason
for
people
to
opt
in
to
something
like
five
coin
and
and
so
yeah
I
think
about
it.
Kind
of
like
an
algorithmic
market
say
instead
of
this
having
a
very
inefficient
market
where
you
have
to.
B
When
you
want
a
higher
storage,
you
have
to
go
and
like
research
companies
and
you
have
to
look
at
them
and
you
have
to
like
sign
up
with
them
and
create
you
know
you
have
to
be
a
legal
entity.
You
have
to
be
either
a
person
or
a
company
and
or
whatever
like
you
have
to
like,
have
a
credit
card,
and
it's
like
by
you
know:
you
enter
into
some
legal
agreements
and
then
you
enter
into
legal
agreement.
B
Then
you
can
send
the
bytes
like
this
huge
onerous
process
and
when
you
compare
them,
you
like
see
their
websites
and
so
on
to
something
closer
to
Lex
like
spot
market
where
any
file
any
storage
that's
available
worldwide.
But
that
has
shown
to
have
good
metrics
and
you
shown
to
be
online
for
the
long
period
of
time
shown
to
be
good
or
whatever
can
then
be
sold
to
you
at
the
cheapest
possible
price
that
you
can.
You
want
immediately
algorithmically
right
like,
and
so
this
is
about
changing
the
market
completely.
A
B
B
That's
doesn't
in
some
questions
that
people
should
look
into.
Can
I
cross
this
storage
so
with
in
some
ways
you
will
be
able
to
in
other
ways
you
won't
so
so
it's
actually
like
it
is
very
protocol
dependent
and
different
verticals
a
lot
of
different
ways.
Some
some
of
the
things
you
won't
be
able
to
cross
this,
some
of
the
things
you
will
be
able
to
cross
list,
and
so
there
will
be
some
kind
of
like
there.
People
will
try
and
get
trying
to
game
it.
B
A
little
bit
yeah
I
mean
like
I
mean
people
are
participating
to
different
networks,
I
mean
like
they're,
storing
data
so
because
of
the
proof
of
replication,
when,
when
you
have
proof
replication,
backed
storage,
that
that
ensures
that
it
is
unique
to
this
particular
request
and
that's
very
important
same
for
my
game.
Theory
perspective.
Like
you,
don't
want
people,
you
don't
want,
like
networks
of
stables,
basically
pretending
to
be
storing
huge
amounts
of
data
when
they're.
Only
storing
like
one
copy
like
the
thing
is
not
replicated.
B
So
that's
what
the
perfect
replication
is
therefore,
and
so
some
things
you
won't
be
able
to
across
this,
but
some
things
like
for
fast
retrieval
and
so
on.
Like
those
those
are
we
cross
the
scible
and
but
I.
Think,
like
answering
the
question
in
like
a
deeper
ways,
it's
like
I
think
I
look
at
path
line
of
something
very
different
in
these
other
networks.
B
It's
not
solving
exactly
the
same
problem
if
I'm
still
thinking
the
problem
of
like
how
do
you
create
a
market
and
allow
any
provider
so
there's
actually
a
possibility
where
SIA
and
storage
make
sense.
As
you
know,
route
route
content
to
them,
because
if
those
networks
provide
kind
of
like
a
tiered
structure,
okay,
we'll
see
what
happens.
A
B
Well,
it
depends
on
how
you
this
is
not
hyperbole.
In
the
whole
sense,
there
are
some
ways
and
you
can
take
that
question.
Lts
prevention
and
say:
oh
well,
no,
you
can't
possibly
mitigate
all
possible
DDoS
attacks
on
something,
but
the
way
to
think
about
access
is
that
when
you
have
a
piece
of
content,
once
you
have
the
piece
of
content
or
anybody
else
around
in
the
network
has
it
you
can
retrieve
it
from
them
and
it
doesn't
have
to
come
from
the
original
source.
B
So
we've
already
seen
cases
where
people
you
know:
can
das
a
specific
location
and
like
it
can
das
a
URL
that
that
some
resource
is
that.
But
if
it's
a
it's
a
name
that
you
know
you,
you
know
some
providers
that
have
that
content
and
you
can
reach
them.
But
the
das
attackers
can't
know
who
those
providers
are
for
a
whole
bunch
of
there
could
be
a
lot
of
reasons
for
this.
B
It
could
be
like
they're,
actually
disconnected
you're
in
a
network
that
they're
not
connected
to,
or
you
have
access
to
a
like
a
network
where
you
have
the
ability
to
search
through
a
whole
bunch
of
nodes
that
are
willing
to
share
routing
information
with
you,
but
are
unwilling
to
open
it
broadly
to
the
whole
world.
This
is
this
is
kind
of
like
a
this.get
starts
getting
into
private
networks
like
when
people
people
are
building
private
ipfs
networks
where
they
have
their
own
set
of
content.
B
That
is
not
as
opposed
to
the
rest
of
the
world
and
so,
for
example,
you're
going
to
be
able
to
like
search
through
through
some
networks
like
that
and
like
right.
There
alone,
like
you,
have
like
entire
barriers
where,
where
people
like
the
doctors
that
can't
even
get
to
the
content,
first
of
all,
what
I
can't
get
to
the
machines
that
are
serving
it
so
that
solves
it.
B
The
other
case
is
hey
like
if
there's
some
really
popular
piece
of
content
and
something
gets
replicated
to
tons
of
people
now,
the
DOS
attack
gets
way
harder
right
like
now.
Now
you
have
to
does
thousands
of
people,
and
so
it's
not
it's
not
fundamentally.
In
that
particular
case,
it's
not
that
it's
impossible.
It
becomes
intractable
so
because
intractable
work
for
it
for
even
a
sophisticated
attacker
to
das,
all
possible
computers
that
that
have
this
piece
of
content.
B
So
this
will
be
especially
with
like
really,
you
know
incendiary
things
that
a
lot
of
people
want
to
replicate.
Think
about
like
WikiLeaks
type
stuff.
A
lot
of
people
want
to
replicate
it
all
over
the
place
and
then
very
quickly
will
become
very
difficult
for
an
attacker
to
actually
silence
all
possible
machines,
and
so
it
is
not
hyperbole.
It
is
impossible
in
some
cases
and
then
intractable
in
others.
Ok,
cool!
That's
a
good
answer!.
A
B
B
Or
you
know
things
like
messengers
and
so
on,
and
all
of
that
flow
of
information
is
passing
through
a
set
of
centralized
agents
that
can
be
brought
down
and
frequently
are
brought
down.
You
know
there's
like
a
lot
of
cases
where
github
does
go
down
or
slack
does
go
down
or
your
connection
to
them
gets
severed
in
some
way.
Look
you
just
can't
reach
them,
like
maybe
you're
offline
or
whatever.
B
B
Next
to
each
other
and
our
piping,
all
of
the
data
flows
straight
up
the
up
the
uplink
straight
into
the
data
center
and
then
back
and
that's
just
stupid
like
it
wrong,
and
we
should
not
live
in
that
world
and
so
I
want
to
live
in
a
world
where,
if
you
have
a
computer
and
you're
trying
to
work
with
somebody
across
from
you,
the
data
can
flow
from
one
person
to
another,
and
you
can
continue
working.
Whether
or
not
some
random
machine
somewhere
else
in
the
world
is
failing.
So.
B
It's
an
infrastructure
thing.
It's
like
there's
a
whole
bunch
of
cases
where,
where
it's
like,
the
underlying
you
have
you
want
to
think
about
how
the
underlying
data
flows
move
and
answering
the
question
for,
like
the
etherium
case,
it's
really
about
power,
it's
like!
Where
do
you
want
people
to
be
able
to
exert
power
and
like
doing
a
transaction
through
etherium
and
happening?
A
I
think,
with
a
lot
of
these
things,
like
you,
don't
necessarily
have
to
make
it
obvious
to
the
end-user
that
this
is
what
you're
doing
it
just
works.
It's
better,
so
Eric
ask
one
more
question
around
decentralization
so
where
and
how
does
decentralization
gain
advantage
over
centralized
benefits
where
you
think
about
scale
and
cost.
B
B
You
can
get
like
providing
cheap
storage
to
the
world
or
cheap
distribution
of
content
to
the
world
is
a
huge,
optimization
problem
right,
like
you're
dealing
with
you
know
billions
of
computers
in
the
rounded
planet
that
are
all
trying
to
store
or
retrieve
content
and
a
whole
bunch
of
places
where
you
can
store
it
and
move
it.
And
then
you
are
dealing
with
again
billions
of
people
that
are
using
those
computers
and
that
some
subset
of
those
billions
of
people
could
actually
work
on
on
maintaining
that
I
work
in
some.
B
Cheap
connectivity,
cheap
storage,
cheap
disk
whatever
and
enabling
them
to
bring
in
and
create
a
service
right,
and
so
it's
kind
of
like
I
get
some
deeper
way
to
look
at
it
is,
do
you
think
markets
are
more
efficient
or
do
you
think
central
planning
is
more
efficient
and
there's
a
lot
of
you
know.
Looking
at
this
question
kind
of
naively,
it's
like
well,
you
know
it
like.
The
naive
answer
is
like
well,
markets
are
better
and
because
you
know
central
planning
is
that
and
the
the
slightly
deeper
answer
is
well.
B
No,
if
you
had
like
a
you,
know
massive
computer,
that
it's
able
to
actually
calculate
everything
correctly.
Then
you
could
actually
solve
that,
and
you
could
have
you
know
correct
allocation
of
resources
by
just
with
one
program.
But
then
the
even
deeper
version
of
that
is
not
all.
Agents
are
similarly
incented,
which
means
that
one
agents
might
produce
an
answer
that
it
doesn't
is
not
actually
optimal
to
everyone.
B
It's
optimal
to
that
agent,
and
so
markets
are
kind
of
fundamental
in
how
we
operate
and
so
markets
allow
individual
actors
to
you,
know
leverage
optimizations
and
so
like
that's,
that's
a
thing
and
those
are
premises
might
not
be
optimizations
for
somebody
else,
and
so
that
that's
I
think
we're
like
decentralization
enough.
Power
is
really
important
to
these
networks,
in
that,
like
the
centralization
of
power
and
choice
of
how
to
run
the
service
affects
the
kind
of
optimizations
that
people
may
want
to
do,
and
so
on
right.
B
So
a
great
example
of
is
I
know
of
a
lot
of
Bitcoin
mines
that
have
super
cheap
power
and
they're
able
to
get
super
to
power
because
they're
in
a
particular
country
where
they
were
able
to
get
a
certain
deal
or
because
they
know
the
right
people
or
whatever
and
there's
a
whole
bunch
of
reasons
why
they
suddenly
have
much
better
unit
economics
that
then
a
major
player
would
have-
and
you
know
they
don't
have
enough
power-
that
they
could
service
everyone
in
the
world.
But
they
could.
B
B
Man
like
this
there's
a
ton
of
interesting
stuff
like
I,
think
I'll
rattle
up
a
few.
A
few
names
I
think
definitely
a
lot
that
people
already
know
about.
You
know,
of
course,
I
think
if
people
don't
yet
understand
how
the
etherium
works
or,
and
all
that
like
definitely
dive
in
it's
like
the
best
interaction
to
the
to
the
future,
I
guess,
then,
then
Bitcoin
ever
was
or
the
kind
of
stuff
so
definitely
like
dive
into
all
of
that
world.
B
Definitely
look
at
things
like
open,
Bazaar
and
you
know
whole
bunch
of
applications
that
are
being
built
with
with
these
new
kinds
of
networks.
You
know
things
like
Z
cache
and
so
on
that
like
bring
in
a
new
property
into
the
world
and
then
start
looking
at
like
if
we
want
to
think
about
like
new
and
more
earlier
things,
there's
a
whole
bunch
of
like
interesting
developments
around
these
networks.
Like
there's
a
lot
of
people
building
on
aetherium,
there's
like
zero
X,
which
is
a
decentralized
exchange.
B
There
is
life
peer,
which
is
like
a
peer-to-peer
distribution
thing
that
will
be
be
interacting
with
that.
That
aligns
really
well
with
a
lot
of
VIP
plastic
and
the
etherium
tech.
There
are
things
like
pesos,
which
are
like,
which
is
a
project
to
build
a
smart
contracts
platform.
That
is
where
the
smart
contracts
are
written
in
El
camel,
and
you
have
a
lot
more
certainty
about,
like
the
the
programming
language
property,
like
the
properties
of
the
programs.
B
This
really
like
further
out
sayings
that
are
that
are
going
to
come
out.
I,
think
I
would,
if
you're
into
research
I
would
HIGHLY
encourage
you
follow
the
proof
of
stake
line
of
work,
we're
getting
ever
and
ever
closer
and
I
think
we're
quite
close
to
something
that
can
succeed
and
work
at
scale,
there's
already
several
provable
protocols.
So
anyway,
that's
some
some
interesting
stuff.
This
was
great
all
right.
Thanks,
fun,
yeah.