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From YouTube: Worldcoin
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https://archive.devcon.org/archive/watch/6/worldcoin/index
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Speaker(s): Remco Bloemen
Skill level: Beginner
Track: ZKPs: Privacy, Identity, Infrastructure, & More
Keywords: zk
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Devcon is the Ethereum conference for developers, researchers, thinkers, and makers.
Devcon 6 was held in Bogotá, Colombia on Oct 11 - 14, 2022.
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A
B
Handing
out
free
stuff,
which
Ubi
basically
is,
is
make
sure
that
people
cannot
fraudulently
climate,
basically
civil
protection,
so
we
have
to
solve
the
Civil
protection
problem.
There's
a
couple
of
approaches
you
can
do.
Kyc
is
one
of
them,
but
not
very
privacy.
Preserving
and
we
are
all
ckp
people,
so
we
like
privacy
turns
out
that
the
only
feasible
strategy
up
to
let's
say
a
billion
people,
okay,
is-
is
to
use
Iris
based
Biometrics,
and
you
need
really
good
Hardware
to
do
that
better
than
what
you
can
currently
find
on
the
market.
B
B
It
generates
a
public
private
key
pair
in
a
system
called
semaphore
that
I'll
go
to
soon.
You
show
the
public
key
as
a
QR
code
to
the
device.
The
device
interacts
with
you
make
sure
you're
a
live
human
being
takes
your
iris
and
Bets
the
iOS
through
a
neural
network,
all
on
this
Hardware
in
a
128,
dimensional
vector
and
then
signs
the
public
key.
This
short
Vector
as
a
message
goes
to
our
server.
B
We
make
sure
that
it's
sufficiently
distant
from
everyone
who
signed
up
before
add
the
factor
to
the
database
and
then
just
send
the
public
key
to
the
semaphore
smart
contract,
where
it
gets
added
to
the
on-chain
Merkle
tree.
Now,
that's
the
sign
up
part
after
this.
It's
just
you,
your
wallet
and
the
blockchain.
B
You
don't
actually
reveal
which
public
key
that
is
you're
completely
Anonymous.
In
that
sense,
you
generate
a
unique
nullifier,
which
is
kind
of
like
episode,
a
random
number
for
the
specific
context
that
you're
using
to
make
sure
that
you
haven't
done
the
particular
thing
before,
and
then
you
can
attach
a
message
to
the
thing,
so
we
can
sign
some
message
with
this
concept.
So
where
can
you
use
this?
For
example?
Now
we
use
this
to
airdrop
tokens
to
our
users.
B
The
way
the
anonymity
actually
pans
out
is
so
strong
that,
even
if
you
vote
on
multiple
proposals,
you
wouldn't
even
be
able
to
trace
that
behavior
back
to
the
same
human
being,
so
privacy
is
extremely
well
preserved
in
this
system.
So
this
is
where
we
are
now,
but
there's
a
couple
things
we
would
like
to
do
better.
B
One
thing
we
need
to
do
is
right:
now:
the
public
key
gets
added
to
the
market
Tree
on
chain
which
costs
about
a
million
gas
which
is
completely
not
feasible
on
ethereum
mainnet,
where
we
want
to
launch
this
thing.
So
the
first
thing
we
did
is
build
growth,
16
proofs,
that
aggregate
multiple
insertions
and
create
a
batch
insertion
operation
and
basically
turn
the
insert
part
of
the
whole
stack
into
a
Seagate
roll-up
thing.
So
there's
like
a
back-end
server,
a
sequencer
that
creates
these
batches
and
sends
them
now.
B
There
are
things
already
get
more
complicated,
because
now
we
need
to
have
a
recursive
proof
system.
The
users
produce
these
proofs
on
their
wallet
and
then
we
want
to
batch
them
together
in
lot
16.
This
is
currently
very
hard,
so
one
of
the
things
we're
working
on
right
now
is
migrating
the
semaphore
proof
system
over
to
blonky2
and
then
have
recursive
plonky2
proofs
and
then
have
a
final
block.
16
verifier
of
the
plunky
2
proof
that
turns
it
into
a
glott
16
proof
that
can
be
very
easily
verified
on
chain.
B
B
We
want
this
to
be
very
inclusive,
so
assume
the
average
user
has
a
10
balance
and
wants
to
use
that
on
an
L2
right
now
on
ethereum,
that
is
like
five
cents
per
transaction,
which
is
kind
of
okay
is
but
it's
because
of
the
bear
Market
a
year
ago
it
was
two
dollars
per
transaction.
So
that's
not
good
enough.
So
how
can
we
fix
this?
B
Another
area
where
cryptography
comes
into
the
equation
is
right.
Now
the
neural
network
basically
runs
on
trusted
Hardware,
but,
like
you've
heard
in
the
past
two
talks,
we
can
actually
do
better
than
that.
Zkml
is
feasible.
A
year
ago,
I
was
experimenting
with
running
a
machine
learning
small
little
Network
in
a
plonky
two
proof
and
I
got
I
managed
to
do
10
million
parameters
on
my
laptop
in
less
than
a
minute,
so
technology
seemed
like,
and
that
was
without
any
significant
optimization.
B
So,
presumably
we
can
get
much
further
than
this,
and
this
is
good
enough
to
do
the
biometric
stuff
on
your
wallet
now.
What
is
the
advantage
there
and
how
do
we
get
there
in
the
first
place
like
right
now?
If
we
update
the
neural
network,
which
will
happen
a
couple
of
times,
we
would
need
to
ask
all
our
users
to
go
back
to
the
hardware
so
that
they
can
trustlessly
create
the
updated
factors
If.
Instead,
we
turn
the
orb
into
an
authenticating
camera.
Like
Jason
mentioned,
the
orb
will
just
sign
sign
your
raw
data.
B
Send
it
to
your
wallet.
You
can
keep
it
on
your
wallet,
self-custody
you're
in
control,
and
then,
whenever
we
have
a
new
version
of
the
neural
network,
we
can
just
push
the
parameters
to
your
phone
and
you
can
just
recompute
the
thing
locally
and
then
send
us
a
zero
knowledge.
Proof
that
hey
I
have
this
I.
Have
this
raw
diametric
data,
it's
authentic,
it's
signed
by
an
orb,
and
here
is
the
updated
embedding
and
we
can
update
it
in
the
system.
B
Another
cool
area
is
looking
at
NPCs
to
get
rid
of
this
Central
database
and
make
it
a
little
bit
more
decentralized.
We're
not
actively
doing
that
actually
at
the
moment,
but
we
are
actively
looking
at
is
using
mixnets
or
private
information
retrieval
to
make
sure
that
when
you
query
one
of
our
servers,
for
example,
to
help
you
generate
the
miracle
proof.
Instead
of
downloading
all
the
raw
data
from
the
chain,
make
sure
that
we
don't
learn
your
IP
address
in
the
process.
B
Yes,
one
more
application
of
the
zkml
stuff
longer
term,
so
right
now
what
I've
described
here
is
a
way
to
do
a
scalable
privacy,
preserving
proof
of
personhood
that
we
can
deploy
on
ethereum,
mainnet
scales
to
a
billion
people
and
then
can
be
used
on
all
the
chains
that
we
can
copy
state
to,
which
is
basically
any
smart
contract
enabled
blockchain
out
there,
but
proof
of
personnel
is
only
the
beginning.
You
would
kind
of
soon
as
want
to
do
a
little
bit
more
like
that.
B
You
would,
for
example,
want
to
make
sure
that
someone
is
in
a
country
that
your
the
app
is
legally
allowed
to
support.
I,
don't
know
there
will
be
applications
that
require
such
things.
How
could
we
integrate
that?
So?
One
of
the
things
we
were
thinking
of
is
we
could
have
the
orb
also
take
an
authenticated
image
of
your
face,
just
like
with
the
iOS
image.
Send
that
authenticated
image
to
your
phone.
You
can
scan
your
passports.
B
B
The
one
that
we
know
is
you
because
of
the
orb
and
the
one
that
is
on
the
passport
verified
that
those
two
are
the
same
verified
that
the
passport
is
signed
by
a
key
from
some
government
or
like
is
in
the
list
of
non-government
root
certificates.
Basically,
and
then
you
can,
you
have
a
chain
of
trust
establish
established,
and
now
you
can
fulfill
arbitrary
queries.
Like
is
the
name
in
the
ofag
list.
Is
the
nationality
in
the
approval
set?
You
name
it
yeah
and
I.
B
Yeah
there's
a
very
common
misconception
about
Biometrics
people,
think
of
them
as
sort
of
a
private
key
like
if
I,
somehow
get
access
to
your
fingerprints.
I
can
steal.
Your
accounts
doesn't
work
like
that.
Your
fingerprints
are
not
secret.
You
leave
them
on
every
single
glass
on
every
restaurant.
You've
ever
been
to
the
thing
that
uniquely
identifies
you
is
that
you
have
that
fingerprint
on
a
real
life
finger.
B
So
it's
very
important
that
you
check
what
is
known
as
the
liveness
check
that
you
make
sure
that
you,
the
data
you're
reading,
actually
comes
from
a
real
live
human
being
and
not
from
a
printout
or
whatever
fingerprints
are
actually
not
that
good
they're
only
unique
up
to
a
million
people.
We
really
need
irises.
For
that.
Irises
have
a
couple
more
advantages.
You
don't
leave
them
at
restaurants.
It's
actually
really
hard
to
get
someone's
Irish
accurate
accurately.
So
it's
it's
quite
consensual.
D
D
B
B
So
we
so
there's
two
parts
where
we
do
this
authenticated
data
game.
The
first
is
just
to
make
the
user
experience
of
updating
the
model
better
like
instead
of
having
to
go
to
The
Trusted
Hardware
again,
we
can
now
trust
you
to
do
it
yourself
correctly
because
of
the
zero
knowledge
machine
learning.