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From YouTube: The interconnected community - GitHub Satellite 2019
Description
About GitHub Satellite 2019
A community connected by code
Explore our interconnected community—and how collaboration turns ideas into innovations.
Join us in November at San Francisco's Palace of Fine Arts for GitHub Universe - https://githubuniverse.com/
A
A
This
is
a
really
exciting
time
for
us
to
be
at
github.
More
people
are
joining
github
every
day
than
ever
before,
and
so
the
audience
here
today
represents
the
more
than
36
million
developers
who
called
github
home.
Now
today
we
have
a
lot
of
great
blockchain
and
I'm
just
kidding,
there's
no
blockchain
announcements.
A
What's
really
at
the
heart
of
github,
which
is
the
open
source
community
every
day
developers
around
the
world
make
millions
of
contributions
to
open-source
projects
on
github,
and
we
thought
it
would
be
interesting
and
fun
to
take
our
data
set
of
that
contribution
stream
and
actually
visualize
it
on
a
globe
and
that's
what
this
is.
Every
little
ray
of
light
that
you
see
coming
out
of
the
earth
and
going
into
space
represents
one
contribution
to
an
open-source
project
from
someone
somewhere
on
earth
and
I,
just
I
think
it's
so
cool.
This
is
real
data.
A
It's
over
a
hundred
million
contributions
over
30
days
being
visualized
here
and
one
of
the
things
that
immediately
stands
out
for
you
when
you
look
at
this
is
how
global
our
community
is
right.
More
than
80%
of
the
contributions
that
occur
to
open-source
come
from
outside
the
US.
So
in
a
way,
if
your
company,
your
team,
is
using
open-source
code,
you've
already
embraced,
promote
work
now
the
chances
are.
A
You
have
already
started
to
use
open
source
code
because
nearly
every
software
project
on
earth
today
has
open
source
dependencies,
so,
whether
you're
working
at
a
large
company
or
a
start-up,
whether
you're,
a
scientist
or
student,
you
rely
every
day
on
open
source
code
and
you
rely
on
the
people
who
create
it
right.
Every
line
of
code
that
you
write,
builds
on
the
work
of
thousands
of
others,
and
you
can
think
about
it.
A
This
way,
when
you
import
an
open
source
library
into
your
code,
you're,
not
just
adding
code
to
your
project,
you
are
effectively
adding
a
team
of
developers
to
your
extended
team,
you're,
actually,
almost
giving
them
commit
access
to
your
code
that
you
then
put
in
production.
Then
you
also
get
to
benefit
from
the
work
they're
doing
every
day
to
improve
their
packages.
A
So
this
is
the
reality
of
building
on
open-source,
and
if
anyone
wants
to
make
an
editor
extension
that
does
this
I
think
that
would
be
really
cool
but
but
still
in
our
heads,
we
have
this
stereotype
of
the
solitary
developer
right.
When
we
think
about
the
act
of
writing
code,
we
often
think
about
a
developer
alone
in
a
dark
room,
writes
just
them
in
the
computer
writing
code
and
you
sort
of
slip
pizza
under
the
door,
and
it
gets
converted
into
code
and
uploaded
to
the
cloud.
A
This
is
the
first
ever
picture
of
a
black
hole.
It
was
published
just
last
month
in
more
than
four
and
a
half
billion
people
around
the
world
have
seen
this
image,
it's
very
famous,
and
it
is
a
huge
landmark
achievement
right.
Scientists
have
theorized
about
black
holes
for
decades,
but
this
is
the
first
time
we've
ever
actually
seen
one,
and
this
one
is
at
the
center
of
a
galaxy
called
m87,
which
is
really
far
away.
A
It's
55
million
light-years
away
from
us
here
in
Berlin
today,
in
the
scientists
who
created
this
picture,
used
a
global
network
of
telescopes
to
generate
a
huge
amount
of
data
which
they
then
composed
into
this
image.
They
spent
years
processing
that
data
to
get
this
image,
and
this
is
the
moment
of
truth
right.
This
is
dr.
Cady
Bauman,
one
of
the
lead
developers
and
scientists
on
the
project
and
one
of
my
personal
heroes,
and
this
has
become
an
iconic
photo
of
this
landmark
human
achievement.
A
I
personally
I
love
this
photo
because,
as
developers,
we
can
all
identify
with
this
feeling
right.
It's
like
it's
that
moment
when
your
code
finally
just
works.
You
know
when
all
your
tests
pass
when
all
your
hard
work
kind
of
comes
together,
it's
a
you
look
at
it
and
you
feel
that
same
feeling,
yourself
and-
and
it
also
makes
you
wonder
to
to
look
at
this
picture
right
like
what
did
it
take
to
get
to
this
point?
What
was
involved?
A
What
was
the
math
and
the
science
and
the
algorithms
that
were
involved
in
getting
here
and
then
like?
What's
going
on
on
that
chalkboard
in
the
background
there's
a
triangle
there,
I
have
so
many
questions
when
I
look
at
this,
and
so
here
to
answer
those
questions.
Please
welcome
via
satellite
from
Boston
Massachusetts,
dr.
Katie,
Baumann
Katie.
A
A
B
Of
course,
so,
taking
the
first
image
of
a
black
hole
was
a
huge
endeavor
and
took
many
people
years
of
hard
work
in
order
to
build
the
computational
telescope.
That
made
it
possible
to
see
the
unseeable,
because
the
black
hole
we
looked
at
is
so
far
away
from
us.
It's
55
million
light
years
away.
It
appears
incredibly
small
in
the
sky,
so
it's
about
the
same
size
to
us
as
a
grain
of
sand
would
appear
in
Los
Angeles
when
standing
in
New
York
and
because
it
is
so
small.
A
That's
awesome
thanks
for
it's
so
wonderful
to
hear
that
from
you
directly
now,
I
have
to
say
this
picture
of
you
has
become
so
famous
and
I.
Think
part
of
the
reason
is
the
obvious
sense
of
delight
and
that
kind
of
feeling
of
Eureka.
You
know
that
you
have
in
that
moment
and
that
every
developer
knows
a
little
bit.
What
do
you
remember
about
that
moment?.
B
Yeah
definitely
so.
This
was
really
an
amazing
day.
It
was
a
hot
day
in
June.
The
data
had
just
finally
been
released
to
us
for
imaging
and
our
collaboration
decided
actually
to
split
ourselves
into
four
teams
by
splitting
ourselves
into
teams
and
having
each
team
independently
make
an
image.
We
avoided
a
shared
human
bias
in
our
results.
So
anyway,
when
the
data
was
released
to
us,
some
of
the
members
of
the
team
I
was
on
team,
one
ran
into
a
small
room
and
we
got
ready
to
make
an
image.
B
So
we
all
had
imaging
scripts
that
we
had
each
developed
on
our
computers
and
we
decided
to
press
go
on
the
stay
at
the
same
time
on
all
of
them,
and
so
it
was
really
amazing.
Seeing
the
picture
just
start
to
appear
on
our
screens,
and
this
picture
was
taken
as
that
was
happening
and
I
was
just
flipping
between
awed
disbelief,
excitement
and
also
just
praying.
B
A
B
B
Andrew
my
collaborator,
so
unlike
the
m87
black
hole
image,
which
was
truly
a
collaborative
effort,
Andrew
can
claim
sole
credit
for
snapping
this
picture
of
me
as
he
sat
next
at
next
to
me,
making
a
picture
of
his
own
and
similarly,
similarly,
on
the
other
side
of
the
table,
where
a
number
of
other
team
members
and
many
others
in
rooms
around
the
world,
we're
doing
the
exact
same
thing.
A
lot.
A
A
It
is
so
awesome
to
have
the
core
team
that
worked
on
the
software
behind
this
black
hole
image
here
today.
I
can't
tell
how
much
we're
all
nerding
out
over
having
you
on
stage.
Why
don't
we
go
down
the
line
and
have
you
each
introduce
yourselves
and
just
say
a
couple
words
about
what
you
worked
on
so.
F
H
A
E
What
we
recorded
the
telescope's
is
actually
mostly
noise,
so
the
calibration
process,
basically,
is
the
process
of
combining
all
the
data
and
taking
out
the
very
weak
signal
in
the
recordings
and
strengthening
the
signal,
modeling
the
instrument
and
atmosphere
to
be
able
to
average
down
from
petabytes
of
data
to
all
the
very
nice
megabytes
of
strong
signal
data
that
then
get
passed
down
to
analysis.
That's.
A
C
A
F
A
That's
awesome
now
this
team
is
actually
gonna,
be
here
all
day
and
they're,
going
to
give
a
talk
at
5:20
today
on
this
stage,
going
into
a
lot
more
detail
about
the
project
and
all
the
details
of
everything
they
did.
Thank
you
all
very
much
for
being
here
and
Katie.
Thank
you
again
for
dialing
in
from
Boston.
B
F
A
It's
just
so
cool
to
have
that
team
here,
I've
been
like
handling
them
constantly.
So
now,
as
both
Katie
and
CK
mentioned,
the
team
actually
used
a
lot
of
Python
code
and
they
made
use
of
a
lot
of
open-source
Python
libraries
and
the
work
that
they
did
and
their
code
is
all
public.
So
we
can
actually
go
to
the
repo
and
look
at
it
and
we
can
also
look
at
their
dependency
graph.
And
here
it
is,
you
can
see.
A
They've
got
quite
a
few
different
dependencies
in
the
graph
and,
in
fact,
all
together
in
the
complete
set
of
transitive
dependencies
that
made
up
these
Python
scripts
there's
over
a
hundred
different
open-source
Python
packages,
and
some
of
these
are
probably
used
pretty
heavily.
Some
used
a
little
less
oh,
but
it's
a
really
interesting
list
to
kind
of
look
through
and
as
we
were
scanning
through
this
out
of
curiosity,
we
started
to
wonder
how
many
people
did
it
take
to
build
all
of
this
right.
A
A
A
We
are
so
lucky
to
have
with
us
today
maintain
errs
and
core
contributors
to
numpy
matplotlib,
sigh
hi,
Astro
pie,
panda's,
Python,
dynasty
scythe
on
Kiwi,
solver
and
many
other
packages.
These
people
represents
the
21,000
who
were
part
of
this
extended
team
that
made
this
work
possible.
We're
so
proud
to
have
you
all
here.
Thank
you
each
for
your
contributions
to
human
progress.
Let's
give
them
a
big
hand
again
thanks.
Everybody.
A
Thank
you
all
okay,
so
the
image
that
needed
a
planet-sized
telescope
also
really
did
truly
require
a
planet-sized
team
to
build
it
and,
by
the
way
at
least
one
of
the
people
who's
here
when
we
called
them
up
and
invited
them
to
come,
did
not
know
that
their
work
had
contributed
to
the
black
hole
image
and
was
very
moved
by
that
and
I
thought
that
was
really
cool.
It's
sort
of
the
magic
of
open
source.
A
Now,
as
Katie
said,
this
is
when
you
look
at
the
team,
that's
working
directly
on
a
codebase
in
a
way
you're
looking
at
the
tip
of
the
iceberg
right.
This
isn't
just
the
story
of
this
one
software
project.
This
is
the
story
of
all
software
projects
today
that
use
open
source,
so
the
tip
of
the
iceberg
goes.
Direct
contributors
are
the
ones
who
are
building
your
code,
but
below
the
waterline
are
the
developers
who
are
contributing
to
your
dependencies
and
we've
been
using
the
phrase
community
contributors
to
refer
to
these
people.
A
They're,
like
the
people
who
are
here
in
the
audience
today,
and
one
of
the
things
you
might
be
thinking
is
well.
Okay.
This
event
horizon
team:
they
wrote
their
code
in
Python,
they
used
a
lot
of
high-level
astronomy,
libraries,
maybe
they're
an
outlier
right.
Maybe
this
twenty
one
thousand
number
is
a
typically
high
and
we
were
curious
about
that
too.
A
So
we
decided
to
sample
a
thousand
of
the
most
popular
repos
on
github,
including
repos,
like
WordPress
and
rails
and
tensorflow
and
others,
and
we
ran
the
query
and
we
averaged
it
all
together,
and
we
discovered
that
on
average,
these
thousand
projects
had
more
than
74,000
contributors.
It's
amazing.
A
This
is
the
actual
size
of
our
teams
right
think
about
it
for
a
second.
This
is
more
software
engineers
than
work
at
Google
or
Apple
or
Microsoft.
It's
actually
more
people
than
there
are
in
the
entire
employee
base
of
90%
of
the
fortune
500,
and
for
a
couple
of
you
out
there.
This
is
more
people
than
the
population
of
Burning
Man.
So
it's
a
pretty
big
group
and
it's
a
testament
to
how
software
development
works.
A
Today
right
it
takes
a
community
to
write
code
so
to
make
this
interconnected
community
and
the
reality
of
this
more
concrete
for
each
of
us
in
our
everyday
work.
We're
introducing
two
new
features
to
github
today:
community
contributors
and
dependent
repositories.
So
today,
if
you
go
to
a
repo
like
this
is
numpy,
you
can
see
that
we
actually
call
out
how
many
contributors
that
repo
has
today
well
we're
adding
a
hovercard.
A
So
when
you
bring
your
mouse
up,
you
can
see
the
total
number
of
community
contributors
you
can
see
who
they
are
browse
them
and
get
to
know
your
extended
team.
It's
pretty
cool,
then
we're
adding
a
new
signal
for
you
to
understand
a
repost
popularity.
So,
right
now,
when
you
look
at
a
repo,
you
can
see
how
many
Forks
it
has
how
many
stars
it
has.
Many
people
are
watching
it
today
now
when
we're
adding
used
by.
A
So
you
can
see
how
many
other
projects
on
github
make
use
of
the
dependencies
of
the
packages
that
are
in
that
repo.
We
hope
this
is
a
useful
signal
of
a
repost
popularity
that
can
help
you
make
better
choices
and
for
you,
as
a
maintainer,
it's
pretty
cool.
You
can
see
how
many
people
are
using
your
stuff.
A
You
can
even
click
on
it
and
see
exactly
who
those
users
are
and
what's
repos
you've
joined
in
the
last
week
or
so
we
screen
shot
at
numpy
a
week
ago
and
it
went
up
by
about
a
thousand
users
in
the
week,
so
that
was
pretty
cool.
So
I'm
personally
really
excited
about
these
two
little
features
they're
rolling
out
today.
A
You
we're
here
to
serve
the
developers
and
the
companies
who
count
on
github
every
day
and
we've
been
spending
a
lot
of
time,
the
last
six
months
in
conversations
with
developers,
maintainer
x'
and
our
customers,
and
using
your
input
to
shape
our
roadmap,
and
so
today
the
new
features
that
we're
going
to
show.
You
are
based
on
the
things
that
you've
told
us
that
you
want.