►
From YouTube: Regenerati News Hour 5/26/22: Let’s Explore the Network
Description
Join Regen Network for news updates and ongoings with our team, including discussion around carbon credits, grant projects, and meet & greets in the refi space. The Regenerati News Hour is an opportunity for community engagement for anyone interested in planetary regeneration.
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B
C
B
Austin,
hey
thanks
for
having
me
happy
to
be
here.
I'm
doing
some
av
configuration
yeah.
Do
it
we're
just
sitting
around.
C
Chit
chat
until
people
file
in
welcome
kiango,
looking
forward
to
talking
to
you
today.
I
think
it's
today.
C
Guiding
our
erstwhile
guide
today,
you
like
to
take
us
away,
looks
like
gregory's
unmuted
as
well.
B
Sure
I'll
start
and
then
maybe
greg.
If
you
want
to
jump
in
and
say
something
we
can
go
hi
everybody
nice
to
see.
You
hear
you
this
beautiful
thursday
yeah.
I'm
really
happy
to
be
here.
I'm
really
happy
for
the
invite
to
co-host
this
conversation
with
with
matthew
today.
So
just
making
sure
that
matthew
has
speaking
privileges
would
probably
be
wise
to
do.
Yeah
I
invited
him
great,
okay,
cool.
I
invited
him
on
yeah.
Well,
I
mean,
I
guess,
greg
owen.
B
Do
you
want
to
say
anything
before
we
kind
of
before?
I
queue
it
up.
C
Well,
first,
I
just
sort
of
matthew.
If
you
haven't
done
a
spaces,
you've
got
to
use
your
phone.
They
are
sneaky,
trying
to
get
us
all
to
have
the
twitter
app
on
our
phone.
So
if
you
were
like
me
and
joining
this
from
your
laptop
or
desktop,
because
you
don't
want
twitter
all
up
in
your
phone
business,
you
might
need
to
just
go
download
the
app
friendly
weekly
reminder
that
I
download
the
app
for
this
call
and
then
delete
it
shortly
thereafter.
C
C
B
It
yeah
it's
like
five
minutes
that
doesn't
exist.
All
of
a
sudden.
It's
like
whoop
that
just
that
was
a
wrinkle
in.
B
C
I'm
but
I'm
I'm
doing
good,
I'm
really
excited
for
this
conversation
with
matthew.
The
work
that
he's
doing
is
really
interesting
and
often
I'm
excited
to
jam
with
you,
austin,
and
I
have
been
playing
a
little
bit
thanks
to
gary
over
at
dream.
Dao
with
some.
B
C
C
Yeah
well-
and
so
I'm
so
excited
about
that-
and
I
was-
and
I
was
just
sharing
in
the
community
dev
call
yesterday,
which
is
a
bi-weekly
thing
where,
where
the
r
d
inc
team
sort
of
gathers
with
validators
and
other
community
members-
and
we
go
through
the
public
road
map
and
some
other
things,
I
was
sharing
in
that
space
and
wanted
to
share
on
to
the
community
here
on
twitter.
That
and-
and
I
think,
austin
and
I
are
going
to
be
collaborating
on
this.
But
I'm
starting
to
work
on
some
art
collections.
C
I'm
doing
it
in
a
couple
of
different
ways,
but
essentially
I'm
I'm
starting
to
generate
some
art
to
be
used
for
project
fundraising.
So
this
is
all
stuff
sort
of
starting
to
generate
collections,
that
land,
stewards
and
scientists
and
other
people
who
aren't
going
to
get
deep
into
geeking
out
on
whether.
A
C
Art
or
or
landscape
art
or
just
other
forms
of
digital
art
can
kind
of
maybe
pick
from
some
beautiful
crafted
images
and
use
them
to
generate
project
funding,
because
one
of
the
big
things
that's
really
important,
looks
like
matt
just
hopped
off,
so
I
bet
he'll
be
hopping
on
with
his
phone
now,
one
of
the
big
things
that
we're
recognizing
at
regen,
especially
in
the
midst
of
this
drama,
which
I
actually
want
to
talk
about
a
little
bit.
But
this
drama
related
to
vera
and
tokenizing.
B
C
Isn't
that
easy
right,
because
we
do
not
have
a
lot
of
the
infrastructure
that's
needed
in
order
to
do,
for
instance,
direct
payments
incumbent
upon
verification
of
ecological
health,
for
instance
right
currently,
this
system
is
very
bureaucratic.
There's
all
these.
C
You
know
the
land
stewards
never
get
paid
directly
and
if
money
does
trickle
down
it's
just
a
fraction
of
what
is
being
valued
on
the
market,
and
so
this
is
sort
of
like
gregory's
rant
and
ramble,
leading
up
to
matthew
getting
up
on
stage
and
the
conversation
that
austin
and
matthew
are
going
to
have,
which
I'm
super
excited
about
is
two
big
brained
humans.
Just
you.
C
So
I'm
going
to
pass
it
back
over
to
you
austin
after
that
ramble
and
yeah
just
stoked
about
this
conversation.
B
Yeah
me
too,
while
we're
here
just
to
say
thanks
for
that
mid-journey
invite
gregory.
If
you're
talking
about
like
having
twitter
on
your
phone
and
losing
five
minutes
just
to
like
doom
scrolling.
I
think
I
lost
about
half
of
my
day
productive
day
yesterday,
just
generating
images
with
mid-journey,
so
super
excited
to
see
what
comes
out
of
it.
It
produces
some
pretty
cool
stuff.
If
you
give
it
sovereign,
bioregional
regenerative
economies,
it
gets
it.
B
I
mean
I
don't
know
what
one
might
think
it
it
is
and
what
it
getting
it
means,
but
it
seems
to
get
it,
which
is
pretty
fun
totally
totally
yeah.
So
that's
like
a
that's
a
wormhole,
that's
pretty
intense
and
I
guess
I'll
skew
up
the
conversation
today,
because
today
we're
going
to
be
talking
with
matthew
who
I've
actually
never
met,
matthew,
hi,
I'm
austin.
B
I
work
at
the
region
foundation,
I'm
a
big
fan
of
active
inferencing
and
I'm
stoked
for
you
to
be
here,
maybe
I'll
I'll
kind
of
set
the
stage
just
with
a
few
comments
and
then
I'll.
Let
you
introduce
yourself
and
then
maybe
I'll
sort
of
queue
it
up
from
there.
You
know
we
can
talk
about
these
like
little
tools
that
are
helpful
towards
the
process
of
regenerative
economics
or
refi.
B
We
could
call
them
primitives
and
the
topic
for
today,
active
inferencing
seems
like
a
pretty
big
tool
and
it
does
not
seem
very
primitive.
It
seems
really
sophisticated
and
really
exciting
and
interesting.
So
that's
my
kind
of
like
splash,
so
matt,
maybe
I'll
just
ask
you
to
turn
on
your
mic
and
introduce
yourself
and
and
then
I'll,
follow
up
with
some
questions.
A
Hey
yeah,
can
you
hear
me
my.
B
A
Birds,
it's
lovely
yeah,
I'm
here
in
downtown
hood
river
and
yeah,
I'm
kind
of
by
a
road.
So
hopefully
you
guys
can
hear
me
all
right,
there's
some
birds
and
some
car
noises.
So
there
might
be
a
little
background,
but
yeah
my
name
is
matthew
burkowski.
I
have
a
bit
of
a
winding
path.
My
original
background
was
in
evolutionary
psychology
and
agent-based
modeling.
A
That's
where
I
learned
software
development
and
then
went
through
a
career
in
software
development
for
quite
some
time,
but
I've
always
maintained
a
passion
for
understanding,
modeling
and
thinking
through
complex
systems
and
trying
to
encapsulate
those
the
extent
they
can
be
encapsulated
in
software
models
and
mathematical
models,
and
recently
that
has
led
me
to
this
project
with
regen
network
and
active
inferencing,
and
so
I'm
sure
we
can
unpack
this
at
any
level
of
depth
that
people
are
interested
in
doing,
but
just
at
a
very
high
level.
A
Active
inferencing
is
a
way
of
understanding
how
agents
or
how
certain
systems
use
information
to
generate
probabilistic
models
of
the
world
and
of
the
causal
structures
of
the
world
and
how
they
update
those
models
across
time.
A
There's
a
metric
that
that
generates
called
free
energy
and
that's
modeled
on
the
idea
of
free
energy
and
physics,
which
is
a
pretty
deep
concept
as
well,
and
we
can
unpack
that
if
we
want
to
or
not
but
that's
sort
of
my
background
and
how
I
was
led
to
this
particular
project
and
I
think,
there's
a
lot
of
interesting
applications
in
terms
of
how
to
use
that
modeling
paradigm
for
governing
or
developing
or
iterating
on
models
in
various
parts
of
the
the
regen
ecology,
in
terms
of
either
modeling
ecological
systems
directly
or
trying
to
understand
the
interface
between
certain
financial
systems
in
sort
of
crypto
or
d5
space,
and
how
that
intersects
with
desired
behaviors
or
incentives
in
ecological
stewardship.
A
B
Yeah,
that's
great,
I
mean,
I
think
you
just
kind
of
gave
a
nice
arc
for
maybe
what
I
was
thinking
the
conversation
could
could
could
process
through.
I
mean
maybe
talking
a
bit
about
these
generative
ecological
models
and
understanding
like
ecological
state
through
active
inferencing
and
then
we'll
get
into
some
space.
That's
definitely
like
outside
of
my
wheelhouse,
but
I'm
super
curious
about
with
some
of
the
work
of
active,
inferencing
related
to
defy
and
automated
market
meter.
B
Our
automated
market
maker
is
related
to
to
some
of
the
tools
which
seems
like
a
really
exciting
and
sort
of
expansive
application
of
it.
Maybe
to
start
us
off,
I
think,
to
give
all,
because
we
have
different
sort
of
familiarities
with
the
with
you
know
the
people
who
show
up
to
this
space.
I
want
to
kind
of
set
the
stage
just
to
talk
about
ecological
state
and
why?
B
Why
that
matters
within
a
project
like
this,
and
it's
as
much
to
explain
why
we
we
want
to
understand,
what's
happening
with
with
the
with
the
biosphere,
but
also
to
sort
of
introduce
the
kind
of
language
that
that
surrounds
some
of
the
work
around
active
inferencing.
So
you
know
the
reason
that
we
would
that
were
talking
about
this
idea
of
you
know
what
is
going
on.
How
do
we
make?
How
do
we
make?
B
How
do
we
infer
about
the
health
or
the
well-being
of
a
particular
bioregion
or
of
a
particular
plot
of
land
is
because
this
larger
idea
of
the
region
registry
runs
on
the
notion
that
that
we're
we're
making
attestations
about
ecological
state
that
a
kind
of
proof
of
regeneration
is
necessary
in
some
form,
but
how
that's
done
has
to
be
circumstantial
and
it's
it's
it's
contextual
and
multifaceted.
B
So
there
isn't
a
one-size-fits-all
way
to
make
a
claim
about,
like
the
current
health
or
the
well-being
of
an
ecosystem,
but
that
active
inferencing
is
a
way
to
support
some
really
sophisticated
understandings
about
ecological
state
in
ways
that
are
hard
to
measure
with
sort
of
state
factors
that
are
difficult
to
do.
You
know
sort
of
conventional
analysis
on
so
we're
talking
about
this
because
we're
in
order
to
build
a
regenerative
economic
model.
We
have
to
base
that
in
what's
actually
happening
on
the
ground
and
we
could
use
remote
sensing
to
do
that.
B
We
can
use
a
ground
truth
like
eyesight.
We
could
use
wireless
sensor
networks
to
do
that.
Some
combination
of
all
of
them,
and
so
active
inferencing
is,
is
a
means
with
which
we
can
attest
to
what's
happening
in
a
particular
plot
or
subplot
on
the
earth's
surface.
Matt
does
that
seem
like
a
fair
kind
of
like
really
broad
claim
of
what
it
does.
A
Yeah
yeah,
I
mean
that's,
definitely,
that's,
definitely
a
fair
assessment
of
how
we're
trying
to
use
it
or
apply
it.
At
this
moment
I
mean
one
really
interesting
aspect
about
active
inferencing
from
a
sort
of
philosophy
of
knowledge
or
epistemology
perspective.
Is
that
you
know
so
many
other
modeling
systems
throughout
you
know
the
history
of
cybernetics
or
history
of
trying
to
understand
and
formally
model
natural
systems
have
made
a
lot
of
assumptions
about
what
kind
of
state
you
know
as
you're
talking
about
these
ecological
states.
A
You
know
what
kind
of
state
is
accessible
or
directly
observable,
and
it's
actually
become
quite
obvious
through
a
lot
of
artificial
intelligence,
research
and
robotics
work
that
it's
actually
very
hard
to
understand
or
directly
perceive
that
calls
a
structure
in
front
of
you
and
you
have
to
basically
access
that
always
indirectly,
and
so
one
of
the
interesting
things
about
active
inference
is
you
know
it
takes
that
as
a
fundamental
axiom,
because
it
emerged
out
of
the
neuroscience
research
paradigm
as
a
general
modeling
toolkit.
A
It
takes
as
axiomatic
the
fact
that
the
world
and
the
states
of
the
world
must
be
accessed
through
sensory
modalities
and
those
sensory
modalities
are
never
error-free
right,
never
noise-free,
I
think
of
consciousness
itself.
Like
you
know
our
eyes
or
our
ears
could
in
theory
betray
us,
but
overall
they
do
give
us.
A
You
know
a
picture
of
the
world
that
can
be
useful
as
we
incorporate
it
into
our
understanding
of
how
certain
behaviors,
how
certain
behaviors,
or
how
certain
causal
structures
unfold
around
us
and
also
how
we
can
act
upon
that
world
to
both
confirm
our
understanding
of
how
the
world
works
and
to
pursue
goals
with
respect
to
those
states
and
the
causal
structure,
and
so
all
of
that
is
quite
relevant
to
something
like
region
network,
in
the
sense
that
you
know
many
actors
are
going
to
be
making
claims
about
not
only
the
particular
levels
of
the
states
that
they're
targeting
for
change,
but
also
their
theory
of
change
around
what
kind
of
actions
they
could
do
to
change
those
states
and
push
those
states
in
the
ecology
towards
a
more
desirable
target.
A
And
you
know
doing
so.
You
know
it
can
also
give
you
information
about
how
well
you
understand
that
causal
structure,
how
well
you
understand
the
ecology,
how
good
your
model
is
and
active
inference
is
a
great
paradigm
to
allow
for
all
of
that,
and
so
you
know
we're
taking
steps
in
that
direction.
Right
now,
it's
at
the
beginning
of
the
project,
but
I
think
the
the
match
between
the
goals
of
this
project
and
the
innate
or
the
the
sort
of
axiomatic
structures
of
the
paradigm
of
modeling
itself
are
really
in
line.
B
Yeah
I
mean
it's
interesting
that
it
emerged
from
a
neuroscientific
context
and
now
we're
talking
about
it
as
a
generalizable
kind
of
model
describing
ecological
conditions,
and
so
that's
it
seems
really
exciting.
I'm
curious,
if
you
could
kind
of
give
like
a
lay
person's
explanation
about
how
observations
can
be
used
to
like
is
part
of
this
generative
model
to
get
at
things
which
are
not
observable.
B
Can
you
can
you
walk
us
through
in
sort
of
like
plain
terms,
what
the
process
is
to
be
able
to
make
understandings
of
state
around
factors
that
are
not
directly
measurable
like
how
might
that
work.
A
Yeah,
so
I
mean
directly
describing
the
transformations
or
the
inferences
themselves.
Are
you
know
the
best
language
for
that
is
linear
algebra?
But
you
know
in
terms
of
just
general
language.
You
know
the
easiest
way
to
think
about.
It
is
fundamentally
there's
a
bayesian
probability
structure
involved
here,
and
the
thing
about
bayes's
rule
is
that
you
know
I'm
not
sure
how
familiar
that
is,
or
if
that's
inbounds
or
not,
for
layman's
definition.
A
But
you
know
the
whole
idea
is
based
on
observations
you
see
in
the
world
and
a
certain
understanding
of
how
likely
something
you
think
is
in
the
world
to
be
the
case.
So
like,
let's
say
that
you
know
you
get
sensory
information.
A
That
says
you
see
an
apple
and
then
there's
some
general
understanding
of
how
likely
you
are
to
see
apples
in
your
day-to-day
existence
and
the
fact
that
you
think
that
you're,
seeing
that
apple
then
impacts
the
degree
to
which
you
believe
you
will
see
apples
in
the
world
and
moving
forward,
and
so
that's
this
general
bayesian
paradigm,
and
you
know
you
can
get
into
the
details
of
that.
A
If
you
want,
but
the
hard
thing
about
that
applying
that
base
theory
because
base
theory
is
pretty
simple
generally,
but
the
hard
thing
about
applying
that
to
more
complex
systems
or
applying
that
through
the
world.
More
generally,
is
that
there's
something
called
you
know
the
posterior
probability
and
then
there's
something:
there's
a
process
called
marginalization
that
you
have
to
do
to
get
that,
and
the
issue
with
marginalization
is
that
you're
kind
of?
A
Supposing
that
you,
in
order
to
do
that
about
an
arbitrary
state
of
the
world,
you
would
have
to
suppose
that
you
were
able
to
get
data
about
all
hypothetical
hypotheses
for
the
causal
structure
of
that
probability
and
that's
really
hard,
and
so
all
you
know,
a
huge
probabilistic
feel
a
whole
huge
field
of
probability.
Statistics
has
been
you're
really
interested
in
researching.
How
to
you
know,
mathematically
get
at
that
problem
and
active
inference
has
a
really
nice
and
elegant
way
in
which
it
piggybacks
on
certain
ideas
and
thermodynamics.
A
So
it
piggybacks
on
this
idea
of
free
energy,
which
is
you
know
in
thermodynamics.
It's
a
measure
of
the
energy
available
in
a
system
to
actually
perform
work.
So
the
amount
of
accessible
or
usable
energy
in
that
system
that
can
be
directed
toward
some
other
process
and
this
paradigm
in
active
inference,
takes
that
and
applies
it
to
the
concept
of
behavior
and
information
in
a
way.
A
So
it's
almost
kind
of
like
saying,
instead
of
just
performing
those
calculations
directly
on
the
bayesian
mathematics
and
saying
what
are
these
probabilities
of
all
the
possible
hypotheses
in
the
world?
It
places
a
constraint
on
that
with
a
very
specific
mathematical
framework
and
allows
you
to
sort
of
get
at
that
idea
of.
You
know
how
likely
your
you
know.
What
is
the
likely
causal
structure,
given
the
observations
that
you
see
in
the
world,
and
you
know
it
also
allows
you
to
use
actions
on
the
world.
A
So
you
know
based
on
how
you
actually
want
to.
Let's
say
I
grab
the
apple
and
rotated
the
apple
around
just
to
check
and
make
sure
that
it
had
a
stem
and
it
looked
like
an
apple,
and
maybe
I
bit
the
apple
and
tasted
the
apple.
All
those
actions
can
also
add,
to
my
certainty,
add
to
my
understanding
of
what
an
apple
is.
A
How
likely
it
is
to
be
in
the
world
how
it
relates
to
other
processes
in
the
world
and
so
yeah
I
mean,
I
hope
I
hope
that's
a
decent,
I'm
trying
not
to
go
too
technical,
but
the
thing
with
active
inference
is:
it
is
a
really
deep,
mathematical,
modeling
paradigm
and
so.
B
C
C
You
know
so
so
recently,
there's
kerfuffle
a
big
deal
around
carbon
credit
registries
and
the
biggest
carbon
credit
registry
vera.
Saying
people
can
no
longer
tokenize
the
carbon
that's
produced
on
this
registry
going
back
a
step.
What
does
vera
do?
Vera
is
a
institutional
sort
of.
Like
truth,
it's
an
institution
that
is
that
is
claiming
to
be
able
to
verify
that
a
carbon
credit
has
value,
and
so
there's
a
sort
of
there's
an
epistemology
around
that
the
epistemology
you
know
or
that
is
to
say
how
knowledge
is
generated
in
the
vera
paradigm.
C
You
know
not
really
working
very
well,
like
somebody
might
hand
you
an
orange
and
insist
that
it's
an
apple
and
if
you
don't
have
the
faculties
to
sort
of
weave
it
back
to
what
matt's
talking
about
this
analogy,
if
you
don't
have
your
own
faculties
to
be
able
to
look
at
that-
and
you
know
maybe
take
a
bite
to
test
it
and
play
with
it,
you
may
you
know
just
accept
that
an
orange
is
an
apple
okay.
So,
coming
back
to,
why
are
we
interested
in
this
conversation?
C
Why
is
it
important
as
a
community
to
be
educating
ourselves
about
these
terms
of
art,
about
this
approach
of
active,
inferencing
and
more
broadly
sort
of
epistemology?
How
are
we,
how
do
we
generate
knowledge
about
ecological
state
as
a
community
and
what
does
that
have
to
do
with
carbon
credits?
Well,
this
is
a
step
this
these.
These
are
explorations
research
and
development
that
is
trying
to
ground
an
open
source
system
for
people
to
be
able
to
make
claims
back.
C
Those
claims
up
with
simple
evidence
and
for
the
rest
of
the
community
to
be
able
to
make
an
assessment
about
the
level
of
uncertainty
that
should
be.
You
know
that
is
baked
into
the
claim,
so
that
you're
you're
not
saying
is
it
completely
false,
or
is
it
completely
true
you're
able
to
make
a
claim
that
says
you
know.
A
A
C
You
know
this
conversation,
I
believe,
is
really
foundational
to
what
a
world
looks
like
when,
when
we're
operating
with
a
don't
trust,
verify
approach
to
ecological
state
and
the
markets
that
sort
of
regenerative
finance
markets
that
can
be
built
on
things
like
quantification
of
ecological
health.
So,
hopefully,
that's
helpful,
like
contextualization.
B
We
are
actively
exploring
and,
working
with
you
know
the
stack
on
a
social,
technical,
ecological
level
of
building
new
kinds
of
eco
credits,
so
we're
not
just
taking
what
vera
has
created
but
building
new
kinds
of
eco
credits,
so
active
inferencing
becomes
like
really
relevant,
and
this
is
an
ignorant
question.
Is
there?
Is
there
any
existing
registry
which
has
has
has
integration
in
it
around
like
uncertainty,
quantifiable
uncertainty,
or
is
it
all
system
to
be
complete?
No.
C
There's
no
there's
no
concept
of
a
reporting
around
uncertainty
at
sort
of
like
a
methodological
level.
Scientists
sometimes
will
be
able
to
answer
uncertain,
like
sort
of
the
statistical
level
of
certainty
that
they
have,
but
at
a
registry
level
and
a
claims
level
that
is
not
currently
sort
of
an
operating
you're
not
going
to
buy
a
carbon
unit.
That
has
a
you
know,
a
level
of
certainty
attached
to
it.
C
A
Just
to
kind
of
pivot
on
that
or
to
to
extend
that
point,
you
know
a
really
a
fascinating
aspect
about
the
active
inferencing
paradigm
for
modeling
is
that
it
doesn't
actually
so
it
it's
very
specific
in
how
it
is
applied
to
a
given
model,
but
it
doesn't
dictate
how
you
generate
the
model
that
you
think
or
that
you're
trying
to
examine
or
experiment
with.
So
what
I
mean
by
that
is
like
many
people
could
just
like
you're,
saying,
vera
or
others
could
arbitrarily
say.
A
Oh,
we
have
a
model
of
how
these
states
work,
and
you
know
how
different
people's
you
know.
Actions
on
an
ecology
or
on
a
given
piece
of
land
will
impact
that
lands
states
or
these
states
that
we
concern
that
are
under
underwriting
this
economic
asset.
This
carbon
credit
and
maybe
10
different
companies
do
that
and
how
do
you
arbitrate
between
those
different
models
and
there's
no
extrinsic
connection
or
way
of
getting
underneath
those
if
people
are
just
disagreeing
about
certain
arbitrary
aspects
of
their
models?
A
And
it's
not
getting
to
a
deeper
level
of
you
know.
The
constraints
that
are
governing
all
of
these
systems
and
active
inference
is
fascinating
because
of
the
fact
that
it
is
so
generally
applicable
and
the
way
that
you
verify
these
principles
of
uncertainty
is
totally
standardized
across
any
kind
of
model.
A
As
you
know,
sensory
systems
are
giving
you
more
information
about
that
land,
as
people
are
submitting
different
proposals
in
terms
of
how
to
update
or
how
to
improve
that
ecology
state
based
on
whichever
one
of
those
models
they
subscribe
to.
You
would
actually
get
a
different
signature.
You'd
get
a
different
pattern
of
how
well
each
of
those
hypothetical
models,
those
generative
models,
those
causal
hypotheses
about
the
world,
how
well
they're,
using
the
information
that
they
have
and
the
actions
that
they
can
take
to
reduce
their
uncertainty
about
the
world
about
these
ecologies.
A
So
you
actually
get
a
you
know.
I
wouldn't
go
so
far
as
to
call
it
objective,
because
that
the
fact
is
that
the
axiom
of
this
model
is
that
nothing.
None
of
these
nothing
is
objective
in
this
sense,
you
don't
get
direct
access
to
this
state,
but
you
do
get
a
metric
that
can
be
applied
as
close
to
objectively
across
different
hypotheses
as
possible,
inter.
A
Intersubjective
integrity
or
interest
objective
coherence
right
yeah.
It
provides
that
ability,
like
you
said,
grounding,
is
very
good
way
of
thinking
of
it.
You
know
grounding
the
dynamics
of
these
supposed
processes
that
we're
saying.
Oh,
I
think
I
understand
how
the
world
works,
and
this
is
what
I
want
to
do
about
it.
Well,
how
do
you
measure
that?
How
do
you
even
get
at
beginning
to
talk
about
that
coherently
across
different
people's
hypotheses.
A
A
Trying
to
come
together
using
observations
in
a
coherent
way
to
understand.
You
know
the
extent
to
which
we
do
understand
the
world
and
the
extent
to
which
we
don't
understand
the
world
and
trying
to
be
able
to.
You
know
if
not
with
total
precision
puts
you
know,
get
gained
some
grasp
on
that,
so
that
we
can
move
toward.
You
know
functional
goals
and
values
that
we
have
in
the
world,
but
yeah
I
mean
it
is.
It
is
a
very
deep
articulation
of
the
scientific
method
as
such.
B
Right
as
as
applied
to
to
making
claims
about
ecological
states
so
that
we're
not
stuck
just
assuming
that
any
any
claim
is,
is,
is
objective
or
is
just
significant,
but
we
actually
have
a
spectrum
of
like
degrees
of
significance
or
the
uncertainty
of
the
claim
is
quantifiable,
and
that
seems
really
relevant
in
the
wake
of
you
know
very
vague
understanding
of
the
additionality
of
certain
carbon
tons
that
you
know
have
could
be
described
as
zombies,
etc,
but
that
you
know
there's
such
a
thing
as
quality
in
involved
here
that
not
all
are
created
equal.
B
So
it's
super
exciting.
I
mean
I,
I
I've
watched
and
and
like
read
some
papers
and
watched
several
lectures
on
this.
I'm
curious
if
you
can
bring
us
into
some
of
the
like
parts
of
the
the
biosphere
here
like.
Are
we
looking
at
like
crop
patterns
or
grazing
patterns
or
storm
patterns,
in
order
to
understand
something
about
a
plot
of
land?
Can
you
give
us
like,
rather
than
describing
them
as
parameters
and
factors?
B
Can
we
describe
this
in
the
language
of
like
abiotic
and
biotic
things
like
the
kind
of
entities
we
know
that
compose
ecosystems?
Is
it
if,
like
I'd
love
to
hear
an
example
walking
through
say
a
grazing
example,
or
something
like
that,
so
we
can
root
these
sort
of
parameters
and
terms
into
into
the
ecosystems.
A
Sure
so
I
mean
at
this
point
that
would
be
hypothetical
just
because
of
the
fact
that
we're
at
the
beginning
of
developing
the
mapping
between
this
model
and
more
general
ecological
systems,
so
we
haven't
gotten
into
applying
it
to
extremely
granular
cases
yet,
but
you
know
you
could
certainly
you
could
certainly
like
it.
You
could
have
one
one
way
you
could
apply.
Something
like
this
is,
you
would
have
an
underlying
understanding
of
you
know
various
measurements
that
you
would
take
of
the
soil.
A
A
You
could
start
understanding
what
you
think
about
the
association
between
those
different
chemical
signatures
and
perhaps
like
the
presence
of
micro,
microsoft,
fungi
of
different
species
or
something
like
that.
Whatever
causal
model
of
that
soil
structure,
you
wanted
to
hypothesize
right
as
the
underlying
states
you're
interested
in.
Maybe
you
want
to
increase
the
soil
complexity
or
the
density
of
a
particular
nutrient,
or
you
know
the
presence
of
some
factor.
A
Some
hormone
that
was
not
necessarily
being
produced
before
that
requires
some
set
of
precursors
that
just
weren't
in
the
soil
you
could
create
whatever
model
you
wanted
to
create
there
and
then
based
on
observations
above
surface
and
behaviors
above
surface
that
you
are
taking
or
observing.
So
you
could.
A
You
know
anything
from
the
visual
signature
of
of
that
land
so
like
an
image
that
you
take
daily
of
a
piece
of
that
area
or
any
sort
of
chemical
sensor,
soil
temperature
sensor
any
of
these
types
of
measurements
that
are
far
easier
to
obtain
than
actually
going
and
taking
soil
samples
and
having
scientists
explicitly
look
at
exactly
what's
in
that
soil.
In
terms
of
you
know,
first
of
all,
it's
expensive
enough
to
do
that
with
just
basic
chemical
signatures
or
levels
of
molecules
like
nitrogen
or
phosphorus.
A
If
you're
trying
to
do
it
at
high
resolution
across
a
large
amount
of
samples,
but
then
you
talk
about
something
like
say:
you're,
saying,
like
my
rise
with
complexity.
Well,
that's
you
know
very
difficult
to
measure
directly
and
we
don't
even
necessarily
have
a
good
proxy
or
understanding
of
how
you
would
quantify
that.
But
you
can
represent
it
as
a
probabilistic
factor
and
in
theory
you
know,
based
on
these
other
observations
that
you
do
have
access
to.
A
You
can
begin
to
infer
based
on
your
model
and
your
observations
and
the
actions
you're
taking.
You
can
begin
to
infer
the
relationships
between
these
factors,
these
causal
relationships,
as
opposed
to
saying
you
know,
we
understand
the
exact
dynamics
and
exactly
what's
happening,
you
can
begin
to
understand.
You
know
how
they
are
structured
or
probably
related
to
one
another.
I'm
trying
to
try
to
make
this
specific,
but
we
haven't
like
right
now:
we've
been
working
at
a
higher
level
and
we're
kind
of
drilling
into
this.
B
A
B
Where
there's
a
tremendous
diversity-
and
you
know,
I
think
that
it'll
be
really
exciting
to
see
in
the
future,
how
you
all
love,
bioforms.
What
your
approach
is
in
terms
of
making
this
available,
how
it's
released?
What
kind
of
how
high
is
the
wall
around
the
garden
or
no
wall
whatsoever?
So.
B
A
Interact
with
it
more
directly
later
on,
it
would
be
in
the
form
of
saying,
let's
say
that
you
have
a
proposal
and
you
have
some
idea
of
of
what
you're
going
to
do.
Maybe
you're
going
to
change
your
composting
practices
or
or
your
xyz
and
you'd
have
some
idea
of
how
that
would
increase
your
capacity
to
cut.
You
know,
capture
carbon
and
then
across
time.
You
know
some
basic
measurements
as
opposed
to
current.
You
know
more
in-depth
auditing
processes.
A
That
would
be
more
also
more
expensive
to
implement
like
having
someone
actually
come
out
to
the
land
and
test
the
soil
at
some
high
frequency.
You
know
in
theory
there
could
be.
You
know
you
would
have
your
hypothesis,
you
would
have
other
pieces
of
evidence
that
could
be
more
easily
taken.
You
know
via
phone
or
camera
systems,
or
things
like
that,
and
you
could
then
therefore
have
a
much
higher
degree
of
certainty
associated
with
you
know
whether
or
not
you
are.
A
You
have
a
good
understanding
of
how
you
are
impacting
your
land,
how
you're
improving
that
state
and
then
that
could
you
know,
increase
the
relative
price
of
that
carbon
credit
right,
because
there's
greater
confidence,
less
uncertainty,
greater
confidence.
You
know
by
this
standard
in
terms
of
the
fact
that
this
whole
network
of
this
region
network
is
now
bringing
many
people
in
who
are
playing
by
these
same
rules
of
reducing
uncertainty
in
terms
of
how
they
are
achieving
their
goals
of
improving.
A
You
know,
biomass
density
or
carbon
capture
capacity
across
this
wide
swath
of
behavioral
patterns,
and
many
of
those
behavioral
patterns
are
now
possible
to
unlock
at
smaller
scales,
where
it
wouldn't
have
made
economic
sense
before,
because
it
would
have
been
like
cost
prohibitive
or
time
prohibitive
for
the
for
the
person
managing
the
land
or.
B
And
that's
huge
that
yeah
one
of
the
largest
like
we're
talking
about
small,
holds
or
vulnerable
economies,
more
vulnerable
populations.
The
overhead
cost
to
see.
If,
if
regeneration
has
happened,
you
know
can
be
prohibitively
expensive
and
you
know
basically
be
a
non-starter.
So
the
sort
of
quantifiable
uncertainty,
coupled
with
the
fact
that
this
lowers
the
barrier
to
entry
to
economic
overhead-
and
you
know
who
has
access
to
being
being
able
to
make
attestations
of
state
is
super
super
exciting.
B
I
want
to
give
a
second
to
to
before
you
open
up
to
questions
later
on.
I
want
to
give
a
moment
for
you
to
for
you
to
describe
a
little
bit
like
how
this
touches
defy
space
and
what
some
of
the
early
thoughts
or
broad
level
you
can
speak
at
whatever
level
of
specificity,
you
think
is
appropriate
around
around
how
active
inferencing
can
relate
to
like
amms
and
and
things
like
that.
A
A
Well,
they
initially
emerged
specifically
to
solve
the
problem
of
the
high
degree
of
cost
and
transaction
frequency
that
would
be
required
to
do
a
normal
order
book
in
a
d5
space,
and
so
you
create
a
algorithmic
mechanism
to
do
that
instead,
but
the
issue
with
those
algorithmic
mechanisms
that
they
have
introduced.
So
you
know
times
b
equals
k
is
the
traditional
and
there
are
others
like
stable,
swap
and
the
whole
point
of
those
is,
though,
to
be
able
to
understand
the
relative
value
of
two
different
or
two
or
more
different.
A
You
know
coins
or
representations
of
value,
just
calling
points
for
now,
based
on
supply
and
demand
and
offsensible
value,
and
then
just
compute
that
algorithmically,
but
the
thing
with
that
is
obviously
it
can
get
quite
volatile
and
whenever
you're
sort
of
arbitrarily
trying
to
structure
the
relation
of
two
or
more
coins
in
the
presence
of
the
market
in
the
presence
of
arbitraging
agents
or
people
who
are
just
trying
to
be
extractive
or
play
an
extractive
game,
it
becomes
quite
risky.
A
A
Well,
then,
something
capital
that
just
got
blown
up
because
there's
like
a
hack
in
which
essentially,
they
were
gifted
a
huge
amount
of
of
one
particular
coin
and
that
put
their
amm
into
a
state
that
was
not
programmed
for
and
that
made
them
vulnerable
to
a
massive.
You
know:
13
million
or
yeah
30
million
dollar
extraction
and
that
sort
of
put
them
underwater.
So,
for
example,
these
mechanisms
are
kind
of
fragile
if
they're
just
computed
without
respect
to
any
extrinsic
reality,
any
extrinsic
set
of
circumstances.
A
C
Questioned
question
about
that
matthew
so,
as
I
was
watching,
some
of
your
guys's
work,
your
summary
of
some
of
your
work
on
this
recently.
One
of
my
questions
was
really
around.
Is
the
pr
or
my
sense
of
things
was
that
basically,
what
you're
talking
about
is
coupling
an
active
inferencing
model
of,
for
instance,
the
value
of
the
economic
value
of
carbon
drawdown,
or
something
like
that
to
the
elliptical
to
the
bonding
curve
that
an
amm
is
operating
on,
so
that
that
bonding
curve
is
actually
responsive,
not
just
to
buy
and
sell
orders.
A
A
It's
taking
into
account,
you
know
in
in
terms
of
the
it's,
if
you
kind
of
think
of,
like
the
simple
case,
with
two
different
coins
on
either
side
of
a
scale,
you're,
sort
of
you're
sort
of
bounding,
the
movements
of
one
of
those
and
the
justification
for
bounding.
The
movements
of
the
volatility
of
the
movements
of
one
of
those
like
by
either
doing
something
like
a
burn,
ornament
or
other
possible
ways
of
bounding
that
you
know
that
flux,
price
fluctuation
or
volume
fluctuation.
A
On
one
side,
your
the
justification
for
that
is
that
it's
actually
attached
to
something
that
is
a
real
representation
of
an
ecological
state
and
that
there's
intrinsic
value
in
reducing
the
uncertainty
associated
with
that
ecology
and
our
understanding
of
how
to
steward
that
ecology,
and
so
that,
in
theory,
attracts
people
who
care
about
the
long-term
value
of
that
of
that
state
of
that
ecology
of
that
vision.
And
then,
insofar
as
those
people
care
about
that
in
the
long
term.
A
That
basically
provides
greater
stability
within
this
amm
mechanism
by
coupling
that
free
energy
metric.
That's
an
open,
transparent
metric
over
the
system.
Right,
it's
not
just
saying
we're
arbitrarily
changing
the
price
fluctuations
which
some
algorithms
do
in
terms
of
arbitrarily
deciding
how
much
to
burn
emit
based
on
a
desired
sort
of
state
of
the
amm
itself.
So
it's
kind
of
just
a
self-referential
structure
like
we
want
the
amm
to
be
in
this
particular
stable
state.
A
So
we're
going
to
do
this
because
we
want
it
to
be
in
this
particular
stable
state,
and
this
is
saying
more
like
no.
No.
This
is
an
actual
mechanism
coupled
to
a
real
extrinsic
system.
People
performing
real
work
to
improve
a
real
ecology,
because
that's
in
line
with
the
community's
values
and
to
the
extent
that
that
community
can
maintain
that
investment
in
that
care
for
those
values
it
can
help
to
stabilize
this
liquidity
dynamic
by
something
like
an
amm.
So
that's
the
general
overall
idea
and
we're
still
experimenting.
A
You
know,
obviously
not
in
the
real
market.
Yet
we're
experimenting
with
models
to
see
if
this
could
work,
there's
some
early
promising
signs
and
then
we're
initially
we're
going
to
be
increasingly
working
towards.
You
know
putting
this
on
some
chestnuts
and
seeing
what
the
the
actual
real
world
behavior
begins
to
look
like.
B
Awesome
I
mean
for
those
who
are
listening:
is
there
a
way
that
they
can
kind
of
follow
along
or
how
to
stay,
how
to
stay
up
to
date?
With
with
some
of
these,
these
applications
trying
on
test
nets,
seeing
how
it
works
with
amms?
How
can
folks
like
keep
abreast
of?
What's
the
state
of
the
art
of
active
inferencing.
A
We
just
well
save
the
art
of
active
inferencing.
There
are
a
few
different
groups
out
there
for
for
that
in
general,
but
this
specific
application,
bioforms
lab,
just
created
a
discord.
So
we
could
share
that.
I
don't
have
that
off
my
head,
but
we
did.
You
know
that
is
a
goal
of
the
near
term
to
start
bringing
in
more
people
from
the
community
any
interested
observers
and
any
interested
contributors.
There
that's
going
to
be
the
primary
point
of
contact
outside
of
that.
A
We,
as
we
make
progress,
we're
going
to
be
sharing
that
progress,
but
currently
we
don't
yet
have
a
like
a
website
or
anything
like
that,
because
this
has
just
been
a
sort
of
off-the-grid
research
project
thus
far,
but
I
think
it's
going
to
be
increasingly
visible
and
as
that
visibility
increases
we'll
definitely
let
definitely
let
people
know
and
the
primary
channel
for
that
information
release
will
be
discord
at
first
and
then.
I'm
sure
greg
will
also
broadcast
that
when
we're
a
little
bit
more
ready
to
take
things
into
more
visible
space.
C
Been
kind
enough
to
offer
to
continue
to
come
and
share
updates
here
on
the
regenerating
news,
hours
and
twitter
spaces,
and
I'm
also
thinking
we'll,
probably
do
you
know
some
sort
of
recorded
zoom,
slideshow
sort
of
thing
periodically
as
as
important
as
milestones
are
met
and
work
kind
of
continues,
just
to
sort
of
be
able
to
share
this
back
and
then
point
back
to
the
bio
forms,
discord
and
you
know
maybe
active
channels
and
in
the
region.
Discord
as
this
is
applied
more
concretely,
more
and
more
concretely
to
ecological
state
claims
and
crediting,
etc.
A
Yeah
that'll,
I
mean
that'll,
be
when
it
gets
extremely
interesting
when
we
actually
are
really
digging
into
the
specific
models
and
applying
the
more
general
framework
to
regen's
use
cases,
and
you
know
we'll
be
able
to
say
a
lot
more
that
I
think
will
just
be
easier
for
people
to
directly
relate
to,
because
it'll
just
be
much
more
concrete
at
that
point,
yeah
right
now,
with
the
preliminary
it's
been
a
bit
abstract,
but
I'm
looking
forward
to
making
it
more
applicable
and
more
easy
for
people
to
digest
in
ways
that
are
directly
relevant
to
them
over
time.
C
A
Yeah,
that's
exactly
right
and
so
right
now
it's
a
lot
of
really
deep
abstract
work
because
of
the
fact
that
it
has
to
have
that
flexibility
to
be
able
to
then
be
used
in
concrete
instances,
and
so
a
lot
of
it
is
engaging
directly
with
the
low-level
libraries
that
were
made
accessible
by.
You
know
the
researchers
and
scientists
that
have
been
developing
active
inference
and
trying
to
map
those
into
more
of
the
applied
world,
and
so
it's
been
a
lot
of
that
kind
of
work
and
then
the
next
phase
is
going
to
be.
A
You
know,
working
with
a
lot
of
you
know
the
internal
team
at
regen
to
make
this
much
more
specific
and
concrete
around
regen
specific
economic
incentives,
regen
specific
goals
and
way
that
ways
that
it
sees
ecologies
ways
that
it
sees
actual.
You
know,
projects
with
the
goal
of
increasing
carbon
capture
through
alterations
to
complex
systems
and
then
it'll
be
very
grounded
in
those
specific
systems
that
region's
targeting.
B
Super
cool,
I'm
looking
forward
to
the
day
when
the
sort
of
trad
standards
of
vera
are
trying
to
integrate
the
new
credit
methodologies
with
active
inferencing
onto
onto
their
process,
so
that
it's
flowing
from
from
web3
native
registry
back
towards
more
like
trad
registries.
A
A
It
does
provide
the
flexibility
to
have
very
complex
multi-scale
models
and
also,
you
know,
can
model
very
different
types
of
systems,
so
it
is
kind
of
like
a
interface
that
can
help
to
standardize
across
many
different
kinds
of
models
and
to
the
extent
that
those
integrations
gain
from
using
this
like.
If
we
demonstrate
that
that's
actually
an
advantage,
then
it
kind
of
places
a
pretty
significant
pressure
on
other
actors
who
aren't
using
this
paradigm
to
adopt
it.
A
Given
the
fact
that
you
know
the
fundamental
mathematics
of
this,
if
they
do
work
in
the
world
essentially
say
that
if
you're
reducing
uncertainty
under
this
paradigm,
you're
actually
using
the
information
in
the
world
more
effectively
than
you
know,
others
who
aren't
using
this
so
like
you're,
actually
maximizing
your
ability
to
use
information
to
steward
a
system
and
the
whole
the
whole
constraint
around.
A
This
is
like
directed
toward
that
effective
use
of
information,
ecology
and
you
know
in
an
applied
sense,
and
so
I
think
it's
pretty
powerful
tool
and
if
it
does
work,
it's
going
to
provide
a
pretty
strong
incentive
for
others
to
adopt
it.
C
To
this
whole
process
as
ecological
state
protocols,
or
that
is
to
say
the
protocols,
models
and
measurement
protocols
that
allow
us
to
understand
ecological
state
and
then
make
claims
and
issue,
you
know,
credits
or
assets
right
and
very
early.
We
realized
that
this
is
really
quite
nested,
so
you
may
have
you
know
like
a
soil
carbon
methodology
and
a
model
that
accompanies
it.
You
know
biodiversity
or
above
ground
biomass.
C
You
know
these
are
all
linking
into
sort
of
global
climate
models
and
other
things,
and
so
you
know
back.
Then
we
were
sort
of
groping
around
in
the
dark,
and
you
know
I
sort
of
had
some
faith
that
there
was
going
to
be
a
way
to
create
kind
of
a
standard
methodological
approach
across
these
different
scales.
But
it's
really
just
now
by
intersecting,
with
active
inferencing,
the
work
that
bioforms
labs
is
doing.
You
know
the
the
whole
paradigm
that
carl
fristen
has
brought
forth
that
I'm
starting
to
feel
like.
A
A
But
the
interesting
aspect
about
this
act
of
interesting
paradigm
is
that
it
unifies
all
of
those
insofar
as
it
shows
that
each
of
those
previous
models
in
these
different
spaces
are
just
special
cases
of
this
overall
framework
because
of
the
fact
that
what
really
ties
all
of
nature's
systems
together
is
this
capacity
for
any
given
system
to
use
information
and
energy
effectively
in
order
to
make
sure
that
it
is,
you
know
it
is
representing
the
world's
causal
structure
in
a
way
that
allows
for
its
further
continued
life
and
growth
and
evolution
and
regeneration.
A
C
So
there's
about
five
minutes
left,
I'm
sure
austin
has
some
some
thoughts
wrap
up,
but
I
did
want
to
ask
you
matt
just
for
make
make
ask
and
make
statements
around
you
know.
So
this
is
a
research
and
development
project
that
that
regen
is
contributing
to
that
other
people
are
contributing
to
what
are
you
know.
There's
been
a
lot
of
early
conversation
as
this
was
going
around
licensing
around.
You
know
who's
owning
this
work.
C
How
is
it
going
to
be
commercialized
right,
as
we've
been
thinking
about
all
this,
and
you
know
instead
of
me
just
proclaiming
you
know
my
strong
beliefs
on
that
I'd
love
for
you
to
answer
for
yourself
and
to
the
degree
you
can
around
bio
forms.
You
know
just
like.
What's
the
approach
here,
you
know:
how
is
this
foundational
research
and
development
work
yeah?
How
are
we
focusing
on
bringing
it
to
the
world
as
a
group
of
humans
trying
to
sort
of
build
this
toolkit
yeah.
A
Yeah,
well
I
mean
the
primary.
The
primary
focus
is
on
providing
high
quality
tools
that
are
open
for
as
many
people
to
use
who
wish
to
use
this
for
or
who
find
value
right
like
the
idea
we're
doing
this
under
mit
licensing
at
first,
and
you
know
specific
instantiations
and
applications
later
down
the
road.
You
know
people
could
use
those
economically
or
you
know
kind
of
they
could
take
that
in
the
directions
they
wish
to.
Take
that,
but
fundamentally,
at
this
base
level
we
want
this
to
be
an
open
platform.
A
Anyone
who
has
interest
in
this
or
the
capacity
to
contribute
to
it.
You
know
we
welcome
those
contributions.
Eventually,
you
know
in
we're
just
getting
the
github
repo
off
the
ground,
but
that's
also
going
to
be
something
to
which
you
know
open
source
contributors
could
contribute
if
they
wish
to
get
involved.
Also-
and
that's
in
line
also
with
the
general
active
inference
community.
A
There's
a
lab
out
of
berkeley
run
by
daniel
friedman,
he's
a
really
interesting
and
awesome
guy
and
and
they're
also
doing
a
bunch
of
open
work
right
now,
they're
doing
a
textbook.
Reading
that
active
inference
textbook.
Just
came
out,
they
have
a
lot
of
collaborative
work
and
they're
very
welcoming
to
anyone
at
any
interest
level,
and
you
know
who
wants
to
apply
this
concept
in
any
domain
and
they're
doing,
and
they
will
be
continuing
to
do
these
types
of
book
read-throughs
and
lessons
in
education
and
on
our
side.
A
We're
also
going
to
be
continuing
to
try
to
build
this
community
out
and
develop
as
much
of
a
as
much
of
a
high
quality
open
foundation
for
this
work
for
the
supplied
work
of
active
inference
in
the
real
world
as
is
possible,
and
then
you
know
whatever
comes
from
that,
you
know
that
will
be
up
to
others
who
apply
this
more
specifically
to
their
own
problems,
and
you
know
they
can
develop
whatever
legal
structures
or
sort
of
ip
structures
they
wish
around
that.
B
Yeah
well,
thank
you
for
that.
I
mean
the
the
potential
for
this.
This
type
of
tool
to
lower
the
barrier
for
more
more
projects,
to
launch
methodologies
and
to
be
able
to
earn
rewards
for
their
stewardship
is
super
super
exciting
and
yeah.
B
Thanks
for
stewarding
the
stewards,
I
don't
have
any
like
witty
wrapping
up
comments
other
than
this
is
super
exciting,
and
I
I
hope
that
this
drives
it
in
a
direction
where
it
decentralizes
the
sort
of
ownership
of
ecological
state
attestations
that
more
communities
can
have
more
capacity
to
own
and
and
build
projects
and
build
methodologies
which
reflect
their
needs
and
circumstances.
B
I
I
was
kind
of
a
bad
host
before
and
I
didn't
really
realize
that
I
had
request
granting
access
so
sophia,
teemo
josh.
I'm
sorry
that
I
didn't
grant
you
all
the
request.
I
have
to
hop
off,
but
if
people
want
to
keep
going,
I'm
welcomed
happy
to
hand
over
the
hand
over
the
reins.
Otherwise,
I
think
we'll
probably
call
it.
A
C
Sorry
well
go
ahead,
I
mean
if,
if
folks
there
are,
I
only
see
one
request
right
now
that
just
happened.
So
maybe
I
missed
it
because
I
was
up
later
there.
B
C
C
Sorry
we
missed
folks,
we
usually
do
keep
it
to
an
hour.
I
see
you
know
it's,
it's
always
a
shame.
We
when
we
got
great
engagement
and
an
exciting
topic,
I
am
also
going
to
need
to
hop.
So
I
would.
C
Yeah,
I
think,
I
think,
we'll
I
think,
we'll
close
down
but
super
grateful
matt
for
your
time,
austin
for
your
time
and
and
everybody
for
hopping
and
listening.
Hopefully,
this
has
been
sort
of
fruitful
and
sort
of
spark.
Some
thinking.
If
you
have
questions
or
comments,
you
know,
feel
free
to
just
dm
or
reach
out,
and
you
know
and
we'll
this
is.
This
is
gonna,
be
a
living
ongoing
conversation.
C
So
please,
chime
in
and
we'll
be
doing
our
best
to
kind
of
we've
put
folks
into
this,
this
process
of
exploring
how
active
inferencing
might
serve
the
refi
space
so
onward,
and
thanks
everybody
for
your
time.