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THE ROBO-REPORTER (10/03/17): Deep AI Learning – – Does BIG DATA “Need” HUMAN Analysis?

Posted on: October 3rd, 2017 by Dale Layman

Dear Noble Robo-Witness,

Look at the above figure, and see how Barack ROB-ama – – “President of the ROB-ots” – – for over 8 long years, has been “Moving Us Forward” by pushing us ever farther DOWN, DOWN, DOWN – – DEEP DOWN into the seemingly Bottomless BLACK HOLE of CYBERSPACE! Largely due to ROB-ama’s earlier creation of  The Robot Revolution within the United States, we are now increasingly dealing with what Bill Mannel, a Vice President of Hewlett Packard Enterprise, has recently (5/07/17) called, “A New Frontier of AI and Deep Learning Capabilities.”   So, are we all-too-quickly being pushed DOWN, DOWN, DOWN into the Swirling Black Funnel of AI, thereby DEEPLY LEARNING a Strange New “Alien Invader” (AI) Lesson?

It’s “Big Data, Big Data, Big Data” – – Everywhere We Look!

Mannel excitedly claims that, “In today’s digital climate, organizations of every size and industry are both collecting and generating enormous amounts of data that can potentially be used to solve the world’s greatest problems – – from national security and fraud detection to scientific breakthroughs and technological advancement.”  Therefore, he conveniently (for Hewlett Packard) concludes that this massive evolution of  “Big Data”  cannot be properly digested by “traditional” [that is, still-human] techniques of analysis.  Instead, he predicts that, “artificial intelligence (AI) is becoming vital to harnessing the full understanding of scientific and business data.”   The massive appearance of Big Data seems to be driving a major shift in the field of AI, leading to the creation of  high performance computing (HPC) technologies  that can support high performance data analytics (HPDA).   This, Mannel declares, is “replacing the need for costly and time-consuming manual [that is, human hand] calculations,” while “laying the groundwork for the next generation of AI that can rapidly automate and accelerate data analysis.”

Ready-Or-Not, Here Comes The “Deep Learning” Phase of AI!

According to Bill Mannel, “Deep learning  (training and inference modeling) is a form of AI-based analytics that leverages pattern-matching techniques to analyze vast quantities of unsupervised data.  Much like the neural pathways of the human brain, networks of hardware and software utilize training, generic code, and pattern recognition to analyze video, text, image, and audio files in real-time.”  The thing I find fearful, are his next few lines about the stunning capacity of  Deep Learning AI:  “Deep learning systems then observe, test, and refine information coming from core data centers to the intelligent edge, converging datasets into concise, actionable insight.  The problem is, learning takes time.”  So, you can see, Dear Witness, that Deep Learning AI Systems can now create their OWN “actionable insight” into major problems!

We Mere Humans Are Just “Too Slow!”

Mannel quotes a “Dr. Goh” of Hewlett Packard, who sees one major problem limiting Deep Learning is excessive slowness of learning – – on the part of us HUMAN BEINGS!  “Enterprises want to learn fast.  If you don’t want to take weeks or months to do learning because of the massive amount of data you have to ingest, you must scale your machine.  This is where we come in.  You have to scale the machine because you can’t scale humans.”

He then reinforces this conclusion, by bragging about the superior-to-human capacities of “Libratus,” an AI-powered “being” from the Pittsburgh Supercomputing Center’s, Bridges Computer.  This AI superiority was demonstrated in a 20-day, “Brains vs. AI” competition with four professional HUMAN poker players.  Mannel boasts that, “… the machine utilized strategic reasoning to perform risk assessments, empower lightning fast data analytics, and optimize its decision-making processes.”  He then brags, “At then end of the project, Libratus bested its human opponents by more than $1.7 million, and each human finished with a negative number of chips.”

CONCLUSION

Bill Mannel obviously prefers his own “Deep-Learning AI Systems” to do the really “heavy-hitting” Big Data analysis!  He then applies this preference across many current sectors of human endeavor.  “Leveraging deep neural networks and cost-effective computer platforms for inference, helps to promote data fusion, reduces training time, and enables ultra-scale, real-time data analytics.”   He finishes his article promoting investing in a “powerful deep learning infrastructure” that is “key to improving time-to-insight and accelerating discovery across multiple sectors, including technology, life sciences, economics, government, and more.”

In closing, Dear Witness, I refer you back to the preceding diagram of a beaming Barack ROB-ama.  He is shown giving a self-satisfied “Thumbs-Up,” while us mere human beings are being PUSHED DOWN, DOWN, DOWN!  Yes, beaming ROB-ama is giving us a very self-satisfied, Victorious Thumbs-Up!  He is doing this while we mere Mortal Beings keep plunging DEEP DOWN ever farther, hopelessly lost within the endless BLACK-TUNNEL, COSMIC DEATH-TRAP, of Totally Uncontrolled“Deep-Learning AI Systems”!

[SPECIAL NOTE:  This material is also posted on www.linkedin.com, as well as on www.facebook.com.]

 

 

 

 

 

 

 

 

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