Advances in logistics, operations, and management science book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 35 - 60
Published: Aug. 29, 2024
The
aim
of
this
research
is
twofold:
1)
to
explore
the
potential
applications
artificial
intelligence
(AI)
and
generative
pre-trained
transformer
(GPT)
models
in
healthcare
and,
2)
identify
challenges
associated
with
integrating
these
technologies
into
clinical
practice.
AI
GPT
have
attracted
significant
attention
within
industry
due
their
revolutionize
medical
practices.
Potential
include
early
disease
detection
through
analysis
images
or
electronic
health
records,
personalized
treatment
recommendations
based
on
patient
data
analysis,
improved
efficiency
automating
routine
administrative
tasks.
These
employ
advanced
deep-learning
algorithms
analyze
extensive
volumes
data,
interpret
images,
provide
diagnostic
suggestions.
As
a
result,
professionals
can
make
well-informed
decisions
enhance
outcomes.
In
addition,
support
remote
monitoring,
care,
triaging,
thereby
improving
accessibility
services.
Nevertheless,
widespread
adoption
faces
several
limitations.
require
high-quality
must
address
issues
related
privacy,
biased
algorithms,
regulatory
frameworks.
Moreover,
ethical
considerations,
including
safeguarding
ensuring
algorithmic
accountability,
avoiding
biases,
be
diligently
addressed
when
implementing
settings.
This
study
as
they
relate
healthcare,
goal
encouraging
future
developments
field.
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
64(1), P. 169 - 175
Published: May 14, 2024
AI
and
cloud
native
are
mutually
reinforcing
inseparable.
Due
to
the
huge
storage
computing
power
requirements,
most
applications
need
support,
especially
large
model
If
has
influenced
software
industry
a
considerable
extent
in
past
few
years,
big
boom
means
that
become
standard
option
for
developers.This
paper
describes
rise
of
their
integration
with
traditional
development
workflows,
pointing
out
challenges
enterprises
developers
face
when
integrating
models.
With
cloud-native
technologies,
combination
artificial
intelligence
is
becoming
increasingly
important.
Cloud-native
technologies
provide
infrastructure
needed
build
run
resilient
scalable
applications,
while
distributed
supports
multi-cloud
integration,
enabling
unified
foundation
"one
cloud,
multiple
computing."
As
an
intelligent
voice
Assistant,
Google
Assistant
achieves
more
intelligent,
convenient
efficient
user
experience
through
smart
home
control,
enterprise
customer
service
healthcare.
Finally,
this
points
advantages
combining
computing,
providing
convenient,
experience.
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
64(1), P. 155 - 161
Published: May 14, 2024
This
study
provides
an
in-depth
analysis
of
the
model
architecture
and
key
technologies
generative
artificial
intelligence,
combined
with
specific
application
cases,
uses
conditional
adversarial
networks
(
cGAN
)
time
series
methods
to
simulate
predict
dynamic
changes
in
financial
markets.
The
research
results
show
that
can
effectively
capture
complexity
market
data,
deviation
between
prediction
actual
performance
is
minimal,
showing
a
high
degree
accuracy.
Through
investment
return
analysis,
value
predictions
strategies
confirmed,
providing
investors
new
ways
improve
decision-making
process.
In
addition,
evaluation
stability
reliability
also
shows
although
there
are
still
challenges
responding
emergencies,
overall,
GAI
technology
has
shown
great
potential
field
prediction.
conclusion
points
out
integrating
intelligence
into
forecasts
not
only
accuracy
forecasts,
but
provide
powerful
data
support
for
decisions,
helping
make
more
informed
decisions
complex
ever-changing
environment.
choose.
Journal of Theory and Practice of Engineering Science,
Journal Year:
2024,
Volume and Issue:
4(05), P. 1 - 8
Published: May 14, 2024
With
the
rapid
development
of
artificial
intelligence
and
robot
technology,
SLAM
as
a
key
component,
has
been
paid
more
attention.
technology
enables
robots
to
autonomously
navigate,
build
maps,
achieve
accurate
positioning
in
unknown
environments,
providing
strong
support
for
autonomy
unmanned
vehicles.
In
this
paper,
position
prediction
method
flying
object
based
on
application
EvolveGCN
model
behavior
are
introduced.
First,
through
fusion
liDAR
data,
we
can
accurately
predict
movement
trajectory
objects,
thereby
improving
safety
efficiency
system.
Secondly,
with
model,
able
capture
dynamic
changes
environment
predictions
objects.
Through
experimental
verification,
accuracy
our
significantly
improved
both
simulation
real
environment,
which
indicates
feasibility
effectiveness
practical
application,
provides
an
important
reference
technical
autonomous
navigation,
aerial
surveillance
other
fields.
Journal of improved oil and gas recovery technology.,
Journal Year:
2024,
Volume and Issue:
7(3), P. 15 - 22
Published: May 15, 2024
This
article
reviews
the
key
role
of
distributed
cloud
architecture
in
autonomous
driving
systems
and
its
integration
with
intelligent
computing
networks.
By
spreading
resources
across
multiple
geographic
locations,
enables
localized
processing
storage
data,
reducing
latency
improving
real-time
decision
making
vehicles.
The
points
out
that
combination
technology
network
provides
a
powerful
solution
to
meet
challenges
technology.
dynamically
allocating
deeply
integrating
cloud,
network,
chip
technologies,
gives
enhanced
data
capabilities
ensure
stable
reliable
performance
variety
scenarios.
Finally,
paper
highlights
synergy
marks
an
important
milestone
for
transportation
systems,
heralding
accelerated
adoption
solutions
automotive
industry,
pace
innovation
transformation.
Academic Journal of Science and Technology,
Journal Year:
2024,
Volume and Issue:
11(1), P. 21 - 25
Published: May 21, 2024
This
paper
delves
into
the
utilization
of
Generative
Artificial
Intelligence
(GAI)
for
virtual
financial
advising
and
analysis
in
capital
markets.
Initially,
it
outlines
fundamental
principles
GAI
its
significance
decision-making.
Subsequently,
scrutinizes
shortcomings
conventional
advisory
models
through
a
review
literature
empirical
data.
It
then
examines
emerging
trends
benefits
intelligent
advising,
contrasting
them
with
traditional
models.
Following
this,
elucidates
practical
applications
generative
AI
finance,
encompassing
investment
guidance,
risk
evaluation,
Advances in logistics, operations, and management science book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 137 - 160
Published: July 26, 2024
Artificial
intelligence
plays
a
crucial
role
in
financial
sectors,
especially
investment
planning.
It
enhanced
or
replaced
traditional
planning
by
applying
AI
techniques
such
as
machine
learning,
natural
language
processing,
deep
and
robo-advisors.
This
chapter
presented
the
applications
of
AI-enabled
decision-making
tools
various
functional
areas
corporate
quantitative
trading
algorithms,
risk
management
systems,
portfolio
optimization
tools,
algorithmic
trading,
forecasting
prediction
securities
market,
automated
building,
data
analysis,
asset
management,
personalized
advice.
Also,
this
case
studies,
success
stories,
benefits
will
be
very
useful
for
companies
investors
to
transform
their
mode
technology-oriented
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 29, 2025
Abstract
The
use
of
artificial
intelligence
(AI)
and
intellectual
machines
can
support
businesses
in
performing
various
activities.
Therefore,
it
is
necessary
to
examine
the
performance
outcomes
by
assessing
concentration
AI
technologies.
To
create
a
quantifiable
score
concentration,
AI-related
terms
are
identified
annual
reports
all
listed
firms
U.S.
For
analysis
purposes,
fixed
effects
model
employed,
using
firms’
panel
data
from
2003
2022.
reveals
that
beneficial
for
company’s
financial
success.
Additional
examines
moderating
role
research
development
(R&D).
Firms
with
higher
R&D
spending
experience
increased
benefits
concentrating
on
uniqueness
this
study
lies
analyzing
success
through
parameters.
findings
AI,
combined
spending,
attain
greater
main
insights
suggest
management
must
evaluate
their
existing
focus
improve
position.
JEL
Classification:
F65;
G30;
O32;
P33
ACM Transactions on Management Information Systems,
Journal Year:
2025,
Volume and Issue:
16(1), P. 1 - 11
Published: Feb. 7, 2025
Large
language
models
have
been
advancing
very
rapidly
and
are
making
substantial
impacts
on
all
areas
of
business
management.
We
review
the
development
large
their
applications
in
management,
identify
major
issues
challenges
faced
by
both
practitioners
researchers.
Based
our
review,
we
propose
an
agenda
for
information
systems
researchers
discuss
some
potential
directions
future
research.
Lastly,
present
articles
special
issue
as
exemplary
research
implications.
