SAS Analytics Experience: Viya and Cognitive Computing


Last fall, SAS announced its new Viya analytics platform with an emphasis on openness -- including the ability for users of more non-SAS languages and tools to access SAS analytics capabilities without learning to program SAS.

With the opening of the first Analytics Experience conference this week in Las Vegas, SAS (sponsor of this site) has released Viya based products to put in into action. However, SAS also is highlighting how Viya serves as a building block for advances in emerging technology concepts such as machine learning and cognitive computing.

SAS presented Viya as supporting access to SAS capabilities from other tools such as Java, R, Python, PMML, C, Hadoop, Spark, and MAPR. For companies doing innovative work in areas such as cognitive computing applications but without having full SAS licenses, they can use the REST API to access SAS analytics capabilties.

Setting the stage for the Monday announcements, SAS co-founder and CEO Jim Goodnight noted the growing importance of analytics in the world today, saying, "What is happening in analytics today is a total revolution."

Discussion of the potential for cognitive computing was a recurrent theme for SAS at AX.

Wayne Thompson, a senior product manager for SAS, said we are entering "the age of cognitive computing."

In explaining cognitive computing, Thompson said that all applications should be able to reason, to identify and highlight trends found in data, even, someday, to recognize human emotions as you go through your daily work. It means marrying natural language programming (NLP) with deep learning.

Thompson cited application areas where cognitive computing already is a factor, such as cybersecurity, healthcare, and image analysis.

Oliver Schabenberger, SAS executive vice president and chief technology officer, said in a press release, “Cognitive computing is disruptive, combining technologies such as natural language processing, image processing, text mining and machine learning to augment human intelligence. SAS has supported cognitive technologies in analytics for decades. The exciting change is applying deep learning and high-performance computing to achieve greater automation and accuracy in the interaction between computers and people.”

According to Schabenberger, when users of Python or other open source languages move from a single-threaded environment to the multithreaded, distributed architecture of SAS Viya, they may see processing times shrink from hours to minutes. This is in addition to the operational benefits of using common data models, centralized administration, governance and world-leading analytics.

In another announcement the company released its Viya-based SAS Visual Data Mining and Machine Learning software, which will be available later this month.

SAS positioned the software as a means to "boost data scientist productivity." The company said it includes features such as flexible, web-based programming; highly scalable, in-memory data manipulation and analytical processing; rowerful data manipulation and management; data exploration, variable transformations and dimension reduction; and modern statistical, data mining and machine-learning techniques.

SAS also introduced SAS Visual Investigator, which leverages Viya to combine advanced analytics with "dynamic and interactive visual workspaces." The company noted, "Analysts can easily grasp reasons for events or alerts and act on deep analytical insights thanks to intuitive visuals and search."

Among other uses, Visual Investigator is positioned in application areas such as fraud detection and response and healthcare.

James M. Connolly, Editor of All Analytics

Jim Connolly is a versatile and experienced technology journalist who has reported on IT trends for more than two decades. As editor of All Analytics he writes about the move to big data analytics and data-driven decision making. Over the years he has covered enterprise computing, the PC revolution, client/server, the evolution of the Internet, the rise of web-based business, and IT management. He has covered breaking industry news and has led teams focused on product reviews and technology trends. Throughout his tech journalism career, he has concentrated on serving the information needs of IT decision-makers in large organizations and has worked with those managers to help them learn from their peers and share their experiences in implementing leading-edge technologies through publications including Computerworld. Jim also has helped to launch a technology-focused startup, as one of the founding editors at TechTarget, and has served as editor of an established news organization focused on technology startups and the Boston-area venture capital sector at MassHighTech. A former crime reporter for the Boston Herald, he majored in journalism at Northeastern University.

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Re: Am I Angry Or Did My Dog Just Die?
  • 9/18/2016 12:53:00 PM
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..

Jim writes


... it's probably early for machines to read emotions. However, I could see how it would come together in the future. It couldn't be based simply on word selection, but more likely that in combination with things like voice level/volume on the part of the caller, key words like "never again", "stupid," etc., of course the usual cuss words, and even speech pattern, when we get angry or frustrated we often speak in bursts with silent moments of stewing in between.

So, it would have to be a multi-factor system.


 

I think machines (or robots or artifically created personalities) would need to be able to recognize and interpret a very wide range of quite subtle cues to competently and adequately read emotions. I predict this would require the development of very advanced machine self-learning capabilities, probably based on infrastructure that incorporates significant components of synthesized artificial DNA with the ability to generate this material as needed to accommodate expanding cognitive requirements.

Well, just my speculation. But one of my characters in a YA-MG novel I'm working on – a humanoid robot created by an alien civilization about 1300 years of development ahead of our own species – incorporates these features.

In any case, I have a hunch that today's human AI researchers have a long way to go to catch up...

 

Re: Am I Angry Or Did My Dog Just Die?
  • 9/16/2016 4:13:33 PM
NO RATINGS

@kq4ym. Right, it's probably early for machines to read emotions. However, I could see how it would come together in the future. It couldn't be based simply on word selection, but more likely that in combination with things like voice level/volume on the part of the caller, key words like "never again", "stupid," etc., of course the usual cuss words, and even speech pattern, when we get angry or frustrated we often speak in bursts with silent moments of stewing in between.

So, it would have to be a multi-factor system.

Some other possibilities for cognitive computing would be for the system to flag aberrations in data. For example, today we can program in parameters for when sales go down in a region (black turns to red and so on). However, the idea floated by SAS is that there is potential for a system to spot trends on its own, such as the first time in three years that a particular product line was in the black.

 

Am I Angry Or Did My Dog Just Die?
  • 9/16/2016 8:13:47 AM
NO RATINGS

I'm a bit skeptical of a machine being able to read my emotions, at least anytime in the near future. It seems that words are not necessarily the best indication of one's emotions. Calling in sympathy, empathy and compassion as necessary components to discover emotions might be a tricky piece of programming. My words indicating "anger" might very well be a disguise for depression. My words that look like happiness might well be faked when I'm really just hiding some other emotion. It will be interesting to watch developments in machines' ability "to recognize human emotions as you go through your daily work."

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