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 TechCrunch.com 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 Troggs-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 InformationWeek.com 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.

Listening

Another article about ambient intelligence entitled Towards a World of Ambient Computing, by Simon Bisson, posted on ZDNet.com 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 Amazon.com
  • 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.

Recommending

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:

Speaking

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 Time.com, 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 TechCrunch.com 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.

Three New Perspectives on Whether Artificial Intelligence Threatens or Benefits the World

"Gritty Refraction", Image by Mark Oakley

“Gritty Refraction”, Image by Mark Oakley

As the velocity of the rate of change in today’s technology steadily continues to increase, one of the contributing factors behind this acceleration the rise of artificial intelligence (AI). “Smart” attributes and functionalities are being baked into a multitude of systems that are affecting our lives in many visible and, at other times, transparent ways. Just to name one well-known example of an AI-enabled app is Siri, the voice recognition system in the iPhone. Two recent Subway Fold posts have also examined AI’s applications in law (1) and music (2).

However, notwithstanding all of the technological, social and commercial benefits produced by AI, a widespread reluctance, if not fear, of its capabilities to produce negative effects still persists. Will the future produce consequences resembling those in the Terminator or Matrix movie franchises, the “singularity” predicted by Ray Kurzweil where machine intelligence will eventually surpass human intelligence, or perhaps other more benign and productive outcomes?

During the past two weeks, three articles have appeared where their authors have expressed more upbeat outlooks about AI’s potential. They believe that smarter systems are not going to become the world’s new overlords (3) and, moreover, there is a long way to go before computers will ever achieve human-level intelligence or even consciousness. I highly recommend reading them all in their entirety for their rich content, insights and engaging prose.

I will sum up, annotate and comment upon some of the key points in these pieces, which have quite a bit in common in their optimism, analyses and forecasts.

First is a reassuring column by Dr. Gary Marcus, a university professor and corporate CEO, entitled Artificial Intelligence Isn’t a Threat—Yet, that appeared in the December 12, 2014 edition of The Wall Street Journal. While acknowledging the advances in machine intelligence, he still believes that computers today are nowhere near “anything that looks remotely like human intelligence”. However,  computers do not necessarily need to be “superintelligent” to do significant harm such as wild swings in the equities markets resulting from programming errors.(4)

He is not calling for an end to further research and development in AI. Rather, he urges proceeding with caution with safeguards carefully in place focusing upon on the apps access to other networked systems, in areas such as, but not limited to, medicine and autos. Still, the design, implementation and regulation of such “oversight” has yet to be worked out.

Dr. Marcus believes that we might now be overly concerned about any real threats from AI while still acknowledging potential threats from it. He poses questions about levels of transparency and technologies that assess whether AI programs are functioning as intended. Essentially, a form of “infrastructure” should be  in place to evaluate and “control the results” if needed.

Second, is an article enumerating five key reasons why the AI apocalypse is not nearly at hand right now. It is aptly entitled Will Artificial Intelligence Destroy Humanity? Here are Reasons Not to Worry, by Timothy B. Lee, which was posted on Vox.com on December 19, 2014. The writer asserts that the fears and dangers of AI are far overstated based on his research and interviews with some AI experts. To sum up these factors:

  • Actual “intelligence” is dependent on real world experience such that massive computing power alone will not produce comparable capabilities in machines. The example cited here is studying a foreign language well enough to pass as a native speaker. This involves both book learning and actually speaking with locals in order to include social elements and slang. A computer does not and never will have these experiences nor can they simulate them.
  • Computers, by their very nature, must reply on humans for maintenance, materials, repairs and ultimately, replacement. The current state of robotics development is unable to handle these responsibilities. Quite simply, machines need us and will continue to do so for a long time.
  • Creating a computerized equivalent of a real human’s brain is very tough and remains beyond the reach of today’s circuitry and programming.  Living neurons are indeed quite different in their behaviors and responses than digital devices.  The author cites the modeling of weather simulations as one where progress has been relatively small despite the huge increases in available processing capacity. Moreover, simulating brain activity in the an effort to generate a form of intelligence is relatively far more difficult than modeling weather systems.(5)
  • Relationships, more than intelligence, are needed to acquire power in the real world. Looking at the achievements of recent US presidents, the author states that they gained their achievements by virtue of their networks, personalities and skills at offering rewards and penalties. Thus, machines assist in attaining great technological breakthroughs, but only governments and companies can assemble to capital and resources to implement great projects. Taking this logic further, machines could never take over the world because they utterly lack the capability to work with the large numbers of people needed to even attempt this. (Take that, SkyNet.)
  • Intelligence will become less valuable as its supply increases according to the laws of supply and demand. As the pricing of computing continues to fall, their technological capabilities continues to rise. As the author interprets these market forces, the availability of “super-intelligent computers” will become commoditized and, in turn, produce even more intelligent machines where pricing is competitive. (6)

The third article presents a likewise sanguine view on the future of AI entitled Apocalypse or Golden Age: What Machine Intelligence Will Do to Us, by Patrick Ehlen, was posted on VentureBeat.com on December 23, 2014. He drew his research from a range of leaders, projects and studies to arrive at similar conclusions that the end of the world as we know it is not at hand because of AI. This piece overlaps with the others on a number of key points. It provides the following additional information and ideas:

  • Well regarded university researchers and tech giants such as Google are pursuing extensive and costly AI research and development programs in conjunction with their ongoing work into such areas as robotics, machine learning, and modeling simple connectomes (see fn.5 below).
  • Unintended bad consequence of well-intentioned research are almost always inevitable. Nonetheless, experts believe that the rate of advancement in this field will continue to accelerate and may well have significant impacts upon the world during the next 20 years.
  • On August 6, 2014, the Pew Internet Research Project published a comprehensive report that was directly on point entitled AI, Robotics, and the Future of Jobs by Aaron Smith and Janna Anderson. This was compiled based on surveys of nearly 1,900 AI experts. To greatly oversimplify the results, while there was largely a consensus view on the progress in this field and ever-increasing integration of AI into numerous areas, there was also a significant split of opinion as the economic,  employment and educational effects of AI in conjunction with robotics. (I highly recommend taking some time to read through this very enlightening report because of its wealth of insights and diversity of perspectives.)
  • Today we are experiencing a “perfect storm” where AI’s progress is further being propelled by the forces of computing power and big data. As a result, we can expect “to create new services that will redefine our expectations”. (7)
  • Certain sectors of our economy will realize greater benefits from the surge in AI than others.(8) This, too, will be likely to cause displacements and realignments in employment in these areas.
  • Changes to relevant social and public policies will be needed in order to successfully adapt to AI-driven effects upon the economy. (This is similar to Dr. Marcus’s views, above, that news forms of safeguards and infrastructure will become necessary.)

I believe that authors Marcus, Lee and Ehlen have all made persuasive cases that AI will continue to produce remarkable new goods, services and markets without any world threatening consequences. Yet they all alert their readers about the unintended and unforeseeable economic and social impacts that likely await us further down the road. My own follow up questions are as follows:

  • Who should take the lead in coordinating the monitoring of these pending changes? Whom should they report to and what, if any, regulatory powers should they have?
  • Will any resulting positive or negative changes attributable to AI be global if and when they manifest themselves, or will they be unevenly distributed in among only certain nations, cities, marketplaces, populations and so on?
  • Is a “negative” impact of AI only in the eye of the beholder? That is, what metrics and analytics exist or need to be developed in order to assess the magnitudes of plus or minus effects? Could such standards be truly objective in their determinations?
  • Assuming that AI development and investment continues to race ahead, will this lead to a possible market/investment bubble or, alternatively, some form of AI Industrial Complex?
  • So, is everyone looking forward to the July 2015 release of Terminator Genisys?

___________________________________

1.  See Possible Futures for Artificial Intelligence in Law Practice posted on September 1, 2014.

2.  See Spotify Enhances Playlist Recommendations Processing with “Deep Learning” Technology posted  on August 14, 2014.

3.  The origin of the popular “I, for one, welcome our new robot overlords” meme originated in the Season 5 episode 15 of The Simpsons entitled Deep Space Homer. (My favorite scene in this ep is where the – – D’oh! – – potato chips are floating all around the spaceship.)

4.   In Flash Boys (W.W. Norton & Company, 2014), renowned author Michael Lewis did an excellent job of reporting on high-speed trading and the ongoing efforts  to reform it. Included is coverage of the “flash crash” in 2010 when errant program trading caused a temporary steep decline in the stock market.

 5For an absolutely fascinating deep and wide analysis of current and future projects to map out all of the billions of connections among the neurons in the human brain, I suggest reading Connectome: How the Brain’s Wiring Makes Us Who We Are (Houghton Mifflin, 2012), by Sebastian Seung.  See also a most interesting column about the work of Dr. Seung and others by James Gorman in the November 10, 2014 edition of The New York Times entitled Learning How Little We Know About the Brain. (For the sake of all humanity, let’s hope these scientists don’t decide to use Homer J. Simpson, at fn.3 above, as a test subject for their work.)

6.  This factor is also closely related to the effects of Moore’s Law which states that the number of transistors that can be packed onto a chip doubles almost doubles in two years (later revised to 18 months). This was originally conceived by Gordon E. Moore, a legendary computer scientists and one of the founders of Intel. This principal has held up for nearly fifty years since it was first published.

7.  This technological convergence is fully and enthusiastically  explored in an excellent article by Kevin Kelly entitled The Three Breakthroughs That Have Finally Unleashed AI on the World in the November 2014 issue of WIRED.

8This seems like a perfect opportunity to invoke the often quoted maxim by master sci-fi and speculative fiction author William Gibson that “The future is already here – it’s just not very evenly distributed.”

Startup is Visualizing and Interpreting Massive Quantities of Daily Online News Content

"News", Image by Mars Hill Church Seattle

“News”, Image by Mars Hill Church Seattle

Just scratching the surface, some recent Subway Fold posts have focused upon sophisticated efforts, scaling from startups to established companies, that analyze and then try to capitalize upon big data trends in finance¹, sports² , cities³, health care* and law**. Now comes a new report on the work of another interesting startup in this sector called Quid. As reported in a most engaging story posted on VentureBeat.com on November 27, 2014 entitled Quid’s Article-analyzing App Can Tell You Many Things — Like Why You Lost the Senate Race in Iowa by Jordan Novet, they are gathering up, indexing and generating interpretive and insightful visualizations for their clients using data drawn from more than a million online articles each day from more than 50,000 sources.

I highly recommend a full read of this story for all of the fascinating details and accompanying screen captures from these apps. As well, I suggest visiting and exploring Quid’s site for a fuller sense of their products, capabilities and clients. I will briefly recap some of the key points from this story. Furthermore, this article provides a timely opportunity to more closely tie together seven related Subway Fold posts.

The first example provided in the story concerns the firm’s production of a rather striking graphic charting the turn in polling numbers for a Democratic candidate running for an open Senate seat in Iowa following a campaign visit from Hillary Clinton. When Senator Clinton spoke in the state in support of the Democratic candidate, she address women’s issue. Based upon Quid’s analysis of the media coverage of this, the visit seemed to have helped the Republican candidate, a woman, more then the Democratic candidate, a man.

Politics aside, Quid’s main objective is to become a leading software firm in supporting corporate strategy for its clients in markets sectors including, among others, technology, finance and government.

Quid’s systems works by scooping up its source materials online and then distilling out specific “people, places, industries and keywords”. In turn, all of the articles are compared and processed against a specific query. In turn, the software creates visualizations where “clusters” and “anomalies” can be further examined. The analytics also assess relative word counts, magnitudes of links shared on social media, and mentions in blog posts and tweets. (X-ref again to this November 22, 2014 post entitled Minting New Big Data Types and Analytics for Investors that covers, among other startups, one called Dataminr that also extensively analyzes trends in Twitter usage and content data.)

The sample screens here demonstrate the app’s deep levels of detail in analytics and visualization. As part of the company’s demo for the author, he provided a query about companies involved in “deep learning”.  (X-ref to this August 14, 2014 Subway Fold post entitled Spotify Enhances Playlist Recommendations Processing with “Deep Learning” Technology concerning how deep learning is being used to, well, tune up Spotify’s music recommendation system.) As this is an area the writer is familiar with, while he did not find any unexpected names in companies provided in the result, he still found this reassuring insofar as this confirmed that he was aware of all of the key participants in this field.

My follow up questions include:

  • Would it be to Quid’s and/or Dataminr’s advantage(s) to cross-license some of their technology and provide supporting expertise for applying and deploying it and, if so, how?
  • Would Quid’s visualizations benefit if they were ported to 3-D virtual environments such as Hyve-3d where users might be able to “walk” through the data? (X-ref to this August 28,2014 Subway Fold post entitled Hyve-3D: A New 3D Immersive and Collaborative Design System.) That is, does elevating these visualizations from 2-D to 3-D add to the accessibility, accuracy and analytics of the results being sought? Would this be a function or multiple functions of the industry, corporate strategy and granularity of the data sets?
  • What other marketplaces, sciences, professions and products might benefit from Quid’s, Dataminr’s and Hyve-3D’s approaches that have not even been considered yet?

________________________________
1.  See this November 22, 2014 post entitled Minting New Big Data Types and Analytics for Investors.

2.  See this October 31, 2014 post entitled New Data Analytics and Video Tools Affecting Defensive Strategies in the NFL and NBA.

3.  See this October 24, 2014 post entitled “I Quant NY” Blog Analyzes Public Data Sets Released by New York City.

*  See this October 3, 2014 post entitled New Startups, Hacks and Conferences Focused Upon Health Data and Analytics .

**  See this August 8, 2014 post entitled New Visualization Service for US Patent and Trademark Data .

Spotify Enhances Playlist Recommendations Processing with “Deep Learning” Technology

Music fans across the Web are now using music streaming services such as Spotify and YouTube for more than downloading sites according to a report in the July 3, 2014 edition of The New York Times entitled Downloads in Decline as Streamed Music Soars. Moreover, streaming is continuing to gain momentum for a number of reasons, not the least of which is that it is less expensive to access. Correspondingly, downloading sales are in decline. This article contains all of the details about this very significant shift in the online music marketplace, including the benefits to consumers and the concerns of musical artists.

A related follow up report entitled How Spotify is Working on Deep Learning to Improve Playlists was posted on Gigaom.com on August 5, 2014 that helps to explain how Spotify is trying to maintain its technical advantage. As reported here, Sander Dieleman, and intern at the company, has developed a method based upon deep learning (a branch of artificial intelligence), that parses large data sets in a new manner aimed at getting newer and lesser known recommendations into Spotify’s users’ playlist recommendations. Underlying this data processing is an examination of the acoustical properties of the user base’s song preferences.

The science behind the recommendation engines used so successfully by Spotify as well as Netflix and Amazon has come along many light years in it sophistication and accuracy since its earliest incarnations on the Web. For a comparative historical perspective, I also, well, recommend checking out an article from the December 1997 issue of WIRED magazine entitled Pattie about the work of Dr. Pattie Maes, a professor at MIT who founded (and later sold to Microsoft), a company called Firefly. Its technology was was one of the first efforts used to create software “agents” to scour the web for user-defined preferences for prices and products.

December 19, 2014 Update: 

Presenting an even stronger case that you-ain’t-seen-nothing-yet in this field was an engaging analysis of some still largely unseen developments in deep learning posted on December 15, 2014, on Gigaom.com entitled What We Read About Deep Learning is Just the Tip of the Iceberg by Derrick Harris. These include experimental systems being tested by the likes of Google, Facebook and Microsoft. As well, there were a series of intriguing presentations and demos at the recent Neural Information Processing Systems conference held in Montreal. As detailed here with a wealth of supporting links, many of these advanced systems and methods are expected to gain more press and publicity in 2015.