Taking the AI Training Wheels Off: From PoC to Production

By Eric Herzog, CMO and VP, IBM Storage Systems

June 22, 2018

Even though it seems simple now, there were a lot of skills to master in learning to ride a bike. From balancing on two wheels, and steering in a straight line, to going around corners and stopping before running over the dog, it took lots of practice to master these skills. If you were lucky enough to have training wheels, you could safely learn without falling and then ride confidently when they came off.

Organizations embarking on Artificial Intelligence (AI) projects also start with training wheels, and then progress through three stages on their journey to enterprise-scale AI. In the first stage, individual data scientists experiment and ‘practice’ on proof of concept projects. Fairly quickly, these PoCs will hit knowledge, data management and infrastructure performance obstacles that keep them from proceeding to the next stage – stabilization and production. In this stage multiple data scientists produce optimized and trained models quickly enough to deliver value to the organization. Moving to the third and final stage of AI adoption, where AI is integrated across multiple lines of business and requires enterprise-scale infrastructure, presents significant integration, security and support challenges.

Wells Fargo is a company that has successfully navigated the new world of AI as they use deep learning models to comply with a critical financial validation process.  Their data scientists build, enhance, and validate hundreds of models each day and speed is critical, as well as scalability, as they deal with greater amounts of data and more complicated models. As Richard Liu, Quantitative Analytics manager at Wells Fargo said at IBM Think, “Academically, people talk about fancy algorithms. But in real life, how efficiently the models run in distributed environments is critical.”  Wells Fargo uses IBM AI Enterprise software platform for the speed and resource scheduling and management functionality it provides. “IBM is a very good partner and we are very pleased with their solution,” added Liu.

When a large Canadian financial institution wanted to build an AI Center of Competency for 35 data scientists to help identify fraud, minimize risk, and increase customer satisfaction, they turned to IBM. By deploying the IBM Systems AI Infrastructure Reference Architecture, they now provide distributed deep learning as a service designed to enable easy-to-deploy, unique environments for each data scientist across shared resources.

When training wheels are not enough

Unlike riding a bike, moving from AI practice (PoC) to stabilization and production is not just a matter of taking off the training wheels. It requires a whole new set of skills and infrastructure to propel the organization up the AI hills and navigate AI hazards. Unfortunately, few people have the knowledge and experience needed to ride on their own without training wheels.

To help fill this knowledge and skills gap, IBM has built PowerAI Enterprise – an easy-to-use, integrated set of tools to get AI open source frameworks up and running quickly and accelerate AI adoption across an organization. These tools utilize cognitive algorithms and automation to dramatically increase the productivity of data scientists throughout the AI workflow.

Ritu Joyti, Vice President of IDC’s Cloud IaaS, Enterprise Storage and Server analyst, noted, “IBM has one of the most comprehensive AI solution stacks that includes tools and software for all the critical personas of AI deployments including the data scientists. Their solution helps reduce the complexity of AI deployments and help organizations improve productivity and efficiency, lower acquisition and support costs, and accelerate adoption of AI.”

PowerAI Enterprise is part of IBM’s tested, validated and optimized on-premises AI infrastructure reference architecture designed to help organizations jump-start AI and deep learning projects, and remove the obstacles to moving from experimentation to production and ultimately to enterprise-scale AI.

IBM AI Infrastructure Reference Architecture

Get started quickly

PowerAI Enterprise shortcuts the time to get up and running with an AI environment that supports the data scientist from data ingest and preparation, through training and optimization and finally to testing and inference. Included are fully compiled and ready-to-use IBM-optimized versions of popular open source deep learning frameworks (including TensorFlow and IBM Caffe), as well as a software framework designed to support distributed deep learning and scale to 100 and 1000 of nodes. The whole solution comes with support from IBM, including the open source frameworks.

With IBM PowerAI Enterprise and the IBM Systems AI Infrastructure Reference Architecture, data scientists can confidently take off the AI training wheels, with less focus on the infrastructure mechanics and more on the AI journey and destination.

Learn more about the IBM Systems AI Infrastructure Reference Architecture and IDC’s review of the architecture here.

IBM Resources

Follow @IBMSystems

IBM Systems on Facebook

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

How the United States Invests in Supercomputing

November 14, 2018

The CORAL supercomputers Summit and Sierra are now the world's fastest computers and are already contributing to science with early applications. Ahead of SC18, Maciej Chojnowski with ICM at the University of Warsaw discussed the details of the CORAL project with Dr. Dimitri Kusnezov from the U.S. Department of Energy. Read more…

By Maciej Chojnowski

At SC18: Humanitarianism Amid Boom Times for HPC

November 14, 2018

At SC18 in Dallas, the feeling on the ground is one of forward-looking buoyancy. Like boom times that cycle through the Texas oil fields, the HPC industry is enjoying a prosperity seen only every few decades, one driven Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, produ Read more…

By John Russell

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

New Data Management Techniques for Intelligent Simulations

The trend in high performance supercomputer design has evolved – from providing maximum compute capability for complex scalable science applications, to capacity computing utilizing efficient, cost-effective computing power for solving a small number of large problems or a large number of small problems. Read more…

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry’s first plug-and-play, portable parallel file system that delivers up to 75 Gb/s per rack on industry standard hardware combined with “enterprise-grade reliability and manageability.” Read more…

By Doug Black

How the United States Invests in Supercomputing

November 14, 2018

The CORAL supercomputers Summit and Sierra are now the world's fastest computers and are already contributing to science with early applications. Ahead of SC18, Maciej Chojnowski with ICM at the University of Warsaw discussed the details of the CORAL project with Dr. Dimitri Kusnezov from the U.S. Department of Energy. Read more…

By Maciej Chojnowski

At SC18: Humanitarianism Amid Boom Times for HPC

November 14, 2018

At SC18 in Dallas, the feeling on the ground is one of forward-looking buoyancy. Like boom times that cycle through the Texas oil fields, the HPC industry is en Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can Read more…

By John Russell

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry’s first plug-and-play, portable parallel file system that delivers up to 75 Gb/s per rack on industry standard hardware combined with “enterprise-grade reliability and manageability.” Read more…

By Doug Black

SC18 Student Cluster Competition – Revealing the Field

November 13, 2018

It’s November again and we’re almost ready for the kick-off of one of the greatest computer sports events in the world – the SC Student Cluster Competitio Read more…

By Dan Olds

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

OpenACC Talks Up Summit and Community Momentum at SC18

November 12, 2018

OpenACC – the directives-based parallel programing model for optimizing applications on heterogeneous architectures – is showcasing user traction and HPC im Read more…

By John Russell

How ASCI Revolutionized the World of High-Performance Computing and Advanced Modeling and Simulation

November 9, 2018

The 1993 Supercomputing Conference was held in Portland, Oregon. That conference and it’s show floor provided a good snapshot of the uncertainty that U.S. supercomputing was facing in the early 1990s. Many of the companies exhibiting that year would soon be gone, either bankrupt or acquired by somebody else. Read more…

By Alex R. Larzelere

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

Leading Solution Providers

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

Google Releases Machine Learning “What-If” Analysis Tool

September 12, 2018

Training machine learning models has long been time-consuming process. Yesterday, Google released a “What-If Tool” for probing how data point changes affect a model’s prediction. The new tool is being launched as a new feature of the open source TensorBoard web application... Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This