Enhanced Data Processing: Key to AI Innovation Across Industries

Accelerated
data
processing
is
becoming
a
cornerstone
of
AI
innovation
across
various
industries,
from
finance
and
telecommunications
to
biomedical
research
and
automotive
development,
according
to
NVIDIA
Blog.

Finance
Organizations
Detect
Fraud
in
a
Fraction
of
a
Second

Financial
institutions
face
a
significant
challenge
in
analyzing
vast
amounts
of
transactional
data
to
detect
fraud
quickly.
Organizations
like
American
Express
leverage
accelerated
computing
to
train
and
deploy
long
short-term
memory
(LSTM)
models,
enabling
real-time
fraud
detection
with
minimal
latency.
This
approach
has
improved
fraud
detection
accuracy
by
up
to
6%
in
specific
segments
and
reduced
cloud
costs
significantly.

Telcos
Simplify
Complex
Routing
Operations

Telecommunications
providers
generate
immense
data
volumes
daily,
necessitating
complex
routing
operations
to
ensure
service
delivery.
AT&T
employs
NVIDIA
cuOpt
and
RAPIDS
to
optimize
technician
dispatch,
reducing
cloud
costs
by
90%
and
boosting
operational
efficiency.
This
integration
has
enhanced
everything
from
AI
model
training
to
network
quality
maintenance.

Biomedical
Researchers
Condense
Drug
Discovery
Timelines

Biomedical
researchers
face
challenges
in
managing
the
vast
amount
of
medical
data
for
drug
discovery.
AstraZeneca’s
Biological
Insights
Knowledge
Graph
(BIKG)
uses
NVIDIA
RAPIDS
to
significantly
speed
up
gene
ranking
processes,
reducing
months-long
tasks
to
seconds
and
accelerating
the
development
of
novel
disease
treatments.

Utility
Companies
Build
the
Future
of
Clean
Energy

As
the
energy
sector
shifts
towards
carbon-neutral
sources,
managing
diverse
energy
inputs
has
become
more
data-intensive.
Utilidata,
in
collaboration
with
NVIDIA,
developed
the
Karman
platform
to
transform
electricity
meters
into
data
collection
and
control
points.
This
enables
real-time
analysis
and
seamless
integration
of
distributed
energy
resources,
optimizing
grid
management
for
a
cleaner
energy
future.

Automakers
Enable
Safer,
More
Accessible,
Self-Driving
Vehicles

For
autonomous
vehicles,
real-time
data
processing
is
crucial
for
safety.
Electric
vehicle
manufacturer
NIO
uses
NVIDIA
Triton
Inference
Server
to
reduce
latency
and
enhance
data
throughput,
facilitating
faster
and
safer
navigation
decisions.
This
GPU-centric
approach
also
simplifies
AI
model
updates,
improving
overall
system
performance.

Retailers
Improve
Demand
Forecasting

In
retail,
quick
data
processing
is
essential
for
accurate
demand
forecasting.
Walmart
leverages
NVIDIA
GPUs
and
RAPIDS
to
enhance
forecasting
accuracy
across
millions
of
items,
reducing
waste
and
optimizing
inventory.
This
shift
has
improved
forecast
accuracy
from
94%
to
97%
and
significantly
cut
down
on
operational
costs
and
environmental
impact.

Public
Sector
Improves
Disaster
Preparedness

Public
and
private
organizations
use
aerial
imagery
for
various
applications,
including
disaster
management.
NVIDIA,
in
collaboration
with
Booz
Allen,
developed
a
solution
using
computer
vision
algorithms
to
process
large
datasets
quickly.
This
innovation
enables
faster
response
times
and
better
planning
for
emergencies,
potentially
saving
lives.

Accelerate
AI
Initiatives
and
Deliver
Business
Results

Enterprises
utilizing
accelerated
computing
for
data
processing
are
better
positioned
to
innovate
and
achieve
higher
performance
levels.
This
technology
enables
the
efficient
handling
of
large
datasets,
faster
model
training,
and
more
precise
AI
solutions,
offering
superior
price-performance
ratios
compared
to
traditional
systems.

Learn
more
about
how

accelerated
computing
helps
organizations
achieve
AI
objectives
and
drive
innovation.

Image
source:
Shutterstock

.
.
.

Tags