Implementation of seamless assistance with Google Assistant leveraging cloud computing
Jiaxin Huang,
No information about this author
Yifan Zhang,
No information about this author
Jingyu Xu
No information about this author
et al.
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.
Language: Английский
Practical applications of advanced cloud services and generative AI systems in medical image analysis
Jingyu Xu,
No information about this author
Binbin Wu,
No information about this author
Jiaxin Huang
No information about this author
et al.
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
64(1), P. 82 - 87
Published: May 14, 2024
The
medical
field
is
one
of
the
important
fields
in
application
artificial
intelligence
technology.
With
explosive
growth
and
diversification
data,
as
well
continuous
improvement
needs
challenges,
technology
playing
an
increasingly
role
field.
Artificial
technologies
represented
by
computer
vision,
natural
language
processing,
machine
learning
have
been
widely
penetrated
into
diverse
scenarios
such
imaging,
health
management,
information,
drug
research
development,
become
driving
force
for
improving
level
quality
services.
article
explores
transformative
potential
generative
AI
emphasizing
its
ability
to
generate
synthetic
enhance
images,
aid
anomaly
detection,
facilitate
image-to-image
translation.
Despite
challenges
like
model
complexity,
applications
models
healthcare,
including
Med-PaLM
2
technology,
show
promising
results.
By
addressing
limitations
dataset
size
diversity,
these
contribute
more
accurate
diagnoses
improved
patient
outcomes.
However,
ethical
considerations
collaboration
among
stakeholders
are
essential
responsible
implementation.
Through
experiments
leveraging
GANs
augment
brain
tumor
MRI
datasets,
study
demonstrates
how
can
image
ultimately
advancing
diagnostics
care.
Language: Английский
Integration of computer networks and artificial neural networks for an AI-based network operator
Binbin Wu,
No information about this author
Jingyu Xu,
No information about this author
Yifan Zhang
No information about this author
et al.
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
64(1), P. 115 - 120
Published: May 14, 2024
This
paper
proposes
an
integrated
approach
combining
computer
networks
and
artificial
neural
to
construct
intelligent
network
operator,
functioning
as
AI
model.
State
information
from
is
transformed
into
embedded
vectors,
enabling
the
operator
efficiently
recognize
different
pieces
of
accurately
output
appropriate
operations
for
at
each
step.
The
has
undergone
comprehensive
testing,
achieving
a
100%
accuracy
rate,
thus
eliminating
operational
risks.
Additionally,
simple
simulator
created
encapsulated
training
testing
environment
components,
automation
data
collection,
training,
processes.
abstract
outline
core
contributions
while
highlighting
innovative
methodology
employed
in
development
validation
AI-based
operator.
Language: Английский
Intelligent robotic control system based on computer vision technology
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
64(1), P. 142 - 147
Published: May 14, 2024
Computer
vision
is
a
kind
of
simulation
biological
using
computers
and
related
equipment.
It
an
important
part
the
field
artificial
intelligence.
Its
research
goal
to
make
have
ability
recognize
three-dimensional
environmental
information
through
two-dimensional
images.
based
on
image
processing
technology,
signal
probability
statistical
analysis,
computational
geometry,
neural
network,
machine
learning
theory
computer
analysis
visual
information.The
article
explores
intersection
technology
robotic
control,
highlighting
its
importance
in
various
fields
such
as
industrial
automation,
healthcare,
protection.
which
simulates
human
observation,
plays
crucial
role
enabling
robots
perceive
understand
their
surroundings,
leading
advancements
tasks
like
autonomous
navigation,
object
recognition,
waste
management.
By
integrating
with
robot
gain
interact
intelligently
environment,
improving
efficiency,
quality,
sustainability.
The
also
discusses
methodologies
for
developing
intelligent
garbage
sorting
robots,
emphasizing
application
feature
extraction,
reinforcement
techniques.
Overall,
integration
control
holds
promise
enhancing
human-computer
interaction,
manufacturing,
protection
efforts.
Language: Английский
Optimizing Human–Machine Collaboration in NLP for Enhanced Content Generation and Decision-Making
Priyanka V. Deshmukh,
No information about this author
Aniket K. Shahade
No information about this author
Lecture notes in networks and systems,
Journal Year:
2025,
Volume and Issue:
unknown, P. 179 - 187
Published: Jan. 1, 2025
Language: Английский
Agent Centric Operating System – A Comprehensive Review and Outlook for Operating System
Published: Dec. 18, 2024
The
operating
system
(OS)
is
the
backbone
of
modern
computing,
providing
essential
services
and
managing
resources
for
computer
hardware
software.
This
review
paper
offers
an
in-depth
analysis
systems’
evolution,
current
state,
prospects.
We
begin
with
overview
concept
significance
systems
in
digital
era.
In
second
section,
we
delve
into
existing
released
systems,
examining
their
architectures,
functionalities,
ecosystems
they
support.
then
explore
recent
advances
OS
highlighting
innovations
real-time
processing,
distributed
security.
third
section
focuses
on
new
era
discussing
emerging
trends
like
Internet
Things
(IoT),
cloud
artificial
intelligence
(AI)
integration.
also
consider
challenges
opportunities
presented
by
these
developments.
concludes
a
synthesis
landscape
forward-looking
discussion
future
trajectories
including
open
issues
areas
ripe
further
research
innovation.
Finally,
put
forward
architecture.
Language: Английский