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From YouTube: RPi Cluster interview with Héctor Sanjuán
Description
Watch the full interview with Héctor about ipfs-cluster... on Raspberry Pi. Learn more: https://blog.ipfs.io/2019-10-03-ipfs-camp-sci-fi-fair-videos/
Learn more about IPFS Camp: https://camp.ipfs.io/
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A
A
That's
pretty
cool,
and
you
know
like
with
this
kind
of
technology
that
we
know
that
is
so
deep
and
like
in
in
the
back
hand,
so
to
speak,
it's
difficult
to
get
the
observability
and
it's
it's
difficult
to
understand.
What's
going
on
so
like
little
experiments
like
this
that
actually
show
you
that
you
can
touch
that
you
can
see
blinking
in
real
life
as
we're
going
to
show
now
are
super
important
to
exactly.
B
You
normally
don't
see
in
the
end
you're
just
maintaining
a
shared
been
set,
but
behind
there
are
all
the
ducts
of
the
IPSS
stack
all
the
feet
to
be
for
using
peers
for
using
secure
channels
or
using
multi
streams
we're
using
CR
disease
to
sink
the
state,
we're
using
the
ipfs
chambers
we
use
in
the
repo
vide
astrology
we're
using
about
every
piece
of
the
stuff
to
make
a
distributed
application
on
top
of
a
distributed
application.
Normally,
you
don't
feel
that
everything
is
summarized
tonight
just
doing
awesome.
A
B
A
computer
which
is
adding
random
pills
beard
pins
to
this
Buster,
and
what
we
see
here
is
that
every
time
a
pink
comes
through
in
its
cluster
beer,
we
see
this
flashing
green
light
and
we
see
how
one
more
little
box
appears
on
this
column
once
that
column
is
filled
up,
it
gets
cleaned
up
and
a
new
box
appears
over
there.
So
the
first
column
means
one
thing.
The
second
column
means
five
pins.
The
third
column
means
25
pins,
the
fourth
column
means
125,
pins
and
so
on.
So.
B
B
A
B
A
B
B
A
A
B
Our
main
feature,
which
is
upcoming
and
our
next
release,
are
collaborative
clusters,
is
the
idea
that
you
can
collaboratively
participate
in
a
cluster
without
exposing
your
cluster
beer
or
your
ipfs
daemon
to
two
people
that
you
don't
trust.
Therefore,
we
will
have
some
insight
maintainer
yet
which
will
decide
what
goes
into
what
our
type,
for
example,
data
data.
You
will
have
a
curator
which
adds
climate
data
to
certain
Glasser.
We
will
have
followers
in
that
cluster
that
do
not
necessarily
trust
each
other,
but
trust
a
curator
of
the
data.