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9
tr
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to
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lo
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m
y
by
2030
[
1
]
.
T
h
e
p
o
ten
tial
of
AI
to
in
ter
r
u
p
t
leg
ac
y
b
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[
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wi
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r
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[
3
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.
T
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led
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in
AI
s
tar
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ups
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at
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d
s
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s
tr
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r
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r
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tatio
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s
[
2
]
.
AI
-
d
r
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tech
s
tar
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ups
ar
e
th
e
f
o
r
ef
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o
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s
f
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m
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ltifa
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y
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T
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tar
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ups
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o
f
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d
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by
tec
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s
,
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tech
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s
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as
to
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ls
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ess
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V
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telli
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1037
cr
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s
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an
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p
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f
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[
4
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,
wh
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n
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v
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with
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-
d
r
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p
r
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d
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cts
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[
2
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.
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if
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t
f
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to
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ass
o
ciate
d
with
r
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ch
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ev
elo
p
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e
n
t
[
2
]
,
s
u
p
p
o
r
tiv
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tech
n
ical
in
f
r
astru
ctu
r
e
f
o
r
AI
in
teg
r
atio
n
[
4
]
.
Ven
tu
r
e
ca
p
ital
(
VC
)
is
a
k
ey
en
ab
ler
by
p
r
o
v
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g
f
i
n
an
cia
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s
u
p
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t,
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tr
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,
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in
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s
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n
etwo
r
k
s
to
h
elp
in
s
ca
lin
g
up
an
d
co
m
p
etin
g
g
lo
b
ally
[
5
]
.
VC
is
a
f
o
r
m
of
eq
u
ity
f
in
a
n
cin
g
th
at
d
ea
ls
with
f
u
n
d
in
g
at
ea
r
ly
s
tag
es
of
s
tar
t
-
ups
an
d
n
ew
b
u
s
in
ess
es
[
6
]
.
Acc
o
r
d
in
g
to
th
e
New
Yo
r
k
T
im
es
(
2
0
2
4
)
,
g
lo
b
al
VC
in
v
estme
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t
in
AI
s
tar
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ups
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as
s
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s
.
In
2
0
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4
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s
in
v
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$
2
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1
b
illi
o
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in
to
AI
s
tar
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ups
[
7
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r
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lectin
g
g
r
o
win
g
co
n
f
i
d
en
c
e
in
AI
-
in
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o
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s
.
Ho
wev
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r
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is
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is
f
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t
with
ch
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ality
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ce
s
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p
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al
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an
d
in
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s
tr
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ch
allen
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[
8
]
.
T
h
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k
s
o
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in
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tain
s
tar
t
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up
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r
o
wth
a
n
d
p
r
o
f
itab
ilit
y
[
2
]
.
T
h
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is
s
u
es
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r
eq
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e
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tly
s
tem
f
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d
s
tar
t
-
u
p
s
,
c
o
n
tr
ib
u
tin
g
to
d
elay
e
d
p
r
o
d
u
ct
d
ev
elo
p
m
en
t
an
d
d
if
f
icu
lties
in
s
ca
lin
g
.
As
Flo
r
id
i
[
9
]
ca
u
tio
n
s
,
u
n
ch
ec
k
e
d
VC
en
th
u
s
iasm
ca
n
in
f
late
an
AI
‘
tech
b
u
b
b
le
’
wh
er
e
in
v
estme
n
t
o
u
tp
ac
es
r
ea
l
ec
o
n
o
m
ic
v
al
u
e
an
d
wea
k
r
e
g
u
latio
n
f
ails
to
r
ein
in
h
y
p
e,
u
n
d
er
s
co
r
in
g
wh
y
s
tag
e
-
awa
r
e
r
is
k
tax
o
n
o
m
y
is
cr
itical
to
p
r
o
m
o
te
more
ef
f
ec
tiv
e
an
d
g
r
o
u
n
d
ed
in
v
estme
n
t
d
ec
is
io
n
s
an
d
s
tar
t
-
up
g
r
o
wth
.
Desp
ite
th
is
r
ec
o
g
n
ize
d
n
ee
d
f
o
r
a
s
tr
u
ctu
r
e
d
u
n
d
e
r
s
tan
d
in
g
of
r
is
k
,
c
u
r
r
e
n
t
liter
atu
r
e
lack
s
a
s
y
s
tem
atic
an
aly
s
is
of
how
r
is
k
f
ac
to
r
s
ev
o
lv
e
ac
r
o
s
s
d
if
f
e
r
en
t
g
r
o
wth
s
tag
es
of
AI
s
tar
t
-
u
p
s
.
T
h
e
cu
r
r
en
t
liter
atu
r
e
m
ain
ly
f
o
cu
s
es
on
i
n
d
iv
id
u
al
r
is
k
ty
p
es
lik
e
m
a
r
k
et
or
tech
n
o
lo
g
y
wh
ile
p
r
o
v
i
d
in
g
b
r
o
ad
i
n
s
ig
h
ts
in
to
VC
in
v
estme
n
t
p
atter
n
s
with
o
u
t
ad
d
r
ess
in
g
th
e
s
tag
e
-
s
p
ec
if
ic
an
d
u
n
p
r
ed
ictab
le
n
a
tu
r
e
of
r
is
k
s
in
AI
d
o
m
ain
.
Mo
r
e
o
v
er
,
lim
ited
s
y
n
th
esis
ex
is
ts
on
how
s
tar
t
-
up
m
at
u
r
ity
s
h
a
p
es
in
v
esto
r
s
’
r
is
k
p
e
r
ce
p
tio
n
s
in
AI
-
d
r
iv
en
tech
s
tar
t
-
u
p
s
.
T
h
i
s
lack
of
s
tr
u
ctu
r
ed
,
s
tag
e
-
b
a
s
ed
k
n
o
wled
g
e
co
n
tin
u
es
to
co
n
s
tr
ain
ef
f
ec
tiv
e
d
ec
is
io
n
-
m
ak
in
g
f
o
r
b
o
th
in
v
e
s
to
r
s
an
d
f
o
u
n
d
er
s
.
To
ad
d
r
ess
th
is
g
ap
,
th
is
s
tu
d
y
ad
o
p
ts
a
s
y
s
tem
atic
liter
atu
r
e
r
ev
iew
(
SLR)
to
m
ap
an
d
s
y
n
th
esize
f
r
ag
m
en
ted
ev
i
d
e
n
ce
an
d
id
en
tify
s
tag
e
-
s
p
ec
i
f
ic
r
is
k
ca
teg
o
r
ies.
Acc
o
r
d
in
g
ly
,
th
is
r
esear
ch
s
ee
k
s
to
f
ill
th
e
id
en
tifie
d
g
ap
an
d
an
s
wer
th
e
f
o
llo
win
g
q
u
esti
o
n
s
:
i)
wh
at
ar
e
th
e
k
ey
r
is
k
v
ar
iatio
n
s
af
f
e
ctin
g
VC
in
v
estme
n
t
in
AI
d
r
iv
en
t
ec
h
s
tar
t
-
u
p
s
?
an
d
(
ii)
wh
at
a
r
e
th
e
d
if
f
er
e
n
ce
s
in
th
ese
r
is
k
s
ac
r
o
s
s
th
e
g
r
o
wth
s
tag
es
of
AI
d
r
i
v
en
tech
s
tar
t
-
u
p
s
an
d
VC
in
v
estme
n
ts
?
T
h
is
r
ev
iew
id
e
n
tifie
d
an
d
ca
t
eg
o
r
ized
th
e
k
ey
r
is
k
s
in
f
lu
en
cin
g
VC
in
v
estme
n
ts
in
AI
-
d
r
iv
en
tec
h
s
tar
t
-
ups
ac
r
o
s
s
d
if
f
er
en
t
g
r
o
wth
s
tag
es.
By
o
f
f
er
in
g
a
s
tag
e
-
s
p
ec
if
ic
r
is
k
tax
o
n
o
m
y
,
th
e
s
tu
d
y
s
u
p
p
o
r
ts
VC
s
in
alig
n
in
g
d
u
e
d
ilig
en
ce
p
r
o
c
ess
es
an
d
in
v
estme
n
t
s
tr
ateg
ie
s
more
ef
f
ec
tiv
ely
.
It
also
o
f
f
er
s
in
s
ig
h
ts
f
o
r
AI
s
tar
t
-
ups
f
o
u
n
d
er
s
to
b
etter
u
n
d
er
s
tan
d
in
v
esto
r
co
n
c
er
n
s
at
each
g
r
o
wth
s
tag
e
an
d
p
r
ep
a
r
e
s
tr
o
n
g
er
f
u
n
d
in
g
ap
p
r
o
ac
h
es.
Aca
d
em
ically
,
th
e
r
ev
iew
ad
d
r
ess
es
a
cr
itical
g
ap
by
e
x
p
lo
r
i
n
g
h
o
w
in
v
estme
n
t
r
is
k
s
v
ar
y
ac
r
o
s
s
s
tag
es
an
d
p
r
o
v
id
es
a
f
o
u
n
d
ati
o
n
f
o
r
f
u
t
u
r
e
em
p
ir
ical
r
esear
c
h
to
s
u
p
p
o
r
t
in
f
o
r
m
ed
in
v
estm
en
t
d
ec
is
io
n
s
.
2.
T
H
E
O
R
E
T
I
CA
L
B
A
SI
S
2
.
1
.
AI
driv
en
t
ec
h
s
t
a
rt
-
ups
AI
-
d
r
iv
en
tech
s
tar
t
-
ups
lack
a
u
n
iv
er
s
ally
ac
ce
p
ted
d
ef
in
it
io
n
in
en
tr
ep
r
en
e
u
r
s
h
ip
an
d
i
n
n
o
v
atio
n
liter
atu
r
e,
u
s
es
o
v
er
lap
p
in
g
t
er
m
s
f
o
r
v
en
tu
r
es
ap
p
ly
i
n
g
AI
in
v
ar
y
in
g
ca
p
ac
ities
.
Dr
awin
g
on
p
r
ev
io
u
s
s
tu
d
ies,
th
ese
s
tar
t
-
ups
ar
e
tak
en
as
n
ew
en
tr
e
p
r
en
e
u
r
ial
f
ir
m
s
or
s
tar
t
-
u
p
s
,
s
ca
led
r
a
p
id
ly
by
em
b
ed
d
in
g
AI
as
a
co
r
e
v
alu
e
-
cr
ea
tio
n
m
ec
h
an
is
m
r
ath
er
th
an
a
s
u
p
p
o
r
tin
g
to
o
l.
T
h
ese
s
tar
t
-
ups
lev
er
ag
e
m
ac
h
in
e
lear
n
in
g
(
ML
)
,
n
atu
r
al
lan
g
u
a
g
e
p
r
o
ce
s
s
in
g
(
NL
P)
,
an
d
r
elate
d
AI
tec
h
n
o
lo
g
ies
to
e
n
h
an
ce
d
ec
is
io
n
-
m
ak
in
g
,
au
to
m
ate
p
r
o
ce
s
s
es,
an
d
d
eliv
er
p
er
s
o
n
alize
d
o
f
f
er
in
g
s
[
1
0
]
,
wh
ile
g
ain
in
g
ef
f
icien
c
y
,
ac
c
u
r
ac
y
,
an
d
co
m
p
etitiv
e
ad
v
an
tag
e
[
1
1
]
.
Su
ch
s
tar
t
-
u
p
s
ex
p
er
im
e
n
t
with
e
m
er
g
in
g
AI
tec
h
n
o
l
o
g
ies
s
u
ch
as
d
ee
p
lear
n
in
g
an
d
co
m
p
u
ter
v
is
io
n
to
d
ev
elo
p
a
d
ap
tiv
e
an
d
ev
o
lv
in
g
s
o
l
u
tio
n
s
[
2
]
an
d
p
u
r
s
u
e
co
m
m
er
cializa
tio
n
of
AI
-
ce
n
tr
ic
in
n
o
v
atio
n
s
in
ar
ea
s
in
clu
d
in
g
d
ee
p
lear
n
in
g
,
v
is
u
al
r
ec
o
g
n
itio
n
,
co
m
p
u
ter
v
is
io
n
,
or
f
r
o
m
in
n
o
v
ativ
e
r
ec
o
m
b
in
atio
n
of
ex
is
tin
g
AI
m
eth
o
d
s
[
3
]
.
T
h
ese
r
eq
u
i
r
e
co
n
s
id
er
ab
le
r
eso
u
r
ce
s
to
b
u
i
ld
AI
ca
p
ab
ilit
ies
th
r
o
u
g
h
AI
f
ac
to
r
y
ap
p
r
o
ac
h
wh
ile
o
p
tim
izin
g
s
ca
le,
s
co
p
e,
an
d
lear
n
i
n
g
th
r
o
u
g
h
th
e
m
an
ag
em
en
t
of
AI
p
r
o
ce
s
s
es
[
1
2
]
,
as
s
h
o
wn
in
Fi
g
u
r
e
1.
T
h
ese
AI
s
tar
t
-
ups
r
el
y
on
VC
in
v
estme
n
t
to
estab
lis
h
AI
f
ac
to
r
ies
an
d
m
an
ag
e
AI
-
r
elate
d
p
r
o
ce
s
s
es
an
d
r
is
k
s
[
1
2
]
.
T
h
is
f
o
u
n
d
atio
n
al
u
n
d
er
s
tan
d
in
g
p
r
o
v
i
d
es
a
b
asis
ex
am
in
in
g
th
e
r
o
le
of
VC
in
s
u
p
p
o
r
tin
g
th
e
ir
d
ev
elo
p
m
e
n
t
an
d
lo
n
g
-
ter
m
g
r
o
wth
ef
f
icien
cy
,
p
ar
ticu
l
ar
ly
th
e
u
n
iq
u
e
r
is
k
r
ea
liti
es
ass
o
ciate
d
with
d
ata,
m
o
d
el
tr
ain
in
g
,
an
d
talen
t
in
te
n
s
ity
.
2
.
2
.
VC
inv
estm
ent
in
AI
driv
en
t
ec
h
s
t
a
rt
-
ups
R
ec
en
t
s
tu
d
ies
s
u
g
g
est
th
at
VC
s
p
lay
a
cr
itical
r
o
le
in
s
u
p
p
o
r
tin
g
AI
-
d
r
iv
e
n
tech
s
tar
t
-
ups
by
en
ab
lin
g
th
e
d
ev
el
o
p
m
en
t
of
AI
f
ac
to
r
ies
[
1
2
]
th
at
ce
n
tr
ali
ze
d
ata
p
r
o
ce
s
s
in
g
[
1
3
]
,
m
o
d
e
l
tr
ain
in
g
[
1
4
]
,
an
d
d
ep
lo
y
m
e
n
t
p
r
o
ce
s
s
es
th
er
eb
y
r
ed
u
cin
g
th
e
d
ata
r
is
k
s
[
1
2
]
,
an
d
s
u
p
p
o
r
tin
g
s
ca
lab
ilit
y
.
B
ey
o
n
d
ca
p
ital,
VC
s
p
r
o
v
id
e
b
u
s
in
ess
an
d
f
in
an
cial
s
u
p
p
o
r
t
[
1
2
]
,
wh
ich
ac
ce
ler
ates
g
r
o
wth
of
AI
s
tar
t
-
ups
but
also
in
tr
o
d
u
ce
s
s
p
ec
if
ic
r
is
k
s
r
eq
u
ir
i
n
g
ca
r
e
f
u
l
ev
alu
atio
n
.
H
o
wev
er
,
VC
in
v
estme
n
t
in
AI
r
em
ai
n
s
lack
in
g
f
r
o
m
an
o
p
er
atio
n
al
p
er
s
p
ec
tiv
e
[
1
5
]
.
Prio
r
s
tu
d
ies
em
p
h
asized
f
u
n
d
in
g
an
d
s
tr
ateg
y
with
lim
ited
atten
tio
n
to
AI
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
5
2
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3
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t J Ar
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tell
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Vo
l.
1
5
,
No
.
2
,
Ap
r
il 2
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2
6
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103
6
-
1
0
4
9
1038
s
p
ec
if
ic
m
o
n
ito
r
in
g
,
due
d
ilig
en
ce
,
an
d
tech
n
ical
ass
ess
m
en
t
d
if
f
er
w
h
en
in
v
esti
n
g
in
AI
s
tar
t
-
ups
co
m
p
ar
e
d
to
co
n
v
e
n
tio
n
al
tech
v
en
tu
r
es.
T
h
er
ef
o
r
e,
AI
s
tar
t
-
ups
r
e
p
r
es
en
t
a
n
ew
d
r
iv
e
r
of
v
alu
e
p
r
o
p
o
s
itio
n
th
r
o
u
g
h
AI
ca
p
ab
ilit
ies,
p
r
o
v
id
e
d
if
f
er
e
n
t
r
o
les
of
d
ata
f
o
r
v
alu
e
cr
ea
tio
n
an
d
th
e
o
f
f
e
r
in
g
an
im
p
ac
t
of
tech
n
o
lo
g
y
on
o
v
er
all
b
u
s
in
ess
lo
g
ic,
wh
ile
elab
o
r
atin
g
p
r
o
m
is
in
g
d
i
r
ec
tio
n
s
f
o
r
en
tr
ep
r
en
eu
r
s
h
ip
a
n
d
s
i
g
n
if
ican
t
ec
o
n
o
m
ic
im
p
ac
t
[
1
4
]
.
As
th
ese
s
tar
t
-
u
p
s
o
p
er
ate
with
h
ig
h
er
r
esear
c
h
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d
d
ev
elo
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m
en
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tain
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y
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is
in
tr
o
d
u
ce
s
a
d
is
tin
ct
in
v
estme
n
t
lo
g
ic
an
d
s
tag
ewise
ev
alu
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n
.
Desp
ite
th
ese
in
s
ig
h
ts
th
e
liter
atu
r
e
r
em
ain
s
f
r
ag
m
en
ted
with
lim
ited
em
p
ir
ical
clar
ity
of
how
VC
s
ad
ju
s
t
ev
alu
atio
n
f
r
am
ewo
r
k
s
f
o
r
AI
-
s
p
ec
if
ic
r
is
k
s
in
clu
d
in
g
d
ata
g
o
v
er
n
an
ce
,
m
o
d
el
s
ca
lab
ilit
y
,
an
d
alg
o
r
ith
m
ic
p
er
f
o
r
m
an
ce
u
n
ce
r
tain
t
y
.
T
h
is
in
d
icate
s
in
s
u
f
f
icien
t
in
teg
r
atio
n
of
AI
tech
n
o
lo
g
ica
l
r
ea
liti
es
in
to
VC
in
v
estme
n
t
th
eo
r
y
.
Fig
u
r
e
1
.
AI
f
ac
to
r
y
ap
p
r
o
ac
h
f
o
r
AI
-
d
r
iv
en
tech
s
tar
t
-
ups
2
.
3
.
Ris
k
f
a
ct
o
rs
in
VC
inv
estm
ent
in
AI
driv
en
t
ec
h
s
t
a
rt
-
ups
L
in
[
1
6
]
h
ig
h
lig
h
ted
th
e
r
o
l
e
of
VC
in
f
o
s
ter
in
g
s
u
s
tain
ab
le
ec
o
n
o
m
ic
d
ev
elo
p
m
en
t,
h
o
wev
e
r
,
liter
atu
r
e
id
en
tifie
s
m
u
ltip
le
r
is
k
f
ac
to
r
s
,
in
clu
d
in
g
ec
o
n
o
m
ic,
p
o
liti
ca
l,
an
d
f
in
a
n
cial
r
is
k
s
,
wh
o
s
e
im
p
ac
t
on
VC
r
em
ain
s
lar
g
ely
u
n
ex
p
lo
r
ed
[
1
7
]
.
VC
ad
o
p
t
h
eter
o
g
en
eo
u
s
ev
alu
atio
n
a
p
p
r
o
ac
h
es,
p
ar
ticu
lar
ly
in
ass
es
s
m
en
t
o
f
en
tr
ep
r
en
e
u
r
i
al
team
s
,
co
m
b
in
in
g
in
tu
iti
v
e
ju
d
g
em
e
n
t
with
s
tr
u
ctu
r
ed
an
d
an
aly
tical
ev
alu
atio
n
s
m
ec
h
an
is
m
s
[
1
8
]
.
I
n
th
e
co
n
te
x
t
o
f
AI
s
tar
t
-
u
p
s
,
s
p
ec
ialized
tech
n
ical
ex
p
er
t
is
e
an
d
co
n
tex
tu
al
f
ac
to
r
s
s
u
ch
as
g
eo
g
r
ap
h
ic
d
is
p
ar
ities
f
u
r
th
er
s
h
ap
e
i
n
v
estme
n
t
ass
ess
m
en
t
p
r
o
ce
s
s
es
,
wh
i
le
f
u
n
d
in
g
r
em
ain
s
h
ig
h
ly
s
elec
tiv
e
with
o
n
ly
3
-
4
s
tar
t
-
u
p
s
f
r
o
m
o
v
er
5
0
0
p
r
o
p
o
s
als
ar
e
f
u
n
d
ed
[
1
9
]
.
VC
m
o
d
el
r
eq
u
i
r
es
s
tag
ed
in
v
estme
n
t
cy
cles
an
d
in
ter
r
u
p
tio
n
s
can
ca
u
s
e
o
p
er
atio
n
al
f
ai
lu
r
e
[
1
5
]
.
W
eb
er
et
a
l.
[
1
4
]
id
e
n
tifie
d
tech
n
o
l
o
g
y
r
elate
d
r
is
k
s
,
ass
o
ciate
d
with
d
ev
elo
p
in
g
an
d
im
p
lem
e
n
tin
g
AI
s
o
lu
tio
n
s
,
i
n
clu
d
in
g
p
o
ten
tial
alg
o
r
ith
m
ic
b
iases
an
d
er
r
o
r
s
,
s
ca
lab
ilit
y
c
h
allen
g
es,
an
d
co
n
ce
r
n
s
r
eg
a
r
d
in
g
th
e
q
u
ality
a
n
d
a
v
ailab
ilit
y
of
d
ata.
Desp
ite
th
ese
co
n
tr
ib
u
tio
n
s
,
cu
r
r
en
t
VC
r
is
k
s
p
r
im
ar
ily
ca
teg
o
r
ize
in
to
m
ar
k
et,
p
r
o
d
u
ct,
m
an
a
g
er
ial,
f
in
an
cial
an
d
in
s
u
f
f
icien
tly
in
teg
r
ate
AI
-
s
p
ec
if
ic
tech
n
o
lo
g
ical
a
n
d
d
ata
-
r
elate
d
r
is
k
s
.
C
o
m
p
a
r
ed
with
ex
is
tin
g
VC
in
v
estme
n
t
f
r
am
ewo
r
k
by
Go
m
p
er
s
et
a
l.
[
2
0
]
wh
ic
h
e
m
p
h
asizes
p
r
e
-
in
v
estme
n
t
s
c
r
ee
n
in
g
a
n
d
p
o
s
t
-
in
v
estme
n
t
m
o
n
ito
r
in
g
,
AI
s
tar
t
-
ups
in
tr
o
d
u
ce
ad
d
itio
n
al
lay
er
s
of
tec
h
n
o
lo
g
ical
an
d
d
ata
r
is
k
s
,
in
d
icatin
g
th
e
n
ee
d
f
o
r
ex
p
an
d
e
d
r
is
k
s
class
i
f
icatio
n
f
o
r
AI
s
tar
t
-
u
p
s
.
2
.
4
.
G
ro
wt
h
s
t
a
g
es
of
AI
t
ec
h
s
t
a
rt
-
ups
a
nd
VC
inv
e
s
t
m
ent
Pre
v
io
u
s
liter
atu
r
e
[
1
5
]
,
[
2
0
]
,
[
2
1
]
h
i
g
h
lig
h
ted
s
tag
es
in
s
tar
t
-
ups
co
n
ce
r
n
in
g
VC
in
v
estme
n
t,
in
clu
d
in
g
:
i
)
s
ee
d
/ear
ly
s
tag
e
f
o
r
tech
n
o
lo
g
y
ex
p
er
im
e
n
tatio
n
an
d
v
alid
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n
,
ii
)
g
r
o
wth
s
tag
e
with
co
m
m
er
cializa
tio
n
a
n
d
in
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m
ar
k
et
ad
o
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tio
n
,
an
d
iii
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later
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r
ity
s
tag
e
with
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ca
lin
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n
d
p
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ep
ar
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r
in
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p
u
b
lic
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f
f
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in
g
(
I
PO
)
/acq
u
is
itio
n
.
T
h
e
n
at
u
r
e
an
d
s
ev
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ity
of
r
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k
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ev
o
lv
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ac
r
o
s
s
th
ese
s
tag
es
an
d
in
d
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g
h
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o
g
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n
o
u
s
VC
i
n
v
o
lv
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e
n
t,
s
h
if
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g
f
r
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m
ca
p
ab
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n
d
tec
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ic
al
due
d
ilig
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ar
k
et
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ca
lin
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p
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t
an
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t.
Un
d
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s
tan
d
in
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s
tag
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f
o
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m
s
th
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elo
p
m
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of
co
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p
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r
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k
ta
x
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m
y
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T
h
i
s
d
ir
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tly
in
f
o
r
m
s
th
e
ap
p
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n
of
a
th
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r
etica
l
len
s
f
o
r
s
tr
u
ctu
r
ed
an
aly
s
is
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
V
en
tu
r
e
ca
p
ita
l a
n
d
r
is
ks in
g
r
o
w
th
s
ta
g
es o
f a
r
tifi
cia
l in
telli
g
en
ce
tech
s
ta
r
t
-
ups
(
S
a
r
a
A
z
iz
)
1039
2
.
5
.
T
heo
re
t
ica
l
persp
ec
t
iv
e
R
is
k
m
an
ag
em
en
t
th
eo
r
y
f
o
c
u
s
es
on
s
y
s
tem
atic
id
e
n
tific
a
tio
n
,
ass
ess
m
en
t,
an
d
m
an
a
g
em
en
t
of
p
o
ten
tial
r
is
k
s
th
at
m
ay
af
f
e
ct
o
r
g
an
izatio
n
al
o
b
jectiv
es.
Alth
o
u
g
h
th
e
co
n
ce
p
t
of
r
is
k
d
ates
b
ac
k
o
v
er
2
,
400
y
ea
r
s
with
ea
r
ly
ex
am
p
les
f
r
o
m
t
h
e
Ath
en
ia
n
s
.
Ho
we
v
er
,
r
is
k
m
an
a
g
em
en
t
as
a
f
o
r
m
al
s
cien
tific
f
ield
em
er
g
ed
with
in
th
e
last
30
-
40
y
ea
r
s
[
2
2
]
.
R
is
k
m
an
ag
e
m
e
n
t
an
d
its
ap
p
licatio
n
in
VC
in
v
estme
n
t
r
em
ain
u
n
d
er
d
ev
elo
p
e
d
in
m
an
ag
e
m
en
t
an
d
en
tr
ep
r
e
n
eu
r
s
h
ip
liter
atu
r
e
[
2
3
]
,
d
esp
ite
VC
in
v
estme
n
ts
b
ein
g
in
h
er
en
tly
h
ig
h
-
r
is
k
,
p
a
r
ticu
lar
ly
f
o
r
s
tar
t
-
ups
f
ac
i
n
g
liab
ilit
y
of
n
ewn
ess
an
d
h
ig
h
er
f
ailu
r
e
r
ates.
Acc
o
r
d
i
n
g
to
I
SO
3
1
0
0
0
,
r
is
k
m
an
a
g
e
m
en
t
is
a
co
n
tin
u
o
u
s
cy
cle
of
r
is
k
id
e
n
tific
atio
n
,
ass
ess
m
en
t,
tr
ea
tm
en
t,
an
d
m
o
n
ito
r
in
g
with
r
is
k
ev
o
lv
in
g
o
v
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tim
e
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d
ac
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s
s
s
tag
es.
I
SO
31000
g
r
o
u
p
e
d
r
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id
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tific
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n
,
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aly
s
is
,
an
d
e
v
alu
atio
n
u
n
d
er
r
is
k
ass
es
s
m
en
t
[
2
4
]
,
a
n
d
class
if
ied
r
is
k
s
in
to
s
tr
ateg
ic,
f
in
an
cial,
o
p
er
atio
n
al,
tech
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o
lo
g
ical,
leg
al
or
r
e
g
u
lat
o
r
y
,
an
d
r
e
p
u
tatio
n
al
ca
teg
o
r
i
es.
T
h
e
two
co
r
e
p
r
o
p
o
s
itio
n
s
,
in
clu
d
in
g
th
e
r
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k
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o
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g
o
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th
e
cl
ass
if
y
in
g
r
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s
in
to
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r
o
a
d
er
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ies,
lead
to
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is
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n
m
a
k
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e
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n
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of
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d
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W
h
ile
I
SO
31000
p
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r
im
ar
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s
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r
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id
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an
d
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v
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,
AI
-
d
r
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v
en
s
tar
t
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ups
o
p
e
r
ate
with
in
s
p
ec
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tech
n
o
lo
g
y
d
e
v
elo
p
m
en
t
life
cy
cles
th
at
in
tr
o
d
u
ce
d
y
n
am
ic
u
n
ce
r
tain
ties
.
Fra
m
ewo
r
k
s
s
u
ch
as
cr
o
s
s
-
in
d
u
s
tr
y
s
tan
d
ar
d
p
r
o
ce
s
s
f
o
r
d
ata
m
in
in
g
(
C
R
I
SP
-
DM
)
[
2
5
]
an
d
AI
f
ac
to
r
y
[
1
2
]
s
h
o
ws
how
r
is
k
s
em
er
g
e
a
cr
o
s
s
d
ata
ac
q
u
is
itio
n
,
m
o
d
el
d
ev
elo
p
m
e
n
t,
d
e
p
lo
y
m
e
n
t
,
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d
c
o
n
tin
u
o
u
s
im
p
r
o
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em
e
n
t,
q
u
ality
,
alg
o
r
ith
m
ic
b
ias,
m
o
d
el
d
r
if
t,
ex
p
lai
n
ab
ilit
y
an
d
o
p
er
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al
r
eliab
ilit
y
.
In
th
is
r
ev
iew
,
r
is
k
m
an
ag
em
en
t
th
eo
r
y
s
tr
u
ctu
r
es
an
d
ca
teg
o
r
izes
r
is
k
s
id
en
tifie
d
in
th
e
liter
atu
r
e
in
alig
n
m
en
t
with
R
Q1
an
d
R
Q2
,
u
s
in
g
a
life
cy
cle
an
d
p
r
o
ce
s
s
-
o
r
ien
ted
ap
p
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o
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h
to
e
x
p
lo
r
e
how
r
is
k
p
er
c
ep
tio
n
s
h
if
ts
ac
r
o
s
s
g
r
o
wth
s
tag
es
of
AI
tech
s
tar
t
-
u
p
s
.
Gu
id
ed
by
I
SO
3
1
0
0
0
p
r
i
n
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les,
a
co
n
ce
p
t
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ap
on
Fig
u
r
e
2
illu
s
tr
ates
how
r
is
k
id
en
tific
atio
n
an
d
a
s
s
es
s
m
en
t
p
r
o
ce
s
s
es
g
u
id
ed
t
h
e
class
if
icatio
n
of
r
is
k
s
an
d
how
th
ese
ev
o
lv
e
ac
r
o
s
s
th
e
life
cy
cle
of
AI
-
d
r
i
v
en
s
tar
t
-
ups
an
d
u
ltima
tely
in
f
l
u
en
cin
g
VC
d
ec
is
io
n
m
a
k
in
g
.
Fig
u
r
e
2.
C
o
n
ce
p
tu
al
m
ap
of
r
is
k
s
ac
r
o
s
s
VC
in
v
estme
n
t
an
d
AI
s
tar
t
-
ups
g
r
o
wth
s
tag
es
3.
M
E
T
H
O
D
T
h
is
s
tu
d
y
f
o
llo
wed
th
e
SLR
ap
p
r
o
ac
h
to
id
en
tify
th
e
r
is
k
v
ar
iatio
n
s
th
at
in
f
lu
en
ce
VC
in
v
estme
n
t
d
ec
is
io
n
s
in
AI
-
d
r
iv
en
tech
s
tar
t
-
u
p
s
.
Mo
h
er
et
a
l.
[
2
6
]
u
s
ed
p
r
e
f
er
r
e
d
r
e
p
o
r
tin
g
item
s
f
o
r
s
y
s
tem
atic
r
ev
iews
an
d
m
eta
-
an
al
y
s
is
(
PR
I
SMA)
g
u
id
elin
es.
T
h
e
r
ev
iew
in
clu
d
es
th
e
f
o
llo
win
g
s
tep
s
.
3
.
1
.
T
o
pic
identif
ica
t
io
n
a
nd
s
elec
t
io
n
of
re
lev
a
nt
lite
ra
t
ure
T
h
is
s
tu
d
y
co
n
d
u
cted
with
a
s
y
s
tem
atic
ap
p
r
o
ac
h
g
u
i
d
ed
by
th
e
PR
I
SMA
g
u
id
elin
es
[
2
7
]
,
[
2
8
]
to
en
s
u
r
e
th
o
r
o
u
g
h
id
en
tific
atio
n
an
d
r
e
v
iew
of
p
u
b
lis
h
ed
s
t
u
d
ies
to
id
en
tify
r
is
k
v
ar
iatio
n
s
in
f
lu
en
cin
g
VC
in
v
estme
n
t
d
ec
is
io
n
s
in
AI
-
d
r
iv
en
tec
h
s
tar
t
-
u
p
s
.
T
h
e
s
ea
r
ch
s
tr
ateg
y
f
o
cu
s
ed
on
VC
in
v
estme
n
t
r
is
k
s
,
f
u
n
d
in
g
s
tag
es,
an
d
r
is
k
m
itig
atio
n
,
s
y
n
th
esizin
g
p
ee
r
-
r
e
v
ie
wed
jo
u
r
n
al
ar
ticles
an
d
co
n
f
er
en
ce
p
r
o
ce
e
d
in
g
s
p
u
b
lis
h
ed
b
etwe
en
2
0
1
9
-
2
0
2
4
with
a
f
o
cu
s
on
th
o
s
e
th
at
d
is
cu
s
s
VC
in
v
estme
n
t
in
AI
tech
s
tar
t
-
u
p
s
.
T
h
e
tim
ef
r
am
e
r
ef
lects
th
e
p
e
r
io
d
of
in
te
n
s
if
ied
in
AI
tech
n
o
lo
g
ies
an
d
ac
ce
p
tan
ce
with
in
cr
ea
s
ed
f
u
n
d
in
g
in
ter
est,
in
cr
ea
s
ed
s
tar
t
-
up
ac
t
iv
ity
,
th
e
g
r
o
win
g
VC
in
ter
est
f
o
llo
win
g
a
d
v
an
c
es
in
AI
m
o
d
els.
Sear
ch
was
p
er
f
o
r
m
ed
ac
r
o
s
s
f
o
u
r
ac
a
d
e
m
ic
d
atab
ases
,
in
clu
d
in
g
I
E
E
E
E
x
p
l
o
r
e,
W
eb
of
Scien
ce
(W
o
S),
Sco
p
u
s
,
an
d
Pro
Qu
est,
s
elec
ted
f
o
r
th
eir
b
r
o
ad
co
v
er
ag
e
of
tech
n
o
l
o
g
y
,
en
tr
e
p
r
en
e
u
r
s
h
ip
,
an
d
in
v
estme
n
t
r
esear
ch
.
Key
wo
r
d
s
in
clu
d
ed
“
v
en
tu
r
e
c
ap
ital”,
“AI
-
s
tar
tu
p
s
”,
“d
ee
p
t
ec
h
n
o
lo
g
y
”,
“in
v
estme
n
t
r
is
k
s
”,
“g
r
o
wth
s
tag
es”,
“seed
s
tag
e”
,
“m
atu
r
ity
s
tag
e”
,
v
en
tu
r
e
ca
p
ital
r
is
k
s
”,
an
d
“r
is
k
m
itig
atio
n
”.
I
n
clu
s
i
o
n
cr
iter
ia
co
v
er
ed
ac
ad
em
ic
an
d
co
n
f
e
r
en
ce
p
u
b
licatio
n
s
ad
d
r
ess
in
g
VC
in
v
estme
n
t
d
ec
is
io
n
s
,
r
is
k
f
ac
to
r
s
,
an
d
AI
s
tar
t
-
u
p
s
ac
tiv
ity
,
wh
ile
s
tu
d
ies
u
n
r
elat
ed
to
VC
in
v
estme
n
t
r
is
k
s
,
AI
tech
n
o
lo
g
y
,
or
f
u
n
d
in
g
s
tr
ateg
ies
wer
e
ex
clu
d
ed
.
To
en
s
u
r
e
co
n
s
is
ten
cy
in
r
is
k
id
en
tific
atio
n
,
a
s
tr
u
ctu
r
e
d
class
if
icatio
n
lo
g
ic
was
ap
p
lied
,
in
f
o
r
m
ed
by
estab
lis
h
ed
VC
an
d
r
is
k
m
an
ag
em
en
t
ty
p
o
l
o
g
ies.
R
is
k
s
we
r
e
o
r
g
an
ize
d
in
to
m
u
tu
ally
e
x
clu
s
iv
e
ca
teg
o
r
ies,
in
clu
d
in
g
tech
n
o
lo
g
ical,
f
in
a
n
cial,
o
p
er
atio
n
al,
m
ar
k
et,
r
eg
u
lato
r
y
an
d
ex
it
r
is
k
s
.
An
y
r
is
k
r
elate
d
to
p
r
o
d
u
ct
-
m
ar
k
et
f
it
or
cu
s
to
m
e
r
ad
o
p
ti
o
n
was
co
d
e
d
as
m
ar
k
et
r
is
k
s
.
I
SO
3
1
0
0
0
in
f
o
r
m
ed
t
h
e
p
r
o
ce
s
s
lo
g
ic
of
R
i
sk
M
a
n
a
g
e
m
e
n
t
T
h
e
o
r
y
(
I
S
O
3
1
0
0
0
)
R
i
sk
M
a
n
a
g
e
m
e
n
t
Pr
o
c
e
ss
(
I
d
e
n
t
i
f
y
-
A
sse
ss
-
T
r
e
a
t
-
M
o
n
i
t
o
r
)
R
i
sk
C
a
t
eg
o
ri
es
A
I T
e
c
h
S
t
a
r
t
u
p
s
S
t
a
g
e
(
Ea
r
l
y
-
G
r
o
w
t
h
-
L
a
t
e
r
)
Evaluation Warning : The document was created with Spire.PDF for Python.
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9
1040
r
is
k
tag
g
in
g
an
d
in
ter
p
r
etatio
n
,
en
ab
lin
g
s
y
s
tem
atic
s
y
n
th
esis
ac
r
o
s
s
s
tu
d
ies.
T
h
is
r
ev
iew
p
o
s
itio
n
s
its
elf
at
th
e
in
ter
s
ec
tio
n
of
AI
en
tr
e
p
r
en
eu
r
s
h
ip
a
n
d
VC
in
v
estme
n
t
by
ex
am
in
i
n
g
h
o
w
AI
-
r
el
ated
r
is
k
ca
teg
o
r
ies
ev
o
lv
e
ac
r
o
s
s
s
tar
t
-
up
s
tag
es.
T
h
e
p
r
o
ce
s
s
of
s
cr
ee
n
in
g
r
e
lev
an
t
s
tu
d
ies
is
illu
s
tr
ated
in
Fig
u
r
e
3
of
th
e
PR
I
SMA
d
iag
r
am
.
Fig
u
r
e
3
.
PR
I
SMA
d
iag
r
am
of
s
ea
r
ch
s
tr
ateg
y
3
.
2
.
Scre
ening
of
s
t
ud
ies
An
in
itial
pool
of
857
a
r
ticles
was
r
etr
iev
ed
u
s
in
g
th
e
d
ef
in
ed
s
ea
r
ch
s
tr
in
g
s
an
d
s
elec
tio
n
cr
iter
ia.
Du
r
in
g
th
e
in
itial
s
cr
ee
n
in
g
,
d
u
p
licates
an
d
clea
r
ly
u
n
r
elate
d
s
tu
d
ies
wer
e
r
em
o
v
ed
,
r
esu
l
tin
g
in
350
ar
ticles
r
etain
ed
f
o
r
title
an
d
ab
s
tr
ac
t
r
ev
iew.
Su
b
s
eq
u
e
n
t
elig
ib
ilit
y
ass
es
s
m
en
t
in
v
o
lv
e
d
f
u
ll
tex
t
to
en
s
u
r
e
alig
n
m
en
t
with
VC
in
v
o
lv
e
m
en
t
in
AI
-
f
o
cu
s
ed
s
tar
t
-
u
p
s
an
d
d
is
cu
s
s
of
r
is
k
r
elate
d
f
ac
to
r
s
.
Stu
d
ie
s
th
at
f
ailed
to
m
ee
t
cr
iter
ia
wer
e
ex
clu
d
ed
.
Fo
llo
win
g
th
e
s
cr
ee
n
in
g
p
r
o
ce
s
s
,
am
o
n
g
3
5
0
,
a
to
tal
of
321
s
tu
d
ies
wer
e
ex
clu
d
ed
due
to
d
u
p
licatio
n
,
t
h
em
atic
ir
r
el
ev
an
ce
or
in
s
u
f
f
icien
t
ac
a
d
e
m
ic
r
ig
o
r
,
leav
i
n
g
29
s
tu
d
ies
f
o
r
f
in
al
in
clu
s
io
n
.
T
h
ese
29
s
tu
d
ies
co
m
p
r
is
ed
jo
u
r
n
al
ar
ticles
an
d
co
n
f
er
en
ce
p
ap
er
s
th
at
p
r
o
v
id
e
d
iv
er
s
e
p
er
s
p
ec
tiv
es
on
r
is
k
an
d
in
v
estme
n
t
co
n
s
id
er
atio
n
s
in
AI
d
r
iv
en
en
t
r
ep
r
en
e
u
r
ial
v
en
tu
r
es.
T
h
ese
29
s
o
u
r
ce
s
as
s
h
o
wn
in
T
ab
le
1
f
o
r
m
ed
th
e
b
asis
f
o
r
s
y
n
th
esis
an
d
an
aly
s
is
in
th
is
r
ev
iew.
3
.
3
.
Da
t
a
s
y
nthesis
a
nd
a
na
ly
s
is
T
h
is
p
h
ase
in
v
o
lv
ed
th
r
ee
s
y
s
tem
atic
p
r
o
ce
d
u
r
es
to
f
ac
i
litate
a
co
m
p
r
e
h
en
s
iv
e
a
n
aly
s
is
of
th
e
s
elec
ted
s
tu
d
ies:
d
ata
ex
tr
ac
tio
n
,
s
y
n
th
esis
,
an
d
r
e
p
o
r
tin
g
.
3
.
3
.
1
.
Da
t
a
ex
t
ra
c
t
io
n
A
s
tr
u
ctu
r
ed
d
ata
ex
tr
ac
tio
n
w
as
u
s
ed
to
s
y
s
tem
atica
lly
co
lle
ct
r
elev
an
t
in
f
o
r
m
atio
n
f
r
o
m
e
ac
h
of
th
e
29
s
elec
ted
s
tu
d
ies.
T
h
e
e
x
tr
a
cted
d
ata
in
cl
u
d
ed
au
th
o
r
(
s
)
,
y
ea
r
of
p
u
b
licatio
n
,
s
tu
d
y
o
b
jec
tiv
es,
ab
s
tr
ac
ts
an
d
k
ey
c
o
n
clu
s
io
n
s
.
T
h
is
s
tep
e
n
s
u
r
ed
co
n
s
is
ten
cy
in
d
ata
h
an
d
l
in
g
an
d
e
n
ab
led
a
r
eliab
le
co
m
p
ar
is
o
n
of
d
iv
er
s
e
s
tu
d
y
f
in
d
in
g
s
.
3
.
3
.
2
.
Da
t
a
s
y
nthesis
T
h
e
co
llected
d
ata
wer
e
s
y
n
th
esized
u
s
in
g
a
th
e
m
atic
an
al
y
s
is
ap
p
r
o
ac
h
th
r
o
u
g
h
a
s
tr
u
c
tu
r
ed
d
ata
ex
tr
ac
tio
n
p
r
o
ce
s
s
.
It
was
ap
p
lied
to
id
en
tify
r
ec
u
r
r
in
g
p
atter
n
s
an
d
co
n
ce
p
ts
,
wh
ich
wer
e
g
r
o
u
p
e
d
in
t
o
ca
teg
o
r
ies
co
r
r
esp
o
n
d
in
g
to
th
e
r
esear
ch
q
u
esti
o
n
s
.
T
h
em
es
wer
e
co
n
s
tr
u
cted
ar
o
u
n
d
r
is
k
f
ac
to
r
s
in
VC
in
v
estme
n
t
d
ec
is
io
n
s
f
o
r
AI
-
d
r
iv
en
tech
s
tar
t
-
u
p
s
,
ty
p
es
of
r
is
k
s
,
r
is
k
f
ac
to
r
id
en
tific
atio
n
at
d
if
f
er
e
n
t
g
r
o
wth
s
tag
es.
A
h
y
b
r
id
c
o
d
in
g
ap
p
r
o
ac
h
co
m
b
in
in
g
in
d
u
ctiv
e
a
n
d
d
ed
u
ctiv
e
co
d
in
g
s
tr
ateg
ies
w
as
u
s
ed
,
with
in
itial
m
u
tu
al
co
d
i
n
g
f
o
llo
wed
by
r
ef
in
em
en
t
u
s
in
g
NViv
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in
g
p
r
o
ce
d
u
r
es.
T
h
is
s
tu
d
y
alig
n
e
d
wit
h
PR
I
SMA
g
u
id
elin
es
an
d
in
co
r
p
o
r
ated
q
u
ality
s
af
eg
u
ar
d
s
s
u
itab
le
f
o
r
s
o
cial
s
cien
ce
ev
id
e
n
ce
s
y
n
th
esis
.
T
h
e
q
u
ality
was
in
d
ir
ec
tly
co
n
s
id
er
ed
by
s
elec
tin
g
o
n
ly
p
ee
r
-
r
ev
iewe
d
jo
u
r
n
al
ar
ticles
an
d
co
n
f
er
e
n
ce
p
ap
er
s
in
d
ex
ed
in
Sco
p
u
s
,
W
o
S
,
I
E
E
E
,
an
d
Pro
Q
u
est
wh
ich
ar
e
wi
d
ely
r
ec
o
g
n
ized
f
o
r
th
ei
r
ac
ad
em
ic
ac
cu
r
ac
y
.
4.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
s
y
n
th
esized
f
in
d
in
g
s
f
r
o
m
th
e
SL
R
of
29
s
elec
ted
s
tu
d
ies,
f
o
cu
s
in
g
on
VC
r
is
k
s
af
f
ec
tin
g
AI
tech
s
tar
t
-
ups
with
a
s
p
ec
if
ic
f
o
cu
s
on
v
ar
iatio
n
s
in
th
ese
r
is
k
s
ac
r
o
s
s
d
if
f
er
en
t
g
r
o
wth
s
tag
es.
T
h
e
an
aly
s
is
o
u
tlin
es
k
ey
VC
r
is
k
ty
p
es,
f
o
llo
wed
by
an
ex
a
m
in
atio
n
of
s
p
ec
if
ic
r
is
k
ca
teg
o
r
ies
th
at
em
er
g
e
d
u
r
in
g
t
h
e
s
ee
d
,
g
r
o
wth
,
an
d
m
atu
r
ity
s
tag
es
of
AI
s
tar
t
-
u
p
s
with
r
ef
er
en
ce
to
i
n
v
estme
n
t.
A
s
y
n
th
esized
m
atr
ix
is
th
e
n
d
e
v
elo
p
ed
to
s
y
s
tem
atica
lly
ca
te
g
o
r
ize
s
tag
e
-
s
p
ec
if
ic
r
is
k
s
.
A
n
ar
r
ativ
e
s
y
n
t
h
esis
s
u
p
p
o
r
ted
by
th
e
m
atic
an
aly
s
is
was
u
s
ed
,
with
NViv
o
15
ap
p
lied
to
en
s
u
r
e
s
y
s
tem
atic
q
u
a
litativ
e
co
d
in
g
.
4
.
1
.
Ris
k
s
a
f
f
ec
t
ing
VC
inv
e
s
t
m
ent
in
AI
VC
in
v
estme
n
t
h
as
s
u
r
g
ed
o
v
er
r
ec
en
t
d
ec
a
d
es
due
to
its
a
d
v
an
tag
es
o
v
er
o
th
e
r
f
in
an
cin
g
o
p
tio
n
s
.
Acc
o
r
d
in
g
to
L
i
u
[
4
9
]
,
one
k
e
y
b
en
ef
it
is
ac
ce
s
s
to
s
u
b
s
tan
t
ial
f
in
an
cial
r
eso
u
r
ce
s
th
at
ar
e
o
f
ten
in
ac
ce
s
s
ib
le
th
r
o
u
g
h
co
n
v
en
tio
n
al
f
u
n
d
i
n
g
ch
an
n
els.
Ho
wev
er
,
VC
in
v
estme
n
t
d
ec
is
io
n
s
in
v
o
lv
e
s
ev
er
a
l
r
is
k
s
f
ac
to
r
s
with
ex
ter
n
al
u
n
ce
r
tain
ties
an
d
in
t
er
n
al
in
d
u
s
tr
y
d
y
n
a
m
ics
[
6
]
.
To
s
tr
u
ctu
r
e
th
e
d
is
cu
s
s
io
n
of
r
is
k
s
,
th
is
r
e
v
iew
o
r
g
an
izes
th
em
in
to
s
ev
en
k
ey
ca
teg
o
r
ies
id
en
tifie
d
in
th
e
lit
er
atu
r
e,
in
clu
d
in
g
m
ar
k
et,
o
p
e
r
atio
n
al,
f
in
an
cial,
tech
n
o
lo
g
ical,
p
er
f
o
r
m
an
ce
,
r
eg
u
lato
r
y
an
d
leg
al,
an
d
ex
it
r
is
k
s
.
T
h
e
f
o
llo
win
g
s
u
b
s
ec
tio
n
s
ex
p
lo
r
e
each
ca
teg
o
r
y
,
h
ig
h
lig
h
tin
g
th
eir
r
el
ev
an
ce
to
VC
in
v
estme
n
t
in
AI
-
d
r
iv
e
n
tech
s
tar
t
-
u
p
s
.
4
.
1
.
1
.
M
a
rk
et
risk
s
Ma
r
k
et
r
is
k
r
ef
er
s
to
f
ailu
r
e
to
s
u
r
v
iv
e
wh
e
n
s
h
if
ts
in
co
n
s
u
m
er
p
r
e
f
er
en
ce
s
af
f
ec
t
a
co
m
p
an
y
’
s
g
r
o
wth
.
VC
in
v
estme
n
ts
ar
e
e
x
p
o
s
ed
to
m
ar
k
et
r
is
k
s
s
u
ch
as
s
ec
to
r
v
o
latilit
y
,
cu
r
r
en
cy
f
lu
ctu
atio
n
s
,
in
ter
est
r
ates,
an
d
v
alu
atio
n
c
h
allen
g
es
th
at
in
f
lu
e
n
ce
e
x
it
v
alu
e
[
6
]
.
Fo
r
AI
-
d
r
iv
en
tech
s
tar
t
-
u
p
s
,
t
h
is
r
is
k
is
h
eig
h
ten
ed
d
u
e
to
r
ap
id
tech
n
o
lo
g
ical
ch
an
g
e
an
d
ev
o
l
v
in
g
m
ar
k
et
ad
o
p
tio
n
of
AI
-
b
a
s
ed
s
o
lu
tio
n
s
[
4
4
]
.
Ma
r
k
et
r
is
k
also
in
clu
d
es
f
l
u
ctu
atio
n
s
in
d
em
a
n
d
with
r
ef
er
en
ce
to
AI
ap
p
licatio
n
s
f
o
r
m
ar
k
etin
g
a
n
d
s
eg
m
en
tatio
n
[
6
]
,
co
m
p
etitiv
e
p
r
ess
u
r
es
an
d
b
r
o
a
d
er
ec
o
n
o
m
ic
c
o
n
d
itio
n
s
[
1
7
]
,
wh
ic
h
can
q
u
ick
ly
alter
m
ar
k
et
d
y
n
am
ics
an
d
ch
alle
n
g
e
AI
s
tar
t
-
u
p
s
’
g
r
o
wth
an
d
tech
n
o
lo
g
ical
r
elev
an
ce
.
G
o
m
p
er
s
et
a
l.
[
2
0
]
em
p
h
asize
th
at
th
e
s
h
if
t
in
co
n
s
u
m
er
p
r
ef
er
en
ce
s
an
d
tec
h
n
o
lo
g
ical
ad
v
a
n
ce
m
en
ts
can
r
a
p
id
ly
alter
m
ar
k
et
d
y
n
am
ics
an
d
p
o
s
e
s
ig
n
if
ican
t
ch
allen
g
es
f
o
r
s
tar
t
-
u
p
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
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tell
I
SS
N:
2252
-
8
9
3
8
V
en
tu
r
e
ca
p
ita
l a
n
d
r
is
ks in
g
r
o
w
th
s
ta
g
es o
f a
r
tifi
cia
l in
telli
g
en
ce
tech
s
ta
r
t
-
ups
(
S
a
r
a
A
z
iz
)
1043
4
.
1
.
2
.
O
pera
t
io
na
l
risk
s
T
h
is
r
is
k
a
r
is
es
f
r
o
m
i
n
t
er
n
al
in
ef
f
i
cie
n
cies
,
m
a
n
a
g
em
en
t
i
s
s
u
es
a
n
d
f
ail
u
r
es
in
e
x
e
c
u
ti
o
n
,
wh
ic
h
h
i
n
d
e
r
t
h
e
ef
f
e
cti
v
e
e
x
ec
u
ti
o
n
of
b
u
s
i
n
ess
p
la
n
.
O
p
e
r
ati
o
n
al
r
is
k
s
s
t
em
f
r
o
m
i
n
t
er
n
al
f
a
ct
o
r
s
s
u
c
h
as
m
a
n
a
g
e
m
e
n
t
ca
p
a
b
i
lit
ies
,
e
x
e
c
u
ti
o
n
c
h
a
lle
n
g
es
,
a
n
d
o
p
er
ati
o
n
al
i
n
e
f
f
ici
en
ci
es
[
6
]
.
In
AI
-
d
r
iv
e
n
tec
h
s
t
a
r
t
-
u
p
s
,
o
p
e
r
at
io
n
a
l
r
is
k
s
i
n
cl
u
d
e
al
g
o
r
it
h
m
ic
i
n
a
cc
u
r
ac
ies
,
s
y
s
t
e
m
d
o
w
n
ti
m
e
p
o
s
e
s
i
g
n
i
f
ic
a
n
t
r
is
k
s
to
e
n
h
a
n
ce
r
el
ia
b
il
it
y
a
n
d
s
a
f
et
y
of
AI
m
o
d
els
[
3
5
]
.
D
ata
d
e
p
e
n
d
e
n
c
y
is
a
n
o
th
e
r
r
is
k
w
h
e
r
e
s
ta
r
t
-
u
p
s
ca
n
t
u
r
n
t
h
is
in
to
ad
v
a
n
t
a
g
e
by
d
e
v
el
o
p
i
n
g
p
r
o
p
r
iet
ar
y
d
at
asets
or
cr
ea
t
in
g
d
at
a
-
d
r
i
v
e
n
p
r
o
d
u
cts
d
is
ti
n
c
t
f
r
o
m
m
a
r
k
et
[
3
1
]
.
Scali
n
g
is
s
u
es
c
o
m
e
u
n
d
e
r
m
a
j
o
r
o
p
e
r
at
io
n
a
l
r
is
k
a
n
d
ca
n
im
p
e
d
e
g
r
o
w
th
a
n
d
r
ela
ti
o
n
s
wi
t
h
VC
i
n
v
es
to
r
s
[
1
5
]
ar
e
n
o
t
ju
s
t
a
r
is
k
b
u
t
als
o
o
p
p
o
r
tu
n
i
ty
f
o
r
AI
s
t
ar
t
-
u
p
s
.
A
d
d
i
tio
n
a
l
o
p
e
r
a
ti
o
n
al
r
is
k
s
s
te
m
f
r
o
m
d
e
p
e
n
d
e
n
c
y
on
th
i
r
d
-
p
ar
t
y
te
c
h
n
o
l
o
g
i
es,
d
at
a
p
r
o
v
i
d
e
r
s
,
an
d
la
c
k
of
s
t
r
a
te
g
i
c
p
ar
tn
e
r
s
h
ip
s
a
n
d
c
o
lla
b
o
r
at
io
n
s
[
3
2
]
.
4
.
1
.
3
.
F
ina
ncia
l
risk
s
It
in
v
o
l
v
es
p
o
o
r
f
i
n
an
cial
m
a
n
ag
em
en
t
an
d
liq
u
id
ity
is
s
u
es
th
at
m
ay
lead
to
co
llap
s
e
an
d
b
an
k
r
u
p
tcy
[
3
6
]
.
It
in
clu
d
es
ch
allen
g
es
r
el
ated
to
f
u
n
d
in
g
av
ailab
ilit
y
,
ca
s
h
f
lo
w
m
an
ag
em
e
n
t
a
n
d
f
in
a
n
cial
s
tab
ilit
y
,
with
liq
u
id
ity
r
is
k
ar
is
in
g
f
r
o
m
lo
n
g
-
ter
m
lo
ck
-
in
p
er
io
d
s
an
d
ab
s
en
ce
of
an
ac
tiv
e
s
ec
o
n
d
a
r
y
m
ar
k
et,
lim
itin
g
ex
it
tim
in
g
an
d
r
et
u
r
n
s
p
r
e
d
ictab
ilit
y
[
6
]
.
In
AI
-
d
r
iv
en
tec
h
s
tar
t
-
u
p
s
,
f
in
an
cial
r
is
k
in
ten
s
if
ied
by
h
ig
h
ca
p
ital
co
s
t
f
o
r
r
esear
ch
an
d
d
ev
elo
p
m
en
t
due
to
th
e
c
o
m
p
lex
n
atu
r
e
of
AI
tech
n
o
lo
g
ies
[
3
7
]
,
o
f
t
en
co
m
b
in
ed
with
d
elay
ed
r
ev
en
u
e
g
e
n
er
atio
n
a
n
d
ex
te
n
d
ed
tim
elin
es
to
p
r
o
f
itab
ilit
y
,
wh
ich
in
cr
ea
s
e
liq
u
i
d
ity
r
is
k
s
[
3
8
]
.
VC
in
v
esto
r
s
also
f
ac
e
v
alu
atio
n
r
elate
d
r
is
k
s
lin
k
ed
to
f
air
-
v
al
u
e
in
v
estme
n
t,
in
v
estme
n
t
m
u
ltip
les,
co
n
s
o
r
tiu
m
s
ize,
in
v
esto
r
ex
p
e
r
ien
ce
,
e
x
it
s
tr
ateg
ies,
an
d
f
in
an
ci
n
g
s
tag
e
th
at
r
esu
lt
in
v
al
u
e
f
l
u
ctu
atio
n
s
b
etwe
en
f
in
an
cin
g
an
d
e
x
it
[
3
9
]
.
Als
o
,
ag
en
c
y
r
is
k
in
VC
ar
is
es
f
r
o
m
in
f
o
r
m
atio
n
asy
m
m
etr
y
a
n
d
lim
ited
o
v
er
s
ig
h
t
wh
er
e
f
o
u
n
d
er
s
m
ay
act
in
th
e
ir
o
wn
in
ter
est
u
n
d
er
co
n
d
itio
n
s
of
u
n
ce
r
tain
ty
a
n
d
in
co
m
p
lete
in
f
o
r
m
atio
n
[
6
]
.
In
ad
d
itio
n
,
AI
s
tar
t
-
u
p
s
f
ac
e
ex
ten
d
e
d
tim
elin
e
to
p
r
o
f
itab
ilit
y
an
d
d
elay
e
d
e
x
its
d
u
e
to
lo
n
g
g
estatio
n
p
er
io
d
s
to
r
ef
in
e
t
h
eir
tech
n
o
l
o
g
ies
an
d
ac
h
iev
e
m
a
r
k
et
ac
c
ep
tan
ce
,
d
elay
in
g
p
o
te
n
tial
ex
it
an
d
r
etu
r
n
in
g
f
o
r
in
v
esto
r
s
[
2
0
]
,
[
3
9
]
.
W
h
ile
r
ap
id
tech
n
o
lo
g
ical
ad
v
an
ce
m
en
ts
an
d
ev
o
lv
in
g
m
ar
k
et
tr
e
n
d
s
,
f
in
an
cial
r
is
k
s
em
er
g
e
wh
er
e
s
tar
t
-
ups
s
tr
u
g
g
le
to
ca
p
tu
r
e
s
u
f
f
icien
t
m
ar
k
et
s
h
ar
e
am
id
s
t
ch
an
g
in
g
co
n
d
itio
n
s
[
3
2
]
.
4
.
1
.
4
.
T
ec
hn
o
lo
g
y
risk
s
T
h
is
r
is
k
a
r
is
es
f
r
o
m
u
n
ce
r
tai
n
ti
es
in
p
r
o
d
u
c
t
d
ev
el
o
p
m
e
n
t
,
te
ch
n
o
l
o
g
ic
al
a
d
v
a
n
c
e
m
e
n
ts
,
a
n
d
in
t
ell
ec
t
u
al
p
r
o
p
e
r
t
y
p
r
o
te
cti
o
n
[
6
]
,
wi
th
AI
s
ta
r
t
-
u
p
s
f
a
cin
g
k
n
o
w
le
d
g
e
o
b
s
o
l
esc
en
c
e,
c
h
a
n
g
i
n
g
m
ar
k
e
t
p
r
e
f
e
r
e
n
c
es,
a
n
d
f
l
u
ct
u
at
in
g
i
n
v
est
m
e
n
t
c
y
c
les
s
u
c
h
as
AI
win
te
r
s
wh
ic
h
r
e
f
l
ec
t
u
n
c
er
tai
n
t
y
in
t
ec
h
n
o
l
o
g
ica
l
tr
e
n
d
s
.
D
esp
ite
g
r
o
w
in
g
i
n
v
es
to
r
in
te
r
est
,
d
ee
p
le
ar
n
i
n
g
al
g
o
r
it
h
m
s
m
a
y
p
r
o
d
u
c
e
u
n
r
el
ia
b
le
o
u
t
co
m
es
,
wh
ile
ch
all
en
g
es
r
el
at
ed
to
e
x
p
lai
n
a
b
il
it
y
,
et
h
i
cs,
b
ias
,
t
r
u
s
t,
ta
le
n
t
s
h
o
r
ta
g
e
t
h
at
h
in
d
e
r
t
h
e
r
e
lia
b
le
a
n
d
s
ca
la
b
le
d
e
v
e
lo
p
m
e
n
t
of
AI
s
o
l
u
t
io
n
s
[
1
1
]
,
[
4
4
]
.
L
e
g
a
l
n
at
u
r
e
of
al
g
o
r
it
h
m
s
a
n
d
in
tel
lec
t
u
al
p
r
o
p
er
t
y
d
is
p
u
t
es
[
3
5
]
t
h
at
im
p
ac
t
t
h
ei
r
c
o
m
p
etit
iv
e
a
d
v
a
n
t
ag
e
a
n
d
m
a
r
k
et
p
o
s
it
io
n
.
AI
e
v
o
l
v
es
s
wi
f
t
ly
w
it
h
b
r
ea
k
t
h
r
o
u
g
h
s
an
d
ad
v
a
n
ce
m
e
n
ts
t
h
at
co
n
t
in
u
a
ll
y
r
esh
ap
e
i
n
d
u
s
t
r
y
s
ta
n
d
a
r
d
s
a
n
d
c
o
m
p
e
titi
v
e
d
y
n
am
ics
.
Stu
d
i
es
[
3
3
]
,
[
4
0
]
em
p
h
asi
ze
d
t
h
a
t
AI
s
t
ar
t
-
u
p
s
f
a
ce
tec
h
n
o
l
o
g
y
r
is
k
s
wh
en
b
e
c
o
m
i
n
g
o
u
t
d
at
ed
or
s
u
p
e
r
s
ed
ed
by
ad
v
an
ce
d
s
o
l
u
ti
o
n
s
,
u
n
d
e
r
m
i
n
e
m
a
r
k
et
p
o
s
it
io
n
,
a
n
d
v
a
lu
e
p
r
o
p
o
s
iti
o
n
.
AI
v
al
u
e
cr
ea
ti
o
n
d
e
p
e
n
d
s
on
ca
p
a
b
l
e
n
et
wo
r
k
s
th
a
t
ass
ess
i
n
te
r
n
a
l
AI
m
at
u
r
it
y
,
i
n
f
r
ast
r
u
ct
u
r
e,
i
n
d
u
s
tr
y
r
ea
d
in
ess
a
n
d
v
al
u
e
c
r
e
ati
o
n
p
o
t
en
t
ial
[
4
0
]
,
w
h
e
r
e
g
a
p
s
cr
ea
t
e
s
ig
n
i
f
i
ca
n
t
t
ec
h
n
o
lo
g
y
r
is
k
s
.
AI
t
ec
h
s
ta
r
t
-
ups
a
ls
o
f
a
c
e
t
ec
h
n
o
l
o
g
ica
l
f
e
asi
b
il
it
y
a
n
d
s
ca
l
ab
ilit
y
r
is
k
s
,
as
AI
al
g
o
r
it
h
m
s
a
n
d
m
o
d
els
m
a
y
p
er
f
o
r
m
u
n
p
r
e
d
ict
a
b
l
y
ac
r
o
s
s
d
atas
ets
a
n
d
en
v
i
r
o
n
m
en
ts
.
C
y
b
er
s
e
c
u
r
it
y
an
d
d
at
a
a
r
e
c
r
it
ica
l
te
ch
n
o
l
o
g
ic
al
r
is
k
s
th
at
a
f
f
ec
t
ass
et
s
e
c
u
r
it
y
,
v
al
u
ati
o
n
,
a
n
d
r
eg
u
l
at
o
r
y
c
o
m
p
li
an
ce
p
a
r
ti
c
u
la
r
l
y
u
n
d
er
g
e
n
e
r
a
l
d
at
a
p
r
o
te
cti
o
n
r
e
g
u
la
ti
o
n
s
(
GDPR
)
.
I
s
s
u
es
s
u
ch
as
al
g
o
r
it
h
m
ic
b
ias
a
n
d
f
ai
r
n
ess
ar
e
g
en
er
all
y
v
ie
we
d
as
te
ch
n
i
ca
l
s
h
o
r
tc
o
m
i
n
g
s
r
at
h
e
r
t
h
a
n
et
h
ic
al
p
r
o
b
l
e
m
s
[
3
3
]
.
P
r
o
te
cti
n
g
p
r
o
p
r
iet
ar
y
a
lg
o
r
it
h
m
s
,
p
a
te
n
ts
an
d
tr
ad
e
s
ec
r
ets
f
r
o
m
u
n
au
t
h
o
r
i
ze
d
u
s
e
or
i
m
it
ati
o
n
is
es
s
en
t
ial
f
o
r
co
m
p
et
iti
v
e
a
d
v
a
n
t
ag
e
a
n
d
VC
s
s
e
ek
ass
u
r
a
n
c
e
of
a
d
e
q
u
at
e
IP
s
tr
at
e
g
ies
a
n
d
s
a
f
e
g
u
a
r
d
s
to
m
i
ti
g
at
e
t
h
ese
r
is
k
s
[
3
4
]
.
4
.
1
.
5
.
P
er
f
o
r
m
a
nce
risk
s
It
is
r
el
ate
d
to
t
h
e
p
e
r
f
o
r
m
a
n
c
e
c
ap
a
b
ili
ties
of
s
ta
r
t
-
up
l
ea
d
e
r
s
h
i
p
,
t
ea
m
b
u
il
d
i
n
g
,
a
n
d
c
o
h
esi
o
n
,
w
h
i
ch
d
i
r
e
ctl
y
in
f
l
u
e
n
ce
i
n
n
o
v
a
ti
o
n
o
u
tc
o
m
es
.
AI
s
ta
r
t
-
ups
r
e
q
u
ir
e
s
c
ar
ce
a
n
d
e
x
p
en
s
iv
e
s
p
ec
i
aliz
e
d
t
ale
n
t
f
r
o
m
r
el
e
v
a
n
t
i
n
d
u
s
t
r
i
es,
p
a
r
ti
cu
la
r
l
y
in
a
r
ea
s
s
u
ch
as
N
L
P
te
ch
n
o
l
o
g
ies
li
k
e
t
h
o
s
e
d
e
v
e
lo
p
i
n
g
AI
C
h
at
b
o
ts
n
ee
d
ex
p
e
r
ts
in
ML
t
ec
h
n
i
q
u
es
[
4
0
]
a
n
d
i
n
n
o
v
ati
v
e
p
e
r
f
o
r
m
a
n
c
e
[
3
7
]
.
AI
s
ta
r
t
-
ups
ca
n
c
r
e
at
e
a
n
d
c
ap
tu
r
e
v
al
u
e
t
h
e
f
a
ct
o
r
s
r
e
lat
ed
to
n
o
v
e
lt
y
a
n
d
e
x
p
e
ct
ati
o
n
s
of
ef
f
i
cie
n
c
y
a
n
d
p
er
f
o
r
m
a
n
ce
.
Pe
r
f
o
r
m
a
n
c
e
i
n
d
i
ca
t
o
r
s
i
n
cl
u
d
e
p
r
o
d
u
ct
iv
it
y
,
p
r
o
f
i
ta
b
il
it
y
,
co
s
t
r
e
d
u
c
ti
o
n
s
a
n
d
in
v
e
n
t
o
r
y
r
e
d
u
ct
io
n
w
it
h
c
o
m
p
etit
iv
e
a
d
v
a
n
ta
g
e
[
4
1
]
,
b
u
t
att
r
ac
ti
n
g
a
n
d
r
e
tai
n
i
n
g
tal
en
t
r
e
m
ai
n
s
c
h
al
le
n
g
i
n
g
a
n
d
af
f
e
c
ts
o
p
er
ati
o
n
al
e
f
f
ic
ie
n
c
y
.
G
o
u
d
a
a
n
d
T
iwa
r
i
[
4
2
]
em
p
h
asized
th
at
talen
t
ag
ilit
y
an
d
i
n
n
o
v
atio
n
ar
e
cr
u
cial
f
o
r
f
ir
m
s
tr
an
s
itio
n
in
g
f
r
o
m
I
n
d
u
s
tr
y
3
.
0
to
4
.
0
.
In
ea
r
ly
2
0
0
0
s
,
talen
t
ag
ilit
y
lin
k
ed
to
p
s
y
ch
o
l
o
g
ical
em
p
o
wer
m
en
t,
th
o
u
g
h
its
en
ab
ler
s
r
em
ain
lim
ited
.
I
n
n
o
v
atio
n
ad
o
p
tio
n
d
ep
e
n
d
s
on
e
m
p
lo
y
ee
s
’
ac
ce
p
tan
ce
an
d
u
s
ag
e
of
n
ew
tech
n
o
lo
g
ies,
in
v
o
lv
es
em
p
lo
y
ee
s
attitu
d
e
f
o
r
m
atio
n
,
d
ec
is
io
n
m
ak
in
g
,
a
n
d
co
r
r
ec
tiv
e
ac
tio
n
s
f
o
r
s
u
cc
ess
f
u
l
im
p
lem
en
tatio
n
.
Hu
tch
in
s
o
n
[
4
3
]
in
tr
o
d
u
ce
d
‘
s
elf
-
in
n
o
v
atin
g
ar
tific
ial
in
tellig
en
ce
(
SAI
)
d
e
f
i
n
ed
as
o
r
g
an
izatio
n
al
u
tili
za
tio
n
of
AI
to
ad
v
an
ce
Evaluation Warning : The document was created with Spire.PDF for Python.
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ex
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tin
g
or
d
ev
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p
in
g
n
ew
c
o
m
p
lex
p
r
o
d
u
cts.
T
h
e
co
m
p
le
x
ity
of
AI
in
n
o
v
atio
n
lead
s
to
tech
n
ical
s
etb
ac
k
s
,
ex
ten
d
ed
tim
elin
es,
a
n
d
in
c
r
ea
s
ed
r
eso
u
r
ce
co
n
s
u
m
p
tio
n
,
lead
in
g
VC
in
v
esto
r
s
to
cl
o
s
ely
ass
ess
tea
m
m
an
ag
em
en
t,
tech
n
o
l
o
g
ical
ac
ce
p
tan
ce
,
an
d
m
ar
k
et
v
iab
ilit
y
of
s
tar
t
-
up
i
n
n
o
v
atio
n
[
3
2
]
.
4
.
1
.
6
.
Reg
ula
t
o
r
y
a
nd
leg
a
l
r
is
k
s
It
in
v
o
l
v
es
ad
v
e
r
s
e
ch
an
g
es
in
laws
an
d
r
e
g
u
latio
n
s
th
at
im
p
o
s
e
ad
d
itio
n
al
c
o
s
ts
or
r
estrict
o
p
er
atio
n
s
,
a
r
is
in
g
f
r
o
m
u
n
ce
r
tain
ties
in
r
eg
u
lato
r
y
f
r
am
ew
o
r
k
s
,
leg
al
r
e
q
u
ir
em
e
n
ts
,
an
d
in
d
u
s
tr
y
s
tan
d
ar
d
s
[
6
]
.
AI
s
tar
t
-
u
p
s
o
p
e
r
ate
with
i
n
co
m
p
lex
r
eg
u
lato
r
y
en
v
ir
o
n
m
en
ts
,
wh
er
e
ev
o
lv
i
n
g
r
eg
u
la
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eq
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ith
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ac
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n
tab
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,
an
d
eth
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u
s
e
p
r
in
cip
les
[
4
8
]
,
[
1
3
]
.
C
r
o
c
k
ett
et
a
l.
[
4
4
]
d
is
cu
s
s
ed
EU
R
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u
lato
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Fra
m
ewo
r
k
on
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r
r
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k
lev
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)
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ups
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3
3
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[
4
5
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.
4
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1
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3
0
]
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As
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[
1
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,
th
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a
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s
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ce
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p
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4
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SLR
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A
I
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T
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2.
Fre
q
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of
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s
in
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R
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N
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mb
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Ris
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Acc
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to
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u
[
4
9
]
,
alth
o
u
g
h
g
lo
b
al
VC
s
h
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s
u
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tan
tial
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Desp
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AI
tech
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tar
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ups
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if
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I
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2
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Seed
a
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tin
g
in
f
r
as
tr
u
ctu
r
e,
in
cr
ea
s
in
g
th
e
lik
eli
h
o
o
d
o
f
tech
n
ical
f
ailu
r
e
[
3
6
]
.
T
h
ese
tech
n
ical
co
n
ce
r
n
s
a
r
e
p
ar
ticu
lar
ly
cr
iti
ca
l
in
AI
s
tar
t
-
u
p
s
b
ec
au
s
e
M
L
m
o
d
els
ty
p
ically
r
eq
u
ir
e
s
u
b
s
tan
tial
h
ig
h
-
q
u
ality
tr
ain
in
g
d
ata
an
d
co
m
p
u
ta
tio
n
al
p
o
wer
r
eso
u
r
ce
s
th
at
ea
r
ly
-
s
tag
e
s
tar
t
-
u
p
s
m
ay
n
o
t
y
et
p
o
s
s
ess
.
E
ar
ly
-
s
tag
e
s
tar
t
-
u
p
s
r
em
ain
in
ex
p
er
im
en
tatio
n
an
d
R
&
D
p
h
ases
,
wh
er
e
u
n
ce
r
tain
ty
ar
o
u
n
d
AI
al
g
o
r
ith
m
f
ea
s
ib
i
lity
,
ex
p
lain
ab
ilit
y
,
an
d
eth
i
ca
l
am
b
ig
u
ity
ca
n
d
elay
p
r
o
d
u
ct
d
ev
elo
p
m
en
t
co
m
m
er
cializa
tio
n
.
T
h
ese
s
tag
e
-
s
p
ec
if
ic
r
is
k
s
co
llectiv
ely
cr
ea
te
a
h
i
g
h
-
r
is
k
i
n
v
estme
n
t
en
v
ir
o
n
m
en
t
f
o
r
VC
s
.
Fin
an
cial
r
is
k
is
s
ig
n
if
ican
t
at
th
e
ea
r
ly
s
tag
e
as
s
ta
r
t
-
u
p
s
lack
s
tab
le
r
ev
en
u
es
a
n
d
r
ely
o
n
e
x
ter
n
al
ca
p
ital,
with
h
ig
h
b
u
r
n
r
ates a
n
d
ca
p
ital
-
in
ten
s
iv
e
AI
d
ev
el
o
p
m
en
t c
y
cles in
cr
ea
s
in
g
u
n
ce
r
tain
ty
[
3
8
]
,
[
3
9
]
.
At
th
e
ea
r
ly
s
tag
e,
with
b
u
s
in
ess
m
o
d
els
s
till
f
o
r
m
in
g
,
an
d
u
n
cl
ea
r
m
o
n
etiza
tio
n
s
tr
ateg
ies,
lack
of
liq
u
id
ity
,
an
d
v
alu
atio
n
u
n
ce
r
tain
ty
f
u
r
t
h
er
in
cr
ea
s
e
r
is
k
s
f
o
r
VC
s
[
6
]
.
Op
er
atio
n
al
r
is
k
s
em
er
g
e
f
r
o
m
lim
ited
h
u
m
an
r
eso
u
r
ce
s
[
5
0
]
,
lac
k
of
in
ter
n
al
co
n
tr
o
ls
a
n
d
ea
r
ly
-
s
tag
e
f
o
u
n
d
e
r
s
’
in
ex
p
er
ien
ce
in
m
a
n
ag
in
g
g
r
o
wth
an
d
attr
ac
tin
g
k
e
y
talen
t
[
3
0
]
.
Ma
r
k
et
r
is
k
s
in
cl
u
d
e
u
n
clea
r
cu
s
to
m
er
d
em
an
d
,
u
n
d
ef
i
n
ed
m
a
r
k
et
s
eg
m
en
ts
a
n
d
f
ast
-
ch
an
g
in
g
e
x
ter
n
al
en
v
ir
o
n
m
en
ts
th
at
m
ay
r
en
d
er
ea
r
ly
ass
u
m
p
tio
n
s
in
v
alid
[
2
9
]
,
[
3
8
]
.
E
ar
ly
-
s
tag
e
s
tar
t
-
ups
o
p
er
ate
on
h
y
p
o
t
h
eses
r
ath
er
th
an
v
alid
ated
m
a
r
k
et
ev
id
en
ce
,
m
ak
in
g
VC
s
r
ely
on
f
o
u
n
d
in
g
team
’
s
v
is
io
n
an
d
ag
ilit
y
.
E
x
it
co
n
ce
r
n
s
lik
e
s
ca
lab
ilit
y
,
r
ea
d
in
ess
f
o
r
ac
q
u
is
itio
n
an
d
I
PO
ar
e
s
ec
o
n
d
ar
y
to
ev
alu
atin
g
p
r
o
d
u
ct
v
iab
ilit
y
an
d
m
ar
k
et
f
i
t
in
th
e
in
itial
p
h
ase.
4
.
2
.
2
.
G
ro
wt
h
s
t
a
g
e
At
th
is
s
tag
e,
s
tar
t
-
ups
ty
p
ically
ex
p
er
ie
n
ce
r
ap
i
d
ex
p
a
n
s
io
n
,
in
cr
ea
s
ed
f
u
n
d
in
g
r
o
u
n
d
s
an
d
b
r
o
a
d
er
m
ar
k
et
en
tr
y
wh
ile
f
ac
in
g
ev
o
lv
in
g
r
is
k
s
as
th
ey
tr
an
s
itio
n
f
r
o
m
ea
r
ly
-
s
tag
e
ex
p
e
r
im
en
t
atio
n
to
o
p
er
atio
n
al
ex
ec
u
tio
n
an
d
m
ar
k
et
co
n
s
o
lid
atio
n
.
T
e
ch
n
o
l
o
g
ical
r
is
k
s
m
ay
less
en
,
b
u
t
AI
m
o
d
el
ex
p
l
ain
ab
ilit
y
,
b
ias,
a
n
d
p
r
iv
ac
y
r
em
ain
cr
itical
a
n
d
r
e
g
u
lato
r
y
co
n
ce
r
n
s
,
p
ar
ticu
lar
l
y
in
co
n
te
x
ts
of
f
r
a
m
ewo
r
k
li
k
e
GDPR
[
3
3
]
,
[
4
0
]
.
Fin
an
cial
r
is
k
s
at
th
is
s
tag
e
in
v
o
lv
e
ca
s
h
f
lo
w
v
o
latilit
y
,
r
ev
en
u
e
p
r
e
d
ictab
ilit
y
,
an
d
p
r
ess
u
r
e
to
m
ee
t
p
er
f
o
r
m
an
ce
m
iles
to
n
es,
in
ten
s
if
ied
b
y
in
v
esto
r
ex
p
ec
tatio
n
s
an
d
s
ca
le
-
u
p
co
s
ts
[
1
8
]
,
[
2
0
]
,
[
3
2
]
.
T
h
is
s
tag
e
r
ef
lects
a
s
h
if
t
f
r
o
m
s
ec
u
r
in
g
f
u
n
d
in
g
to
d
em
o
n
s
tr
atin
g
f
in
an
cial
s
u
s
tain
ab
ilit
y
an
d
ju
s
tify
in
g
in
cr
ea
s
ed
v
alu
atio
n
s
.
Op
er
atio
n
al
r
is
k
s
in
ten
s
if
y
as
s
tar
t
-
ups
f
ac
e
o
r
g
an
izatio
n
al
c
o
m
p
lex
ity
,
th
e
n
ee
d
f
o
r
s
ca
lab
le
in
f
r
astru
ctu
r
e
an
d
s
er
v
ice
d
eliv
er
y
,
f
o
r
m
alize
d
p
r
o
ce
s
s
es,
h
i
r
in
g
,
an
d
s
y
s
tem
s
in
teg
r
atio
n
[
3
0
]
.
Ma
r
k
et
r
is
k
s
s
h
if
t
f
r
o
m
p
r
o
d
u
ct
-
m
a
r
k
et
f
it
to
war
d
co
m
p
etitiv
e
p
o
s
itio
n
in
g
,
c
h
an
g
in
g
cu
s
to
m
e
r
p
r
ef
er
e
n
ce
s
,
an
d
m
ac
r
o
ec
o
n
o
m
ic
in
f
lu
en
ce
s
in
a
m
o
r
e
s
atu
r
ated
m
a
r
k
et
[
3
2
]
.
Alo
n
g
with
th
is
c
y
b
er
s
ec
u
r
ity
[
3
3
]
an
d
co
m
p
lian
ce
r
is
k
s
g
r
o
w
with
in
cr
ea
s
ed
d
ata
an
d
cu
s
to
m
er
in
ter
ac
tio
n
s
m
an
ag
ed
d
u
r
in
g
s
ca
le
-
up
[
3
2
]
,
p
ar
ticu
lar
ly
with
u
s
er
-
f
ac
in
g
AI
ap
p
licatio
n
s
.
VC
s
f
o
cu
s
on
s
ca
lab
ilit
y
,
g
o
v
er
n
an
ce
,
a
n
d
s
u
s
tain
ab
le
g
r
o
wth
,
en
s
u
r
in
g
p
o
r
tf
o
li
o
co
m
p
an
ies
r
em
ain
o
p
e
r
atio
n
ally
s
tr
o
n
g
an
d
co
m
p
lain
t
[
3
7
]
,
wh
ile
m
ain
t
ain
in
g
in
n
o
v
atio
n
.
4
.
2
.
3
.
M
a
t
urit
y
/
la
t
er
s
t
a
g
e
In
th
e
m
atu
r
ity
s
tag
e,
r
is
k
s
i
n
cr
ea
s
e
due
to
i
n
cr
ea
s
ed
p
r
e
s
s
u
r
e
to
s
ca
le
o
p
e
r
atio
n
s
,
m
e
et
r
ev
en
u
e
ex
p
ec
tatio
n
s
an
d
p
r
ep
ar
e
f
o
r
e
x
it
s
u
ch
as
ac
q
u
is
itio
n
an
d
I
PO
[
4
7
]
.
R
eg
u
lato
r
y
an
d
leg
al
r
is
k
s
in
ten
s
if
y
with
g
r
ea
ter
m
a
r
k
et
v
is
ib
ilit
y
,
r
eq
u
ir
in
g
co
m
p
lian
ce
with
d
ata
g
o
v
er
n
an
ce
,
cy
b
er
s
ec
u
r
ity
,
IP
l
aws
[
3
5
]
.
Failu
r
e
to
co
m
p
ly
with
em
er
g
in
g
AI
r
eg
u
latio
n
s
s
u
ch
as
E
u
r
o
p
ea
n
Un
io
n
(
E
U)
AI
Act
[
4
4
]
a
n
d
t
h
e
GDPR
,
an
d
eth
ical
co
n
ce
r
n
s
lik
e
alg
o
r
ith
m
ic
b
ia
s
,
d
ata
p
r
iv
ac
y
,
an
d
f
air
n
ess
in
au
to
m
ated
d
ec
is
io
n
-
m
ak
i
n
g
s
y
s
tem
s
[
1
3
]
,
[
3
3
]
also
in
clu
d
ed
as
r
eg
u
lato
r
y
a
n
d
leg
al
co
n
ce
r
n
s
at
th
is
s
tag
e.
L
eg
al
u
n
ce
r
tain
ties
ar
o
u
n
d
cr
o
s
s
-
b
o
r
d
er
d
ata
f
lo
ws
an
d
AI
ac
co
u
n
tab
ilit
y
f
u
r
th
er
co
m
p
licate
g
lo
b
al
ex
p
an
s
io
n
an
d
im
p
ac
t
in
v
esto
r
c
o
n
f
id
en
ce
a
n
d
ex
it
v
alu
atio
n
s
[
3
3
]
,
[
4
0
]
.
E
x
it
r
el
ated
r
is
k
s
b
ec
o
m
e
m
o
r
e
p
r
o
m
in
en
t
in
th
e
m
at
u
r
ity
p
h
ase
as
in
v
esto
r
s
ev
alu
ate
th
e
r
etu
r
n
f
ea
s
ib
ilit
y
,
with
liq
u
id
ity
co
n
s
tr
ain
ts
,
an
d
ex
ten
d
ed
tim
elin
es
to
r
ea
ch
p
r
o
f
ita
b
ilit
y
can
d
elay
ex
it
o
p
p
o
r
tu
n
ities
[
6
]
,
[
3
0
]
.
T
ec
h
n
o
lo
g
ical
o
b
s
o
lescen
ce
f
u
r
th
er
co
m
p
licates
ex
it
s
tr
ateg
ies
with
ef
f
icien
t
AI
m
o
d
els
r
en
d
er
e
x
is
tin
g
s
o
lu
ti
o
n
s
o
u
td
ated
[
4
7
]
.
Op
er
atio
n
al
r
is
k
s
with
s
ca
lin
g
ch
allen
g
es
an
d
p
a
r
tn
er
s
h
ip
d
ep
en
d
e
n
cies,
r
elian
ce
on
clo
u
d
in
f
r
astru
ctu
r
e,
t
h
ir
d
-
p
ar
ty
d
ata
p
r
o
v
id
er
s
,
an
d
s
tr
ateg
ic
allian
ce
s
in
cr
ea
s
es
[
3
2
]
,
in
tr
o
d
u
cin
g
n
ew
v
u
l
n
er
a
b
ilit
ies
if
th
ese
r
elatio
n
s
h
ip
s
a
r
e
m
is
m
an
ag
e
d
or
f
ail
to
d
eli
v
er
ex
p
ec
ted
v
alu
e.
Op
er
atio
n
al
c
o
m
p
lex
ity
g
r
o
ws
with
lar
g
er
c
u
s
to
m
er
b
ases
an
d
m
u
ltip
le
g
eo
g
r
ap
h
ies,
d
em
a
n
d
a
h
ig
h
d
eg
r
ee
of
co
o
r
d
in
atio
n
a
n
d
r
eso
u
r
ce
allo
ca
tio
n
[
5
1
]
to
b
alan
ce
g
r
o
wth
an
d
co
s
t
ef
f
icien
cy
.
Fin
an
cial
r
is
k
s
s
u
ch
as
ca
s
h
f
lo
w
in
s
tab
ilit
y
,
u
n
b
alan
ce
d
b
u
r
n
r
ates,
a
n
d
s
ca
r
e
ex
ter
n
a
l
f
u
n
d
in
g
r
em
ain
cr
itical
d
u
r
i
n
g
m
ac
r
o
ec
o
n
o
m
ic
s
h
if
ts
[
3
2
]
.
T
h
e
lo
n
g
g
estatio
n
al
o
f
AI
i
n
n
o
v
atio
n
a
n
d
p
r
ess
u
r
e
f
o
r
s
u
s
tain
ab
le
p
r
o
f
itab
ilit
y
in
ten
s
if
y
i
n
v
esto
r
co
n
ce
r
n
s
a
n
d
d
elay
f
in
a
n
cial
r
etu
r
n
s
[
1
8
]
,
[
2
0
]
.
VC
s
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