Learn how the intersection of AI and HPC are advancing deep learning solutions for enterprises and research institutions around the world,

1. Weekly insights into the new computing model
DEEP LEARNING TOP 5
Feb 20th, 2017
Exploring the Momentum:
The Intersection of AI and HPC

2. AI-BASED TOOLS ARE NOW POURING INTO THE
MAINSTREAM MARKETPLACE.

3. MANY OF THE LARGEST BRANDS ARE FULLY
COMMITTED TO DEVELOPING AI SOLUTIONS IN
THEIR PRODUCTS.

4. THE BIGGEST QUESTIONS SURROUNDING THIS
NEW-FOUND MOMENTUM IS “WHY NOW?”

5. (i)Scale of Data
(ii)Scale of Computation
It was only recently, that
technologists have figured out
how to scale computation to
build deep learning algorithms
that can take effective
advantage of voluminous
amounts of data.
Image Source: GE Report
The answer centers
around two key points:

6. The answer centers
around two key points:
(i) Scale of Data
(ii)Scale of Computation
Today, computers have
become fast enough to
run large-scale neural
networks.
With the adoption of GPUs, neural
network developers can now run deep
learning with compute power required
to bring AI to life quickly.

7. BRINGING US TO THE INTERSECTION
OF AI AND HPC

8. How is HPC speeding
up AI research?
Baidu Chief Scientist Andrew Ng
indicated that much progress in AI is
driven by running experiments. HPC
enables researchers to be more
productive by letting them iterate
experiments. Instead of weeks,
months, or even years to complete an
experiment, the time can be reduced
to days.

9. For example, the use of AI for speech recognition shows that using
10x more data can lower relative error rates by 40%. HPC allows
training models on ever larger data sets, and is therefore a key part
of progress in AI.
Image Source

10. A RECENT SURVEY DONE ABOUT HPC
INTERSECTION WITH AI SHOWED …
1. 28% of respondents felt that HPC technologies will allow
them to scale computationally to build deep learning
algorithms and take advantage of big data
2. 25% felt that HPC will enable training of deep neural
networks
3. 24% felt that HPC translates into machine learning progress
Source: InsideBIGDATA Guide to Deep Learning & Artificial Intelligence

11. LEARN MORE
This intersection of AI and
HPC is showing that cognition
can be computable in
practical ways for real-world
applications
It is now an area of intense activity in
commercial, industrial, government, and
academic settings.
Image Source

12. • AI platform to accelerate cancer research
To speed advances against cancer, the Cancer
Moonshot initiative is utilizing the NVIDIA DGX
SATURNV and AI framework CANDLE.
• Accelerating drug discoveries with AI
BenevolentAI is using GPU deep learning to
bring new therapies to market quickly and more
affordably by using the DGX-1 AI supercomputer.
• AI predicts and prevents disease
Icahn School of Medicine built an AI-powered
tool “Deep Patient” that can analyze a patient’s
medical history to predict 80 diseases up to one
year prior onset.
AI Healthcare with GPUs
Image Source

13. AI Weather Forecasting
• Colorful Clouds is using GPU
computing and AI to process,
predict, and communicate weather
through a new forecasting tool. It
provides individual location based
real-time forecasts with extreme
accuracy.
• MeteoSwiss is the first major
national weather service to deploy
a GPU-accelerated supercomputer
to improve its daily weather
forecast
Learn More
Image Source

14. AI-Backed Cyber Defense
• Accenture’s cyber security lab
uses GPUs, CUDA, and machine
learning to accelerate the analysis
and visualization of 200M – 300M
alerts daily so analysts can take
timely action.
Image Source

15. Defending the Planet with AI
• The NASA Frontier Development Lab is
employing GPU powered AI & Deep
Learning to identify threats and their
unique characteristics. The resulting
product “Deflector Selector” achieved a
98% success rate in determining which
technology produced the most
successful deflection.
Image Source

16. The timeline of
successes with HPC
and AI across
industries.

17. DOWNLOAD THE FULL REPORT ON
HOW AI IS INTERSECTING WITH HPC:
insideBIGDATA Guide