Weekly insights into the new computing modelDEEP LEARNING TOP 5Feb 20th, 2017

Exploring the Momentum:The Intersection of AI and

HPC

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

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

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

(i)Scale of Data(ii)Scale of

ComputationIt 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:

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.

BRINGING US TO THE INTERSECTION OF AI AND HPC

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.

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.

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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

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

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• 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 diseaseIcahn 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

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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

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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.

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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.

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The timeline of successes with HPC and AI across industries.

DOWNLOAD THE FULL REPORT ON HOW AI IS INTERSECTING WITH HPC:

insideBIGDATA Guide