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According to Gartner, Machine Learning is at the Peak of Inflated Expectations: eDiscovery Trends

I missed this earlier, but, last month, Gartner published the 2016 edition of its Hype Cycle chart.  Machine Learning is only one of several “smart machine technologies” that will be “the most disruptive class of technologies over the next 10 years”.  But, if you look at the chart closely, you will find that Machine Learning is at the “Peak of Inflated Expectations”.

The report (available here), which “distills insight from more than 2,000 technologies”, says the following regarding smart machine technologies:

“Smart machine technologies will be the most disruptive class of technologies over the next 10 years due to radical computational power, near-endless amounts of data, and unprecedented advances in deep neural networks that will allow organizations with smart machine technologies to harness data in order to adapt to new situations and solve problems that no one has encountered previously. Enterprises that are seeking leverage in this theme should consider the following technologies: Smart Dust, Machine Learning, Virtual Personal Assistants, Cognitive Expert Advisors, Smart Data Discovery, Smart Workspace, Conversational User Interfaces, Smart Robots, Commercial UAVs (Drones), Autonomous Vehicles, Natural-Language Question Answering, Personal Analytics, Enterprise Taxonomy and Ontology Management, Data Broker PaaS (dbrPaaS), and Context Brokering.

The infographic shown below (have I told you lately how I love infographics?) shows the following phases: “Innovation Trigger”, “Peak of Inflated Expectations”, “Trough of Disillusionment”, “Slope of Enlightenment” and “Plateau of Productivity”.  It also color codes each of the technologies as to the number of years to mainstream adoption (i.e., less than 2 years, 2 to 5 years, 5 to 10 years, more than 10 years and obsolete before plateau).  Sorry folks, self-driving cars (a.k.a., Autonomous Vehicles) are still more than ten years away.  Machine learning is at the top of the curve (i.e., “Peak of Inflated Expectations”) and is predicted to become a mainstream item within two to five years.  Great news, though, in the short term, that means we’re about to head down the “Trough of Disillusionment”.  Oh dear.  Here is the infographic again, full-sized for easier reading:


Here is additional commentary from Sharon Nelson of Ride the Lightning and Serdar Yegulalp of InfoWorld.

So, what do you think?  Are the expectations for machine learning technology inflated at this point?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine. eDiscovery Daily is made available by CloudNine solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Daily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.