Younger
readers
may
not
remember,
but
cloud
computing
was
once
the
future.
The
advent
of
unlimited
computing
and
storage
resources
represented
one
of
the
few
tech
‘revolutions’
worthy
of
the
name.
But
the
age
of
AI
has
made
the
centralized
cloud
model
not
only
obsolete
but
also
an
active
danger
for
those
building
on
it
—
and
for
every
user,
too.
The
AI
Summit
at
Consensus
2024
takes
place
Friday,
May
31,
in
Austin,
Texas.
If
that
sounds
a
little
hyperbolic,
consider
the
recently
uncovered
vulnerability
affecting
Hugging
Face,
a
major
AI-as-a-Service
platform.
This
vulnerability
could
potentially
allow
tampered
models
uploaded
by
users
to
execute
arbitrary
code
via
their
inference
API
feature
to
gain
escalated
control.
Fortunately,
this
was
spotted
in
time
and
did
not
seem
to
have
seriously
affected
users
—
although
researchers
point
out
that
such
vulnerabilities
are
“far
from
unique.”
The
problem
here
isn’t
with
AI
at
all;
it’s
the
outdated,
centralized,
X-as-a-Service
models,
where
there’s
no
incentive
either
to
guarantee
the
security
of
their
systems
or
to
develop
applications
that
the
market
and
ordinary
users
want.
The
preferred
future
of
AI
—
where
it
is
safe,
secure,
and,
above
all,
able
to
draw
on
vast
compute
resources
—
can
only
be
achieved
by
flipping
the
cloud
on
its
head
and
embracing
the
decentralization
revolution.
‘Big
Cloud’
and
the
monopolization
of
AI
Megacorps
like
Microsoft,
OpenAI,
Google,
and
Amazon
dominate
the
AI
field
because
they
have
the
immense
financial,
human,
and
compute
resources
necessary
to
make
it
work
at
scale.
This
is
terrible
for
the
development
of
AI,
and
completely
antithetical
to
its
democratizing
potential.
When
algorithms
and
applications
are
built
by
a
small
coterie
of
devs
at
trillion-dollar
California
companies,
it
imposes
a
blinkered,
one-dimensional,
and
incredibly
subjective
bias
on
AI
agents.
This
affects
everything
from
financial
services,
to
creativity…even
to
human
interactions.
There
are
equally
compelling
technical
arguments
against
the
monopolization
of
the
AI
market.
Throughout
its
training
process,
AI
must
feed
on
a
constant
diet
of
new
data,
including
from
other
AI
applications.
Yet
the
current
centralizing
tendencies
of
Big
AI
mean
platforms
and
applications
remain
highly
siloed,
even
with
open-source
models.
This
hinders
innovation
and
leaves
the
field
open
for
errors
or
malicious
applications
which
can
multiply
with
dizzying,
potentially
catastrophic
consequences.
What’s
more,
the
centralized
model
has
enormous
and
obvious
risks
when
it
comes
to
safeguarding
users’
personal
data,
privacy,
and,
in
many
cases,
financial
information.
When
one
entity
holds
huge
volumes
of
sensitive
and
business-critical
data,
it
represents
a
single
point
of
failure
for
attackers
and
enables
one
provider
to
censor
or
deny
services
to
its
users
based
on
arbitrary
and
unchallengeable
decisions.
Democratization
through
decentralization
When
it
comes
to
AI,
the
cloud
model
is
clearly
a
dangerous
dead-end.
AI
requires
such
phenomenal
amounts
of
computing
power
that
it
stretches
the
capabilities
of
even
the
hyperscale
centralized
cloud
platforms
and
the
microchip
industry
that
serves
them.
The
chip
shortage
is
so
severe
that
there
is
now
an
astonishing
52-week
wait
for
the
H-100
servers
used
by
the
industry’s
most
advanced
AI
applications.
Through
decentralization,
we
can
eliminate
this
problem
at
a
stroke
by
creating
a
network
of
nodes
that
harness
huge
reserves
of
unused
CPU
power.
This
modular
approach
of
decentralized
physical
infrastructure
(DePIN)
is
perfect
for
multiple
reasons:
it’s
almost
infinitely
scalable,
far
cheaper
than
spinning
up
new
servers
with
your
cloud
provider
(costs
are
typically
around
80%
lower),
and
contributes
to
parallel
computing
and
the
de-siloization
of
AI,
so
applications
can
more
easily
learn
from
each
other.
In
addition,
decentralized
AI,
enabled
by
blockchain
technology,
offers
innovative
ways
to
reward
creators
of
large
language
models
(LLMs)
through
crypto
tokens
and
smart
contracts
–
providing
a
sustainable
and
equitable
model
for
rewarding
innovation
and
contribution
in
the
AI
field.
The
rise
of
new
economic
models
—
in
particular,
those
based
on
digital
tokens
—
not
only
increases
the
need
for
more
secure
decentralized
infrastructure;
it
supports
it,
too.
Basing
the
AI
ecosystem
on
a
token
economy
incentivises
developers
to
create
more
secure
AI
agents,
and
enables
them
to
deliver
these
models
into
a
crypto
wallet
for
ownership.
This
gives
users
complete
peace
of
mind
that
their
data
is
theirs
and
cannot
be
shared
without
their
knowledge
or
permission.
Perhaps
most
importantly
of
all,
the
token
model
means
that
AI
projects
will
deliver
what
the
market
truly
wants
and
needs,
as
compute
and
storage
costs
reflect
the
iron
law
of
supply-and-demand.
With
the
current
monopolization,
there
is
no
incentive
for
AI
to
serve
real-life
needs
and
demands.
Under
decentralization,
users
themselves
can
reward
developers
based
on
an
AI
agent’s
popularity
or
the
good
it
brings
to
the
world.
This
could
not
be
more
different
from
the
Big
Tech
oligarchy
that
currently
—
but
not
for
long
—
rules
the
roost
of
AI.
Decentralization
also
provides
an
answer
to
vulnerabilities
we’ve
seen
on
platforms
like
Hugging
Face.
With
the
rapid
evolution
of
blockchain
technology
—
in
particular,
zero-knowledge
(ZK)
proofs
—
we
now
have
a
range
of
tools
to
ensure
the
security
and
provenance
of
AI
applications.
For
those
of
us
close
to
these
developments,
we
can
often
forget
the
sheer
speed
and
profundity
of
this
technological
transformation.
It’s
not
that
traditional
cloud
providers
are
fighting
tooth-and-nail
to
retain
outdated
models;
it’s
simply
that
decentralization
and
ZK
are
very
recent
inventions,
and
it’s
naturally
taking
a
little
time
for
industry
players
to
realize
how
they
can
best
be
applied
in
their
(and
their
customers’)
interests.
It’s
largely
a
matter
of
education:
to
show
that
decentralized
AI
architecture,
when
built
correctly,
is
private
and
secure
by
design,
with
all
on-chain
data
encrypted
yet
still
supporting
interaction
and
collaboration
between
different
projects,
nodes
and
parties.
With
AI,
centralization
doesn’t
work
on
any
level:
technical,
philosophical,
ethical,
or
market.
What’s
more,
I
suggest
that
with
people
growing
increasingly
weary
(and
wary)
of
the
outsized
influence
of
Big
Tech
—
from
developers
to
tech
providers
to
everyday
users
like
you
and
me
—
the
time
has
clearly
come
for
a
revolution
of
our
own.
Note:
The
views
expressed
in
this
column
are
those
of
the
author
and
do
not
necessarily
reflect
those
of
CoinDesk,
Inc.
or
its
owners
and
affiliates.