►
Description
We had Alexander Demidko (https://twitter.com/xdralex) from Fluence (https://twitter.com/Fluence_One) speaking with Alex Skidanov (https://twitter.com/AlexSkidanov) on the 17th Episode of the Whiteboard Series.
More about Fluence Labs: https://fluence.network/
Location: NEAR Protocol HQ, San Francisco, CA
Download the video here: https://near.ai/ca580
------- About Whiteboard Series ---------
The Whiteboard Series with NEAR is a set of video interviews with Founders who are building scalable solutions for Blockchain. We deep dive into their story, what they're developing and how it is helping the ecosystem.
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#WhiteboardSeries #FutureIsNEAR
A
B
B
Think
that's
the
beef
tea
OneNote
is
also
50,
so
we're
really
small
ones,
really
small
clusters,
the
beef
tea
ones
and
because
they
are
really
small,
there
is
a
chance
that
some
of
these
machines
can,
you
know,
go
wild.
So
in
order
to
keep
those
guys
in
check,
we
use
a
share,
it
validation,
layer
and
the
validation.
Where
is
shirt?
We
usually
use
this.
You
know
symbol
to
depictive
our
data
because
it
looks
like
we-
and
this
is
basically
shared
validator
spool
and
we
call
this
thin
a
security
layer
and
it's.
B
I
mean
they
might
be,
I
mean
you,
you
can
have
I
mean
you
can
have.
This
is
different
software
in
some
kind
of,
but
you
can
have
this
like
one
single
hardware
machine
to
run
both
the
real-time
node
and
a
validator.
So
the
way
it
works
I
mean
how
do
those
guys
keep
each
other
in
check?
Is
that
real-time,
we're
basically
uploads
every
time
when
well?
There
is
also
client
and
here's.
The
client
and
I
will
draw
a
mobile
phone.
B
So
the
white,
client
or
the
thin
client
interacts
with
the
real
time
we
are
only
and
every
time
like
the
way
how
interaction
goes.
The
client
sends
requests,
which
is
like
transaction
essentially
and
receives
a
response
from
the
real
time
where
and
for
the
validators,
for
the
security
where
to
verify
the
real
time,
where
the
real
time,
where
stores
transactions
into
a
decentralized
storage,
and
for
this
purpose
we
use
like
swaram,
you
can
also
use
file
coin
I
mean
honestly
right
now.
B
We
expect
that
in
theory,
those
storages
you
support
basically
in
like,
if
say,
for
example,
if
you
take
a
look
at
this,
one
paper
form
paper
talks
about
how
it
can
force
nodes
to
return
you,
the
data
you
have
put
there,
basically
to
how
to
guarantee
that
it
will
return
the
data
there
and
if
it
will
not
return
you.
The
data
then
like
this
knows
who's
the
deposits.
But
if
you
look
at
what
swarm
does
currently
have
in,
you
know
what
deployed
they
do
not
have
this
like
incentivization
layer.
B
B
B
B
B
B
Well,
it's
I
mean
it
basically
will
make
the
water
on
those
classes,
irregular
I,
would
say
it's
like
yeah,
so
those
classes
I
used
to,
for
example,
a
steady
transactions
like
in
common
rate,
but
once
they
have
to
upload
the
snapshot
somewhere,
that's
kind
of
like
might
decrease
the
ability
to
process
transactions,
so
no
those
guys
do
not
do
not
process
name
shots.
So
only
what
liters
are
produced
snapshots
so
yeah.
They
basically
read
those
transactions,
this
history
and
snapshots,
and
produce
the
new
snapshot.
If,
during
the
block
processing,
they
do
not
agree
with
him.
B
Basically,
with
the
results
they
get,
they
can
file
a
dispute
so
but
first
of
all
let
me
get
to
how
do
they
not
agree?
So
in
the
end
of
the
of
each
block,
we
like
the
currently
here
in
the
real-time,
where
we
use
tender
moment
as
the
VFD
consensus
agent,
essentially
so
in
tender
mint
after
like
in
the
end
of
each
block.
You
also
you
not
only
put
transactions
there.
You
also
put
the
hash
of
your
state,
and
that's
also
is
stored
here
in
swarm,
so
we
have
like,
for
example,
after
each
block.
B
We
have
here
Hershey
virtual
machines
and
half
of
your
machine,
sub
n,
plus
1,
h,
vm
sub,
1,
plus
2,
and
so
on.
So
what
datums
go
over
those
blocks
and
if,
basically,
when
they
are
trying
to
apply
a
new
block
to
the
current
state,
if
they
produce
a
different
hash,
then
they're
like
okay
I
mean
it
doesn't
work
out.
So
let's
basically
point
the
garment
to
those
guys
so.
A
A
B
And
anyways,
so
we've
got
like
those
guys
free
transactions
and
those
guys
read
snapshots
and
if
they
like,
for
example,
one
of
those
for
the
80s
dot
instead
of
hash
have
some
BAM.
It
got
hash,
sub-brand,
prime,
it
clearly
like
doesn't
match
and
they
submit
a
dispute
and
they
submit
a
dispute
to
theorem.
B
Okay,
so
once
the
dispute
is
submitted
to
a
film
well,
those
guys
have
to
I
mean
a
film
is
obviously
is
not
able
to
download
the
entire
state
and
is
not
able
to
don't
her
downward.
Even
the
block
I
would
say
of
transactions
to
basically
replay
that
what
those
guys
are
doing.
They
are
playing
a
concept
code,
verification
game
and
that
was
basically
proposed
by
true--but
and
the
way
it
works
like
you
execute
a
program
instruction
by
instruction
and
if
it's
some
instruction,
you
found
that
you're.
B
Basically
your
stage,
you
have
achieved
different
state,
then
you
counterparty,
then
you
say
well,
this
instruction
is
the
bad
one,
and
you
don't
have
to
do
this
like
in
a
linear
fashion.
You
can
do
like
a
basic
search
so
once
those
guys
have
found
by
the
instruction
they
take.
The
chunk
of
the
state
that
is
was
used
by
this
instruction
as
an
input
like
say
for
low
I
mean
at
not
an
expense.
For
example,
if
you
have
instruction
I
set
you
to
add,
this
instruction
obviously
uses
this
stack.
B
It
basically
takes
two
Whaley's
from
the
top
of
this
stack
here
and
it
then
pushed
one
value
back
to
the
top
of
the
stack
and
it
consumes
those.
So
it's
like
pop-
and
this
is
why
push
one
so
in
order
for
the
like,
for
the
virtual
machine
on
a
theorem
to
operate,
you
have
to
give
it
like
this
chunk
of
memory,
and
you
also
have
to
give
it
the
chunk
of
memory
where
this
stuff
you'll
be
written.
Do.
A
B
You
can
build
only
the
half
of
the
chunk
and
then
you
compute
the
the
entire
hash.
The
problem
is
that
it
still
might
be
too
much
for
a
theorem,
smart
contracts,
and
so
we
are
looking
and
how
optimize
that,
because,
like
the
chunk
like
it
might
be,
four
kilobytes
and
transferring
four
kilobyte
still
might
not
be
also
like,
like
the
brightest
idea
anyways.
So
once
those
guys
have
pushed
this
into
the
virtual
machine
on
a
theorem,
it
basically
execute
the
instruction
produces.
B
A
A
A
B
If
all
of
those
holiday
tours
agree,
if
all
of
them
received
the
same
hash,
then
like
only
the
first
one,
who
has
a
port
at
this
state,
like
is
I,
mean,
has
to
upload
this
state.
If
any
of
those
validators
disagree,
they
also
have
pay
the
same
verification
game
between
each
other.
It's
like
you,
don't
actually
like
either
they
all
agree
or
like.
If
there
is
some
disagreement,
then
someone
will
like
lose
money
and.
A
B
No
okay
was
there
was
there
was
one
more
thing:
yeah
yeah
you
because,
like
you,
don't
want
to
upload
the
half
of
each
block
to
assume
that
also
you'll
be
too
expensive.
So
we
have
a
separate
layer.
We
should
probably
probably
should
talk
about.
Let
me
I
mean
once
we
got
to
the
validators
model.
Let
me
let
me
describe
that
I
guess
so
you
can.
Man
should
be.
B
Like
if
you
mentioned
multiple
validators,
so
let
me
try
to
explain
how
that
thing
works.
So,
first
of
all,
voters
are
selected
completely
by
random
from
the
validator
spool
and
the
way
it
works.
Basically,
all
the
active
editors
they
have
to
register
on
the
theorems
must
contract,
and
then
you
have
a
like
Randall
random
number
generator
that
you
can
use
to
choose
one
of
those
auditors
and
evaluator.
Once
it's
like
selected.
It
must
it
must
execute
the
history
fragment.
B
Otherwise,
if
it
does
not
do
that
within
a
certain
time
out,
which
I
probably
should
talk
about
so
I
will
I
will
put
a
reminder
for
myself
here
time
outs
in
in
this
case
it
will
like
who's
it
like
a
small
fraction
of
feasible.
It's
like
it
will
not
with
the
entire
deposit,
because
it's
like
like
a
minor
offense,
but
it
will
was
like
a
fraction
of
that.
So
the
way
it
works.
So
once
you
have
selected
one
void,
ATAR
and
this
whole
data
is
verifying.
This
beefed
equals
rate.
B
Now
you,
after
this
auditor,
you
also
select
another
validator,
and
you
also
select
is
for
date
by
random
from
the
entire
pool
and
what
else
happens
like
once
when
this
way
data
is
selected,
it
does
not
know
if
there
will
be
another
validation
or
not
so
the
way
it
works.
We
are
saying
that
and
what
the
next
validation
will
happen
with
the
probability
P.
So
this
means
that,
because
in
this
case
it
will
be
geometric
distribution.
In
this
case,
the
expected
value
of
the
number
of
validations
will
be
P
divided
by
1
minus
P.
B
So
if
say,
for
example,
you
put
I,
don't
know
what
here
like
P
equals
4/5,
then
in
this
case
this
will
be
4
yeah.
So
you
can,
you
basically
can
can
control
the
expected
value
of
the
number
of
validations,
but
the
idea
is
that
you,
you
don't
really
know
if
there
will
be
another
validator
or
not
so
the
raw
data
that
goes
last
so
here
we
probably
will
go
yet
to
the
proof
independent
equation.
This
was
proposed
by
Jason
Drake.
B
The
idea
was
that
each
validator,
when
it
valid
is
it,
has
to
provide
basically
build
like
I,
would
say
a
fingerprint
of
the
execution,
and
this
fingerprint
of
the
execution
is
specific
to
the
activity.
So
later
only
so
this
hold,
it
will
produce
the
proof
p1.
This
will
produce
the
proof
b2,
and
this
will
produce
the
proof
p3
and
also
while
this
void
is,
is
like
performing
the
verification
it
will
like
well
this
one.
A
Idea
that
here
is
that,
if
I
as
adversary
control
certain
number
of
validators,
there
is
never
a
moment
for
me
when
I'm
certain
that,
if,
if
I
fake,
all
the
so
so,
let's
say,
I
managed
to
fake
few
validations
after
certain
extent
right.
The
idea
is
that
even
if
I
know
that,
even
if
I
control,
the
next
validation
I
still
have
a
risk
that
the.
B
A
A
B
In
our
case,
the
idea
was
basically
to
make
the
computation
of
the
proven
execution
really
like
the
overhead
really
well,
so
you
don't
have
a
reckon
incentive
to
remove
that,
and
also
the
idea
is
like,
if
you
catch
this
guy,
like
that,
this
guy
has
produced
an
incorrect
or
maybe
an
execution.
Then
well
you
you,
you
go
get
a
fraction
of
its
like
of
this
guy
deposit,
but
I
mean
yeah
I
mean
in
theory
like
you
could
like.
I
would
expect
someone
to
go
and
modify
the
source
code
and
remove
this
like
proof.
A
The
idea
right
now
is
that,
if
I'm
validator
number
five
as
I'm
executing
the
code
of
the
query,
whenever
I
need
to
compute
my
well,
we
didn't
go
much
into
proof
from
independent
execution,
but
whenever
I
need
to
compute
my
hash
of
the
state
in
the
present
binary
I
will
also
compute
hash
of
everybody
else.
Yeah
and
you're
saying
the
incentive
to
recompile
the
binaries.
It's.
A
B
Do
like
to
actually
verify
the
proof.
Okay,
let
me
probably
talk
about
time
outs,
because
there
is
also
again
like
a
potential
like
you
know,
problems
here
so
the
way
so,
first
of
all,
before
talking
about
time,
outs,
I
probably
should
talk
about
like
few
accounting.
So
we
use
very
similar
like
approaches
like
what
the
theorem
does.
We
use
a
few
so
the,
but
here
we
have
a
kind
of
different
thing.
B
B
So,
first
of
all,
there
is
like
a
complexity
of
instructions
which
is
like
we
read
like
similar
to
what
you
found
like
in
the
theorem,
although
we
have
complexity
of
web
assembly
instructions,
and
but
second
thing
is
so
first,
you
have
algorithmic
complexity
and
the
second
thing
is
amount
of
allocated
memory,
so
these
machines
they
have
to
allocate
memory.
We
haven't
like
for
like
right
now,
if
you
focus
only
on
the
memory.
B
Like
you
know,
in
memory
stuff,
you
haven't
only
touch
disk
master
I'm
not
going
to
talk
about
that,
but
you,
for
example,
can
tell
those
guys
I
need
four
gigabytes
of
memory
or
when,
once
when
assembly
supports
more,
you
can
say:
I
want
like
32
gigabytes
of
memory,
but
anyway,
like
the
developer
can
have
control
over
how
much
memory
she
wants
to
allocate
and
yeah.
So
there
is
memory,
but
the
problem
is
memories.
Memory
is
not
really
like.
If
you,
if
you
calculate
the
algorithmic
complexity
of
the
microbe
assembly
program,
it's
like
equal
to
work.
A
B
B
B
B
B
Yeah
so
the
way
the
way
it
works.
So
we
have
you,
have
this
thing
and
we
also
I
mean
remember.
We
have
spoken
that
we
have
to
compute
the
hash
of
the
virtual
machine
and
we
also
said
that
the
hash
is
like
localized
is
in
your
question.
So
imagine
that
that
you,
for
example,
need
to
put
to
perform
a
single
put
request
like
right,
just
one
bite
into
the
memory,
but
your
memory
is
like
four
gigabytes
and
your
chunks
are
probably
like
four
kilobytes.
Let's
say,
let's
say
like
that.
So
now
are.
B
Is
pure
like,
yes,
those
guys
have
like
yeah
if
we
go
bicep
reallocated
and
I
mentioned
that
the
let
me
show
you
like
the
issue
here.
You
have
the
say,
for
example,
you
have
a
miracle
tree
and
bring
it
this
way,
and
this
Merkle
tree
has
like
eight
chunks
is
like
four
kilobytes
and
I'm
going
to
write.
Amazon
developer
have
written
a
program
that
writes
a
single
bite
into
chunk.
So
now,
if
I'm
just
calculating
the
algorithm
complexity
of
this
thing,
it's
quite
well.
B
So
writing
one
byte
is
pretty
small,
has
pretty
small
complexity
but
we're
computing.
The
macro
hash
of
this
chunk
and
this
one
and
this
one
I
can
risk
a
propagating
all
the
way
to
the
top.
It's
like
pretty
expensive,
because
you
also
have
to
calculate
the
hash
of
this
thing
and
this
and
this
and
so
on,
so
we
also
charge
for
the
code
for
dojin
chunks.
So,
every
time
when
you
write
to
a
chunk,
this
chunk
is
like
Marcos
duty,
but.
B
Yeah,
basically,
we
have
a
Hawaiian
Coulson
and
work
right
into
the
same
like
trying
to
write
to
the
same
page
of
memory
so
anyways,
but
we
have
like
price
for
Georgian
chunks
and
basically,
that's
also
goes
into
this
for
more
dirty
channels.
Multiplied
by
like
some
another
coefficient
and
that's
the
entire
price,
like
that's
the
entire
fuel
price.
How
much
a
developer
has
to
pay
for
that
and
if
the
developer
might
be,
might
be
compensated
or
might
not
be
compensated
for
like
this
show
is
for.
A
B
Write
write
so
I
mean,
if
you
say,
for
example,
have
deployed
it
back
into
its
like
centralized
data
center.
Then
I
can
make
a
DDoS
attack
on
you
and
but
anyways
I
mean
I
mean
here
we
have
a
central
developer
role
here,
which
is
kind
of
makes
things
a
little
bit
centralized,
but
you
can
make
it
more
decentralized
by
saying
well,
each
client
has
to
pay
the
work
to
use
the
service.
Clients
need
to
pay
a
developer,
like
say,
for
example,
at
once
in
a
month,
some-some
or
pay
for
each
transaction
like
somehow.
B
A
A
B
B
A
B
A
High
okay,
but
still
effectively,
that
implies
that
rotation
is
very
possible
right.
So
so
wouldn't
would
it
not
make
sense
like
let's
say
I
want
my
speed
layer
to
be
more
secure.
We
did
not
make
sense
for
me
to
say:
I
want
EFT
consensus
for
four
people:
I,
don't
care
about
link
or
availability,
but
I
want
more
security.
I
want
those
to
rotate,
because
clearly
they
can
write
in
principle.
B
A
A
Let's
say:
I
chose
to
have
one
validator
in
my
tender,
mint
consensus
group
and
then
I
chose
to
have
let
sit
like
probability
6
over
7,
so
we're
going
to
get
6
right.
It
sounds
very
suspicious.
I
know
that
so
good.
That
means
I'm
already
paying
for
six
people
to
every
now
and
then
go
download
my
state
and
validate
right.
A
So
in
essence,
let's
say
that
instead
I
drop
this
guy
or
like
I,
keep
this
guy
doesn't
matter,
but
they
make
those
six
people
to
to
be
more
real-time
and
I'm,
telling
them
to
download
the
stable
state
a
little
in
advance
and
then
validate
in
real-time
for
the
same
amount
of
time.
That
would
give
me
a
slightly
less
security
in
a
sense
that
they,
the
Master
of
Puppets.
Oh
you.
A
What
what
I'm!
But
you
see
what
I'm
saying
right,
I'm
losing
a
little
bit
of
security,
because
the
Master
of
Puppets
now
during
that
epoch,
while
they
validate
me,
they
know
them
all,
and
so
they
know
exactly
whom
to
corrupt,
so
we're
losing
were
losing
that
advantage
of
the
last
validator
right
so
I'm
losing
that
what
what
I'm
gaining
is
that
my
speed
layer
is
significantly
more
secure
right.
B
B
A
B
I
mean
what
could
what
could
be
done?
What
may
think
what
could
be
done
here?
You
can
say,
take
this
for
later
and
like
no,
not
not.
You
take
this
for
later
once
this
validator
is
selected
and
has
done,
ordered
the
state
and
applied
it
and
produce
the
new
state.
Maybe
you
could
replace
this
note
with
the
oh
wait.
Actually,
this
world,
it
will
be
learned
because
it
yeah,
but.
A
A
I'm
not
well
technically,
someone
does
control
the
Slayer
today
like
this.
This
is
the
theorem
chain
with
randomness,
which
says
you
validate
this
now.
So
what
will
change
that
in
a
theory
instead
of
saying
you
validate
it
now
says
you
validate
it
and
half
an
hour
from
now,
so
you
have
time
to
download
state
catch-up
intended
in
sync
right.
B
A
To
hear
the
trade-off
is
the
security
will
be
slightly
less.
That's
that's.
Like
that's
a
philosophical
question.
Is
it
the
case
that
like
if
someone
can
corrupt
two
thirds
of
my
seven
node
cluster
in
principle,
they
can
like
tamper
with
people
who
get
assigned
to
them
totally
with
my
data
set,
but
what
I
get
is
that
my
speed
layers
fast
right?
Sorry,
my
speed
layer
is
secure.
It's
more.
B
A
But
it
is
also
here's
another
sort
of
consideration
which
is
so
those
validators.
You
chose
them
from
some
pool
right
and
presumably
that
pool
it
is
unlikely
that
you
happen
to
to
sample
two-thirds
plus
one
malicious
actors
or
like
even
one
four
plus
1
depends
on
where
you
draw
the
line,
so
we
expect
that
it
will
only
break
if
a
malicious
actor
can
somehow
reach
out
to
them
and
corrupt
them.
Adaptively
right
by
adaptively
I
mean
that
when
I
when
I
created.
So
let's
say
this
is
my
cluster.
A
So
the
secure
layer
protects
me
against
someone,
let's
call
them
an
adversary,
an
adversary
somehow
reached
out
to
them,
so
they
like,
for
example,
let's
say
all
the
validators
are
sitting
in
the
same
disc
or
channel
right,
so
they
want
to
the
disc
or
channel,
and
they
said
if
you
validating
this
cluster
I
will
give
you
your
stake.
X2
for
your
private
key
right.
So
that's
what
we're
trying
to
protect
against.
B
A
Thing
is
that
clearly
this
validator
knows
that
they
will
be
validating
your
your
particular
fragment
for
a
while
right.
So,
let's
so,
let's
say
you
want
them
to
validate
for
like
two
hours
in
row.
That
means
there
is
two
hours
during
which
the
validators
themselves
knows
that
they
are
validating
the
fragment.
You
can
do
some
smart
construction
so
that
nobody
else
knows
until
they
publish
right,
but
but
they
know
that's.
So
that's
what
is
important
so
now
as
an
adversary.
A
What
I
will
do
is
I
will
go
to
discord
and
I
will
publish
a
smart
contract
on
aetherium,
where,
if
you
prove
that
you
got
a
sign
to
this
to
this
fragment
and
you
provided
your
private
key,
you
get
your
stake.
X2
right
right,
so
I
still
can
adaptively
corrupt
I
mean
I'm
still
risking
something
right,
because
I
could
adopt
this
person,
but
I
don't
know
if
there's
going
to
be
next
one
or
rather
I,
don't
know
if
they
will
be
corruptible
but
different
if
I
really
want
to
I
mean.
B
Yeah
I
mean
it's
it's.
Basically,
we
can
tell
like
the
developer
a
price.
Basically,
the
developer
knows
that
those
guys
have
put
that
much
stake
and
the
auditors
will
put
like
that.
Much
stake
and
the
developer
knows
that
if
someone
spends
more
than
this
take
yeah,
then
probably
the
results
that,
like
the
entire,
where
produces
like
you,
will
not
work
but.
A
B
The
I
would
probably
say
that
the
in
this
case
you
so
for
this
case
in
the
speed
where
you
need
to
corrupt
two-thirds
of
the
class,
for
things
like
to
work
in
the
security
where
you
have
to
corrupt
I,
guess
everyone,
and
in
this
case
you
will
be
like
so
it's
like,
basically
corrupt,
all
and
I
would
probably
say
that
if
you
put
everyone
here
so
let's
consider
two
situations.
You
have
seven
nodes
in
real
time
and
you
have
one.
A
But
also
to
an
extent,
it
depends
on
how
how
much
will
be
leaving
the
power
of
the
adaptive
anniversary,
because,
obviously
you
cannot
expect
all
the
sticks
validators
to
be
online,
so
an
adversary
can
provide
them
a
choice.
They
can
either
get
corrupted
for
2x,
they
can
lose
the
stake
or
they
can
just
skip
their
style.
You
can.
B
A
But
let's
say
we
make
small
step.
Let's
say
we
remove
completely
the
security
layer
or
a
shared
validator
pool
yeah,
but
we
made,
but
in
the
tender
mean
consensus,
we're
saying
that
yeah,
let's
you
craft
it
to
third,
but
we
still
making
like
the
remaining
participants
can
still
challenge
right.
They
can
still
fish
yeah.
B
A
B
Yeah
yeah
yeah,
so
I
guess,
if
those
guys,
let
me
think
about
this,
so
I
guess
if
those
guys
are
safe
to
be,
if
those
guys
safe
everything
to
the
data,
I
can
get
you
later,
then
these
could
yeah
I
mean
they
are
not
in
the
consensus,
but
they
are
like
well,
someone
has
cut
us
out
and
they
can
go
here
and
download
the
data
in
the
way
I
Cho
I,
like
I
challenge
you
I'll,
probably
say
that
I
would
probably
say
that's
quite
possible.
So.
A
What
we
lose
so
effectively
if
I
understand
everything
correctly.
The
the
only
thing
we're
losing
in
this
approach
is
that
the
adaptive
adversary
has
full
information
on
whether
the
attack
will
be
successful
before
the
attack
like
in
fact,
they
can
choose
not
to
attack
until
they
have
full
control.
While
the.
A
A
B
A
A
B
Also
I,
would
you
say
that
yeah
this
takes
that
the
world
eaters
have
put
their
basically
kind
of
saying?
Well,
you
can
expect
that
much
security
if
an
adversity
like
say,
for
example,
of
those
nodes
have
put
like
10k
in
as
a
security
deposit.
If
someone
is
going
to
spend
70
K,
you
know
to
break
the
thing
like
yeah
right
like
50.
Well,
no,
actually,
like
you
also
need
to
grab
those
like
70
k,
then
yeah,
probably
like
you
should
like.
B
B
Let's
talk
about
my
mouse,
so
we
have
just
discussed
like
well
be
like
we
have
few,
and
the
view
is
basic
instituted
from
three
components,
and
the
first
component
is
how
like
what
the
algorithm
complexity
was
of
the
program.
Second
company
is
how
much
memory
was
allocated
for
how
much
time
and
the
third
one
is
like
how
many
chunks
of
the
memory
we
like
made
duty.
So
now
you
have
calculated.
Let's
say
you
have
calculated
fuel
and
once
you
once,
you
basically
have
calculated
few
you
can
like.
B
Like
if
the
mode
that
does
not
hold
it
in
a
certain
time,
then
a
fraction
of
his
deposit
is
like
slashed.
Okay,
like
a
small
fraction
like
one
feel
like
one
hundred
one
thousand
one
ten
thousandth,
so
how
the
timeout
is
calculated.
We
basically
take
the
few
and
here's
the
thing
the
few
is
declared
by
this
cluster
because
you,
you
cannot
really
know
how
much
fuel
will
be
spent
without
actually
executing
the
program,
but.
B
B
So
now
you
have
the
real
time
cluster
and
it
might
happen
that
the
real
time
cluster
says
well.
I
have
spent
that
much
view,
but
this
view
is
much
less
than
the
like.
True
amount
of
view.
That
is
required
to
perform
the
computation.
So
now-
and
this
view
is
written
here
in
like
in
those
blogs
how
much
time
how
much
fuel
was
spent
for
like
each
of
those
works.
So
now
you
can
say
if
I
want
to
throw
a
data
fragment
of
history.
B
I
need
to
spend
like
that
much
view,
but
if
the
real-time
cluster
was
lying
about
the
fuel
spent,
then
the
time
on
that
will
be
given
to
divide
it
is
like
really
small,
and
for
this
we
have
like
few
disputes.
So
once
of
all
the
data
comes
and
notices
that
he
was
given
a
really
like
small
amount
of
time.
It
can
execute.
A
few
of
this
good
and
I
feel
disposed
is
really
similar
to
the
just
normal
verification
game
dispute.
You
basically
saying
like
say,
for
example,
these
are
two.
A
B
B
Probably
well
I,
don't
know
the
answer
right
now.
So
probably
we
need
to
think
about
this.
So
let's
finish
with
this
and
then
think
how
we,
how
this
cannot
die
can
be
solved
so
anyways
for
the
time
art
attack.
You
can
say
each
of
those
guys
once
this
guy
has
found
that
he
spent
more
fuel
than
this
guy.
You
can
say
well,
I
want
to
dispute
on
this
part
of
execution,
and
then
you
do
the
same
basic
search
and
you
find
the
instruction
that
has
produced
diversion
amounts
of
you
and
like
the
raw
time
cost.
A
B
B
This
is,
if
you
put
fewer
than
you,
don't
have
any
time
so
for
the
time
out
what
what
kind
of
a
problem
might
happen
here
that
the
like
date,
availability,
where
like
if
an
adversary
tries
to
corrupt
the
data
mobility?
Where
and
say,
hey,
do
not
return
any
like
any
data
to
the
evaluators.
So
they
time
out,
essentially
that
might
help,
might
might
become
a
problem
and.
B
A
B
Like
we
remember
this,
we
said
there
will
be
like
multiple
validations,
so
the
stakes
of
the
real-time
nodes
are
not
released
until
the
camión,
the
real-time
nodes
that
have
produced
this
like
history
fragment
they
will
not
be
released
until
like
the
reason
why
classification
was
completed.
So
if
an
adversary's
pain
to
someone
to
you
know.
B
Like
to
not
return
the
data,
then
stakes
of
these
guys
will
never
be
unlocked,
and
this
essentially
would
be
similar
to
it,
just
paying
those
guys
their
stakes
yeah.
You
have
asked
about
the
I
think
about
what,
if,
let's
say,
yeah,
let's
think
about
this.
What
if
those
guys
have
uploaded
like
a
really
big
like
transaction
file,
you
probably
can
compute
the
proof,
like
you
probably
can
do
the
proof
of
this
sighs
all.
A
A
B
That's
that's!
That's
actually,
like
that's
actually
an
interesting
case.
I
mean
we
okay.
So
let's,
let's,
let's
also
talk
about
this.
The
Merkel
what's
what's
important
here,
is
that
the
Merkel
three
of
the
I
mean
here's
where
the
discrepancy
might
come
from.
So
there
is
a
hash
over
this
theme
and
swarm.
So
there
are
actually
two
hash.
Okay,
let's
get
to
this,
there
are
two
hashes
actually
and
the
first
cache
is
the
virtual
machine.
That's
the
miracle
drug
yeah,
that's
one
of
the
markers,
but
there
is
also
swarm.
That's.
B
A
road
data
like
what
of
auditor
can
do
like
this
guy
can
come
and
download.
Let's
say,
for
example,
it
has
produced
a
new
state
and
it
says
yes,
the
state
of
the
like
I
agree
with
the
state
of
the
virtual
machine
that
is
written
here,
but
it
then
uploads
not
match
and
file
an
automation
state
file
to
here,
and
in
this
case,
and
because
those
hashes
are
different,
it's
not
like
I
mean
I
well,
I,
don't
know
of
an
easy
way
how
to
prove
that
this
hair
doesn't
match
this,
but.
B
B
So
what
we
have
thought
about
in
that
the
next
like
I
mean
they
will
be,
they
will
always
be
the
next
validator
like
either
the
one
that
is
really
verifying
this
guy
or
the
validator.
That
is
like
verifying
the
next
history
fragment
that
will
download
this
file
and
once
it
downloads
the
file
it
there
is
a
way
how
to
prove
that
this
file,
like
that
the
file
available
by
this
form
hash,
does
not
really
correspond
to
this
virtual
machine
hash.
You.