Digital Smarts Everywhere: The Emergence of Ambient Intelligence

Image from Pixabay

Image from Pixabay

The Troggs were a legendary rock and roll band who were part of the British Invasion in the late 1960’s. They have always been best known for their iconic rocker Wild Thing. This was also the only Top 10 hit that ever had an ocarina solo. How cool is that! The band went on to have two other major hits, With a Girl Like You and Love is All Around.¹

The third of the band’s classic singles can be stretched a bit to be used as a helpful metaphor to describe an emerging form pervasive “all around”-edness, this time in a more technological context. Upon reading a fascinating recent article on entitled The Next Stop on the Road to Revolution is Ambient Intelligence, by Gary Grossman, on May 7, 2016, you will find a compelling (but not too rocking) analysis about how the rapidly expanding universe of digital intelligent systems wired into our daily routines is becoming more ubiquitous, unavoidable and ambient each day.

All around indeed. Just as romance can dramatically affect our actions and perspectives, studies now likewise indicate that the relentless global spread of smarter – – and soon thereafter still smarter – – technologies is comparably affecting people’s lives at many different levels.² 

We have followed just a sampling of developments and trends in the related technologies of artificial intelligence, machine learning, expert systems and swarm intelligence in these 15 Subway Fold posts. I believe this new article, adding “ambient intelligence” to the mix, provides a timely opportunity to bring these related domains closer together in terms of their common goals, implementations and benefits. I highly recommend reading Mr. Grossman’s piece it in its entirety.

I will summarize and annotate it, add some additional context, and then pose some of my own Trogg-inspired questions.

Internet of Experiences

Digital this, that and everything is everywhere in today’s world. There is a surging confluence of connected personal and business devices, the Internet, and the Internet of Things (I0T) ³. Woven closely together on a global scale, we have essentially built “a digital intelligence network that transcends all that has gone before”. In some cases, this quantum of advanced technologies gains the “ability to sense, predict and respond to our needs”, and is becoming part of everyone’s “natural behaviors”.

A forth industrial revolution might even manifest itself in the form of machine intelligence whereby we will interact with the “always-on, interconnected world of things”. As a result, the Internet may become characterized more by experiences where users will converse with ambient intelligent systems everywhere. The supporting planks of this new paradigm include:

A prediction of what more fully realized ambient intelligence might look like using travel as an example appeared in an article entitled Gearing Up for Ambient Intelligence, by Lisa Morgan, on on March 14, 2016. Upon leaving his or her plane, the traveler will receive a welcoming message and a request to proceed to the curb to retrieve their luggage. Upon reaching curbside, a self-driving car6 will be waiting with information about the hotel booked for the stay.


Another article about ambient intelligence entitled Towards a World of Ambient Computing, by Simon Bisson, posted on on February 14, 2014, is briefly quoted for the line “We will talk, and the world will answer”, to illustrate the point that current technology will be morphing into something in the future that would be nearly unrecognizable today. Grossman’s article proceeds to survey a series of commercial technologies recently brought to market as components of a fuller ambient intelligence that will “understand what we are asking” and provide responsive information.

Starting with Amazon’s Echo, this new device can, among other things:

  • Answer certain types of questions
  • Track shopping lists
  • Place orders on
  • Schedule a ride with Uber
  • Operate a thermostat
  • Provide transit schedules
  • Commence short workouts
  • Review recipes
  • Perform math
  • Request a plumber
  • Provide medical advice

Will it be long before we begin to see similar smart devices everywhere in homes and businesses?

Kevin Kelly, the founding Executive Editor of WIRED and a renowned futurist7, believes that in the near future, digital intelligence will become available in the form of a utility8 and, as he puts it “IQ as a service”. This is already being done by Google, Amazon, IBM and Microsoft who are providing open access to sections of their AI coding.9 He believes that success for the next round of startups will go to those who enhance and transforms something already in existence with the addition of AI. The best example of this is once again self-driving cars.

As well, in a chapter on Ambient Computing from a report by Deloitte UK entitled Tech Trends 2015, it was noted that some products were engineering ambient intelligence into their products as a means to remain competitive.


A great deal of AI is founded upon the collection of big data from online searching, the use of apps and the IoT. This universe of information supports neural networks learn from repeated behaviors including people’s responses and interests. In turn, it provides a basis for “deep learning-derived personalized information and services” that can, in turn, derive “increasingly educated guesses with any given content”.

An alternative perspective, that “AI is simply the outsourcing of cognition by machines”, has been expressed by Jason Silva, a technologist, philosopher and video blogger on Shots of Awe. He believes that this process is the “most powerful force in the universe”, that is, of intelligence. Nonetheless, he sees this as an evolutionary process which should not be feared. (See also the December 27, 2014 Subway Fold post entitled  Three New Perspectives on Whether Artificial Intelligence Threatens or Benefits the World.)

Bots are another contemporary manifestation of ambient intelligence. These are a form of software agent, driven by algorithms, that can independently perform a range of sophisticated tasks. Two examples include:


Optimally, bots should also be able to listen and “speak” back in return much like a 2-way phone conversation. This would also add much-needed context, more natural interactions and “help to refine understanding” to these human/machine exchanges. Such conversations would “become an intelligent and ambient part” of daily life.

An example of this development path is evident in Google Now. This service combines voice search with predictive analytics to present users with information prior to searching. It is an attempt to create an “omniscient assistant” that can reply to any request for information “including those you haven’t thought of yet”.

Recently, the company created a Bluetooth-enable prototype of lapel pin based on this technology that operates just by tapping it much like the communicators on Star Trek. (For more details, see Google Made a Secret Prototype That Works Like the Star Trek Communicator, by Victor Luckerson, on, posted on November 22, 2015.)

The configurations and specs of AI-powered devices, be it lapel pins, some form of augmented reality10 headsets or something else altogether, supporting such pervasive and ambient intelligence are not exactly clear yet. Their development and introduction will take time but remain inevitable.

Will ambient intelligence make our lives any better? It remains to be seen, but it is probably a viable means to handle some of more our ordinary daily tasks. It will likely “fade into the fabric of daily life” and be readily accessible everywhere.

Quite possibly then, the world will truly become a better place to live upon the arrival of ambient intelligence-enabled ocarina solos.

My Questions

  • Does the emergence of ambient intelligence, in fact, signal the arrival of a genuine fourth industrial revolution or is this all just a semantic tool to characterize a broader spectrum of smarter technologies?
  • How might this trend affect overall employment in terms of increasing or decreasing jobs on an industry by industry basis and/or the entire workforce? (See also this June 4, 2015 Subway Fold post entitled How Robots and Computer Algorithms Are Challenging Jobs and the Economy.)
  • How might this trend also effect non-commercial spheres such as public interest causes and political movements?
  • As ambient intelligence insinuates itself deeper into our online worlds, will this become a principal driver of new entrepreneurial opportunities for startups? Will ambient intelligence itself provide new tools for startups to launch and thrive?


1.   Thanks to Little Steven (@StevieVanZandt) for keeping the band’s music in occasional rotation on The Underground Garage  (#UndergroundGarage.) Also, for an appreciation of this radio show see this August 14, 2014 Subway Fold post entitled The Spirit of Rock and Roll Lives on Little Steven’s Underground Garage.

2.  For a remarkably comprehensive report on the pervasiveness of this phenomenon, see the Pew Research Center report entitled U.S. Smartphone Use in 2015, by Aaron Smith, posted on April 1, 2015.

3These 10 Subway Fold posts touch upon the IoT.

4.  The Subway Fold category Big Data and Analytics contains 50 posts cover this topic in whole or in part.

5.  The Subway Fold category Telecommunications contains 12 posts cover this topic in whole or in part.

6These 5 Subway Fold posts contain references to self-driving cars.

7.   Mr. Kelly is also the author of a forthcoming book entitled The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future, to be published on June 7, 2016 by Viking.

8.  This September 1, 2014 Subway Fold post entitled Possible Futures for Artificial Intelligence in Law Practice, in part summarized an article by Steven Levy in the September 2014 issue of WIRED entitled Siri’s Inventors Are Building a Radical New AI That Does Anything You Ask. This covered a startup called Viv Labs whose objective was to transform AI into a form of utility. Fast forward to the Disrupt NY 2016 conference going on in New York last week. On May 9, 2016, the founder of Viv, Dag Kittlaus, gave his presentation about the Viv platform. This was reported in an article posted on entitled Siri-creator Shows Off First Public Demo of Viv, ‘the Intelligent Interface for Everything’, by Romain Dillet, on May 9, 2016. The video of this 28-minute presentation is embedded in this story.

9.  For the full details on this story see a recent article entitled The Race Is On to Control Artificial Intelligence, and Tech’s Future by John Markoff and Steve Lohr, published in the March 25, 2016 edition of The New York Times.

10These 10 Subway Fold posts cover some recent trends and development in augmented reality.

Smart Dust: Specialized Computers Fabricated to Be Smaller Than a Single Grain of Rice


“Sabotage #4: Mixing Noodles with Rice”, Image by Stefan

Back in 1977, Steve Martin put out a live album of his stand-up comedy performances called Let’s Get Small. Included was one of his signature routines called Well, Excuse Me. It went on to sell more than a millions copies. Much of it was laugh-out-loud hilarious.

Now, 48 years later, when the Internet of Things (IoT) has becoming a burgeoning global phenomenon, some very imaginative people have taken this notion (in name only), and  in a way that could have never been foreseen in any manner back then.

Certainly no excuses needed here. Rather, let’s have a look at this exciting new development.

Researchers at the University of Michigan, led by Professor David Blaauw, have recently fabricated a functional and autonomous computer measuring only 1 millimeter on each side. This device, dubbed the Michigan Micro Mote (M^3), was the subject of a most interesting article by Rex Sakamoto on entitled This Working Computer is Smaller Than a Grain of Rice, posted on April 6, 2015. I will summarize it, add some links and annotations, and pose a few questions. (The CNET article also contains an embedded video of a very informative recent report about this project on CBS News.)

This team’s work has been ongoing for more than ten years. With regards to the IoT, they believe that all of devices connected to it will require more “intelligence” and networking capabilities integrated into them whereby the M^3 could be the means to accomplish this.

The M^3’s current capabilities are photography and as temperature and pressure sensors. The researchers are now exploring a range of potential applications “ranging from medical to industrial” including:

  • Medical: How it can be “injected into the body” to take such temperature and pressure readings, as well as an electrocardiogram (EKG).
  • Energy: Assessing whether an existing oil well still contains any extractable reserves.
  • Consumer Goods: Attaching M^3s to everyday items such as keys and wallets to insure they are never lost inside or outside of the home.
  • Other potential apps on the project’s website include a platform containing “low-resolution imager, signal processing and memory, temperature sensor, on-board CMOS timer, wireless communication, battery, and solar energy harvesting that are all packaged in a 1mm3 volume through low-cost die stacking and encapsulation.”

In order to program and power up the M^3, the researchers created a means to accomplish this by using “strobing light at high frequency”. In turn, the M^3’s output is transmitted to an external computer by “conventional radio frequencies”.

The team’s current efforts involve reducing the size of the M^3 even further to a point where it may become the basis for a form of “smart dust“.

Just a few days ago in the April 10, 2015 Subway Fold post entitled The Next Wave in High Tech Material Science about metamaterials that can bend sound, light, radar and seismic waves, I speculated about some other potential applications for this emerging technology. With the M^3 so similar insofar as its originality and  potential to generate a myriad of applications not even considered yet,  my questions include:

  • Are there apps where the M^3 and metamaterials can be combined? What about in optical networks where metamaterials are using in the production of fiber cables where the M^3s could be used as sensors?
  • Would the M^3 make a via sensor for transportation infrastructure (roads, bridges, rails and so on), as well as the bodies, engines and electronics in cars, planes and trains? How about embedding them into buildings for additional safety technologies?
  • What safety and privacy protocols and policies will need to be developed and by whom? How can they be enforced?

Artificial Intelligence Apps for Business are Approaching a Tipping Point


“Algorithmic Contaminations”, Image by Derek Gavey

There have been many points during the long decades of the development of business applications using artificial intelligence (AI) when it appeared that The Rubicon was about to be crossed. That is, this technology often seemed to be right on the verge of going mainstream in global commerce. Yet it has still to achieve a pervasive critical mass despite the vast resources and best intentions behind it.

Today, with the advent of big data and analytics and their many manifestations¹ spreading across a wide spectrum of industries, AI is now closer than ever to reaching such a tipping point. Consultant, researcher and writer Brad Power makes a timely and very persuasive case for this in a highly insightful and informative article entitled Artificial Intelligence Is Almost Ready for Business, posted on the Harvard Business Review site on March 19, 2015. I will summarize some of the key points, add some links and annotations, and pose a few questions.

Mr. Power sees AI being brought to this threshold by the convergence of rapidly increasing tech sophistication, “smarter analytics engines, and the surge in data”. Further adding to this mix is the incursion and growth of the Internet of Things (Iot), better means to analyze “unstructured” data, and the extensive categorization and tagging of data. Furthermore,  there is the dynamic development and application of smarter algorithms to  discern complex patterns in data and to generate increasingly accurate predictive models.

So, too, does machine learning² play a highly significant role in AI applications. It can be used to generate “thousands of models a week”. For example, a model premised upon machine learning can be used to select which ads should be placed on what websites within milliseconds in order to achieve the greatest effectiveness in reaching an intended audience. DataXu is one of the model-generating firms in this space.

Tom Davenport, a professor at Babson College and an analytics expert³, was one of the experts interviewed by Power for this article. To paraphrase part of his quote, he believes that AI and machine learning would be useful adjuncts to the human analysts (often referred to as “quants”4). Such living experts can far better understand what goes into and comes out of a model than a machine learning app alone. In turn, these people can persuade business managers to apply such “analytical insights” to actual business processes.

AI can also now produce greater competitive efficiencies by closing the time gap between analyzing vast troves of data at high speeds and decision-making on how to apply the results.

IBM, one of the leading integrators of AI, has recently invested $1B in the creation of their Watson Group, dedicated to exploring and leveraging commercial applications for Watson technology. (X-ref to the December 1, 2014 Subway Fold post entitled Possible Futures for Artificial Intelligence in Law Practice for a previous mention and links concerning Watson.) This AI technology is currently finding significant applications in:

  • Health Care: Due to Watson’s ability to process large, complex and dynamic quantities of text-based data, in turn, it can “generate and evaluate hypotheses”. With specialized training, these systems can then make recommendation about treating particular patients. A number of elite medical teaching institutions in the US are currently engaging with IBM to deploy Watson to “better understand patients’ diseases” and recommend treatments.
  • Finance: IBM is presently working with 45 companies on app including “digital virtual agents” to work with their clients in a more “personalized way”; a “wealth advisor” for financial planning5; and on “risk and compliance management”. For example, USAA provides financial services to active members of the military services and to their veterans. Watson is being used to provide a range of financial support functions to soldiers as they move to civilian status.
  • Startups: The company has designated $100 million for introducing Watson into startups. An example is WayBlazer which, according to its home page, is “an intelligence search discovery system” to assist travelers throughout all aspects of their trips. This online service is designed to be an easy-to-use series of tools to provide personalized answers and support for all sort of journeys. At the very bottom of their home page on the left-hand side are the words “Powered by IBM Watson”.

To get a sense of the trends and future of AI in business, Power spoke with the following venture capitalists who are knowledgeable about commercial AI systems:

  • Mark Gorenberg, Managing Director at Zetta Venture Partners which invests in big data and analytics startups, believes that AI is an “embedded technology”. It is akin to adding “a brain”  – – in the form of cognitive computing – – to an application through the use of machine learning.
  • Promod Haque, senior managing partner at Norwest Venture Partners, believes that when systems can draw correlations and construct models on their own, and thus labor is reduced and better speed is achieved. As a result, a system such as Watson can be used to automate analytics.
  • Manoj Saxena, a venture capitalists (formerly with IBM), sees analytics migrating to the “cognitive cloud”, a virtual place where vast amounts of data from various sources will be processed in such a manner to “deliver real-time analytics and learning”. In effect, this will promote smoother integration of data with analytics, something that still remains challenging. He is an investor in a startup called Cognitive Scale working in this space.

My own questions (not derived through machine learning), are as follows:

  • Just as Watson has begun to take root in the medical profession as described above, will it likewise begin to propagate across the legal profession? For a fascinating analysis as a starting point, I highly recommend 10 Predictions About How IBM’s Watson Will Impact the Legal Profession, by Paul Lippe and Daniel Katz, posted on the ABA Journal website on October 4, 2014. I wonder whether the installation of Watson in law offices take on other manifestations that cannot even be foreseen until the systems are fully integrated and running? Might the Law of Unintended Consequences also come into play and produce some negative results?
  • What other professions, industries and services might also be receptive to the introduction of AI apps that have not even considered it yet?
  • Does the implementation of AI always produce reductions in jobs or is this just a misconception? Are there instances where it could increase the number of jobs in a business? What might be some of the new types of jobs that could result? How about AI Facilitator, AI Change Manager, AI Instructor, AI Project Manager, AI Fun Specialist, Chief AI Officer,  or perhaps AI Intrapreneur?


1.  There are 27 Subway Fold posts in the category of Big Data and Analytics.

2.  See the Subway Fold posts on December 12, 2014 entitled Three New Perspectives on Whether Artificial Intelligence Threatens or Benefits the World and then another on December 10, 2014 entitled  Is Big Data Calling and Calculating the Tune in Today’s Global Music Market? for specific examples of machine learning.

3.  I had the great privilege of reading one of Mr. Davenport’s very insightful and enlightening books entitled Competing on Analytics: The New Science of Winning (Harvard Business Review Press, 2007), when it was first published. I learned a great deal from it and this book was responsible for my initial interest in the applications of analytics in commerce. Although big data and analytics have grown exponentially since its publication, I still highly recommend this book for its clarity, usefulness and enthusiasm for this field.

4.  For a terrific and highly engaging study of the work and influence of these analysts, I also recommend reading The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (Crown Business, 2011), by Scott Patterson.

5.  There was a most interesting side-by-side comparison of human versus automated financial advisors entitled Robo-Advisors Vs. Financial Advisors: Which Is Better For Your Money? by Libby Kane, posted on on July 21, 2014.