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IBM Technical University in Orlando 2018 Day 1 Keynote Sessions
This week, I am in Orlando, Florida for the [IBM Technical University], with focus on IBM storage, IBM Z mainframes and IBM Power servers. Here is my recap for the keynote sessions on Day 1.
Art Beller, IBM Vice President of WW Systems Technical Sales
Art Beller, my third-line manager, kicked off the event. He explained that with [Artificial Intelligence], or AI for short, we are entering the "age of the incumbent". All across industries, the companies that have established dominance over the decades have the most data to get value from.
Kathryn Guarini, IBM Vice President Research Strategy
Kathryn provided an overview of the latest news on AI. Over 700 students at MIT, and 1,000 students at Stanford University, have signed up for "Intro to AI" classes. There are over 30,000 AI-related jobs in IT today. The investment in AI is 10 times more than it was just four years ago.
Kathryn explained there are three levels of AI: Narrow, Broad, and General. Narrow AI finally works, such as face recognition or speech-to-text translation. Broad AI is still a ways out, and General AI is not expected until year 2050.
An area of research is to "Learn more with less". For example, if you train a photo image recognition to identify different species of dogs, can you extend some of this learning to recognize different cats? This is often referred to as "Transfer Learning".
Cyber-criminals are already using AI, and if they can infiltrate AI training models, can introduce some scary scenarios. The next cyber battle-field will be AI vs. AI.
AI results need to be "Explainable", both in the training and debugging phases, as well as the infer/deployment phases. We need to detect and eliminate human biases, and rank different models on their fairness.
Kathryn gave some real examples:
Medical Sieve: An MRI scan captures over 10,000 images. Through AI, the top 25 most important images can be identified, making a doctor's job easier in identifying tumors.
Cancer Research: There are over 800 billion DNA base pairs to evaluate for different cancers, combined with 723 million published articles are relevant research. AI can help sort this out, matching the best research for the appropriate type of cancer.
Banking Regulations: There are over a million compliance documents, and some banks have more than 10,000 employees focused on enforcing compliance. About 10 percent of these compliance documents change every year, making this a moving target.
Fraud Detection: There are too many "false positives" in today's algorithms for suspicious spending behavior. AI can help identify this better.
Video Highlights: AI can be used to generate movie trailers or sports highlights by identify the most relevant portions of a movie or sporting event.
Reduce Air Pollution: China is investigating the use of AI to reduce air pollution in its country. Large cities like Beijing are particularly over-polluted.
Hillery Hunter, IBM Fellow and Director of Accelerated Cognitive Infrastructure at IBM Research
AI takes Terabytes of information, both structured and unstructured data, to develop a model that is very small, perhaps a few MB or GB.
The four steps are: identify your data sources, do some data preparation, train your model, and then infer using that model. Your data sources are stored in a Capacity Tier (often referred to as Data Lake). Inference must be done quickly, so a Performance tier is needed for that phase.
In some cases, data can't move, so for those situations, we need "Federated AI" where we can combine results from different systems.
IBM has added Distributed Deep Learning (DDL) to its PowerAI set of libraries. To estimate "Click-Thru Rate", a typical approach with 4.2 billion training examples took 70 minutes. With PowerAI DDL, this was reduced to 91 seconds. In another example, training that took nine days was reduced to four hours.
Lastly, Hillery mentioned "in-memory computing". Rather than reading data in from memory, and performing some computation on it, this new approach does part of the compute processing on the memory chip itself, eliminating a lot of data transfers.
Clod Barrera, IBM Distinguished Engineer and Chief Technical Strategist for storage
In previous years, IBM Technical University would offer brand-specific keynote sessions for IBM Z, IBM Power and IBM Storage. However, these were in the same time slot, so you could only see one of them. This year, IBM Storage was put into a different slot, so people could hear about their server of choice, and then also listen to the storage keynote.
Clod gave a state of the industry related to different storage media. For Flash, for example, he explained that Phase Change Memory is being developed, using the difference between amorphous and crystalline states to represent ones and zeros.
Tape is also seeing a resurgence. In 2005, Microsoft had declared tape was dead. Today, their Microsoft Azure is a big fan of tape to store data at reduced cost. Tape is 20 times less expensive than disk.
Clod summarized his talk by stating the key areas of storage development:
Optimizing for Artificial Intelligence
Automation for Security and Privacy
Data Governance and Management
You can follow along this week with Twitter hashtag #IBMTechU, or follow me at @az990tony.