The Internet and the Web have evolved rapidly over the past twenty years. Web innovations in graphical presentation, ease of use, and request-response speed were quickly adopted by consumer-facing and customer-facing Internet companies, such as Amazon.com, Google, Priceline.com, Baidu, Netflix, and Salesforce.com, and more gradually adopted by employee-facing and business-facing enterprise companies, such as PeopleSoft, Microsoft, IBM, Oracle, and SAP.

We believe the adoption of artificial intelligence (AI) technologies will proceed in a similar fashion, with rapid adoption of smart voice and text assistants by consumers followed by a more gradual yet rapidly accelerating adoption of AI-powered cognitive applications, or apps, and cognitive cloud services by enterprise firms, as shown in the adjacent diagram entitled the 2020 Cognitive Things Cycle. 

While the primary benefit of smart assistants to consumers is to know more and do more faster than ever before, the key benefit of cognitive apps and cloud services to enterprises is to dramatically shift the workforce intelligence curve to make better decisions more quickly.

By unifying these benefits across consumers and enterprises, we posit with strong conviction that speed and optimality of action through augmented cognition is likely to be the core value proposition of AI. Under this premise, AI voice and text assistants, AI apps, and AI cloud services will significantly and perhaps radically disrupt entire global industries over the next decade.

Industries requiring highly intelligent and productive workforces as well as access to and interpretation of vast streams of raw data generated by the Internet of things (IoT) are most likely to be profoundly disrupted by AI and therefore ideally suited for early adoption of cognitive technologies. Examples of such industries include healthcare, finance, security, education, energy, and commerce, as illustrated in the cognitive voice, apps, cloud services, and IoT diagrams above.

Given the checkered history of AI, how do ensure that it will be sustainably successful this time? More specifically, how do we convey the value of AI to prospective users in such a way that it becomes both socially accepted and widely adopted by billions of users on a global scale?

While early research work in the field of AI showed immense promise, it failed to achieve its envisioned potential due to immature software algorithms, a dearth of large-scale data sets, and a lack of massively scalable computing power. As a result the entire field of AI went dormant until recent advances in machine learning algorithms, Internet of Things (IoT) data streams, and hybrid cloud computing technologies became simultaneously available at hyperscale earlier in this decade. 

Google, with its core assets in deep learning algorithms, IoT big data streams, and cloud-scale data datacenters, was singularly positioned to capitalize the resurgence of AI. Sensing this generational opportunity to stream bits directly to human eyes, the company launched Google Glass, a new class of wearable mobile intelligent eyewear enabling users to fundamentally know more, as illustrated in the diagram entitled Intelligent Eyewear Era.

Glass enabled users to instantly access information from the Internet, learn about about their surrounding environments, and share live photo and video snaps with friends and family members, as illustrated in the Internet glasses diagrams below.

Despite the initial version of Google Glass attracting immediate and mostly positive media attention at launch, the product soon came under fire as stories began to surface across numerous social media channels that Glass users were experiencing unwelcome and in some cases violent responses from onlookers while wearing the Internet-connected device in public. 

Unfortunately, the reputation and overall desirability of Glass was perhaps irreversibly sullied as these stories morphed into belittling skits presented ceaselessly during nightly and weekly comedy shows and YouTube videos.

While Glass clearly lacked a number of key technical features, such as long battery life, large number of apps, direct 4G connection, ultralight design, and loud noise suppression, the primary reason for its premature withdrawal from the market was fundamentally due to a) privacy concerns and b) design aesthetics.

More specifically, the public and the media rejected Glass primarily because the device could record and immediately share voice, sound, or video anytime or anyplace of anyone or anything and secondarily because of its awkward, bulky, and irregular asymmetric design relative to normal-looking glasses worn in public by everyday folks.

In contrast to the early setbacks experienced by Google Glass, we envision a very bright future for post-PC wearable Internet-connected smart glasses in general, or inocles, which represent an entirely new class of intelligent eyewear empowering users know more, do more, play more, and share more faster than ever before.

By addressing the two drawbacks of early releases of intelligent eyewear, next-generation inocles will be precision crafted, stylishly designed, and host to one or more embedded AI voice assistants with the ability to instantly comply with local privacy control rules and social norms. 

These rules and norms may be based on geographic location, time of day, or presence of privacy-sensitive individuals. For example, a prominent upscale restaurant may establish a no-video rule within its geographic boundaries. As a result of this rule, all inocle assistants would be required to immediately prevent an incoled user from accessing the embedded video capture system and wink-snapping photo or video snaps while inside or in close proximity to the restaurant.

Addressing consumer and business concerns over privacy control and design aesthetics will undoubtedly improve the adoption rate and social acceptance of next-generation versions of intelligent eyewear. However, mitigating these two concerns will not be sufficient to catapult this new class of devices into the global mainstream. 

Because intelligent eyewear (inocles) represents an entirely new computing platform, it needs a killer app or cloud service to galvanize consumer and business demand, in the same way in which killer apps drove demand for the PC platform and killer cloud services ignited demand for the smartphone platform.

In the mid-1980s, the killer app for the PC was the Lotus 123 spreadsheet; by the early 1990s, the Microsoft Office productivity suite became the primary reason for most business and consumer users to buy a PC. 

Similarly, in the late 2000s, the killer pair of cloud services for the smartphone were the Apple App Store and the Google Play store; by the mid-2010s, the Facebook social media app coupled with the astonishing worldwide popularity of selfies became the key reasons for most consumer users to buy a smartphone. 

If the success story of the PC (with an estimated installed base of 2 billion devices) was driven by primarily by spreadsheets and office suites and the success story of the smartphone (with a potential installed base of 10 billion devices) has been driven by social media apps and selfie snaps, then what game-changing apps, cloud services, and social media content types will drive the success story of inocles, with a potential installed base on the same scale as the number of pairs of shoes in the world?

In the next section, we feature a possible game-changing app, cloud service, and post-selfie content type for inocles that was first proposed on inocle.com in mid-2014 and subsequently extended and popularized by snapmashie.com in 2015.

As smart wearable mobile post-PC devices and suites become more powerful and next-generation wireless networking services provide near instantaneous transmission of ultra high definition audio, images, and video, we envision post-PC users will increasingly rely on smart voice agents, or AI assistants, to create and share new forms of structured social media content for entertainment, communication, and commercial purposes.

Over the past decade, the Apple iPhone, with its unprecedented simplicity, intuitive control, optimized experience, and direct access to the cloud, singularly defined the core qualities of a modern post-PC device, and it continues to serve as the anchor device for the Apple post-PC wearable mobile suite, as shown in the adjacent diagram entitled the Apple iFamily Post-PC Mobile Smart Suite.

Apple competitors Samsung, Google, and Xiaomi each have their own wearable mobile suite, typically comprising smart glasses, bands, watches, phones, and tablets, as shown in the adjacent diagram entitled Android Mobile Suites.

The wearable (smart glasses, bands, and watches) and mobile (smart phones and tablets) post-PC devices in these suites have made it extraordinarily simple for users to capture and create highly engaging social media content, most notably the universally popular selfie.

Given the remarkable rise of selfies across the globe, the key question is, “What comes after the selfie?” More specifically, how will social media users continue to entertain and engage friends, family, fans, and followers in the future? Will the selfie rule the day, or will a new more collaborative media type surface that changes the nature of social media communication.

One possible answer is that the selfie begins to share the global social media stage with an new collaborative media type called a mashie, as illustrated in the adjacent diagram entitled Post-Selfie Internet Storytelling.

A selfie typically depicts a static posed story constructed in isolation that is inwardly centered upon the user himself or herself and shared with local and global friends and fans on social networks without the possibility post-publication personalization, customization, or enhancement.

In contrast, a mashie typically describes a dynamic natural story constructed collaboratively with friends that is outwardly focused upon the user’s friends or surrounding environment rather than the user himself or herself and shared with local and global friends and fans on social networks with the expectation and anticipation of post-publication personalization, customization, and enhancement by select friends and fans.

An more in depth example of this new mashie-based approach to collaborative post-selfie Internet storytelling involving top supermodel icons of the nineteen eighties is illustrated by the adjacent supermodel mashie diagrams. The diagrams are based on a hypothetical gathering of top supermodel icons of the 1980s during an afternoon celebrity event and an evening afterparty.

Over the course of the afternoon and evening, supermodel friends interact naturally with each other and casually capture candid photo snaps and video snaps of each other meeting famous celebrity guests, dancing to live music performed by featured artists, adventuring back stage for a visit to an exclusive dressing room, or simply hanging out doing goofy things together using any one of the devices in their cloud-connected wearable mobile post-PC suite, such as a smart phone, smart watch, or their favorite pair of incoles.

During the events, supermodels occasionally bump their heads (for incoles) or hands (for smart watches and phones) together to automatically generate master mashies consisting of three-by-three grids of the most interesting and compelling photo and video snaps taken at the events thus far.

During or after the events, supermodels can personalize (with stickers, messages, backgrounds, and frames) and customize (with rotations, layouts, and speeds) their favorite master mashies and share them with friends, family, fans, and followers on Instagram, Twitter, Facebook, and Snapchat via the cloud.

What makes a mashie so unique is not just that it is collaboratively created and automatically generated as described above, but that its storyline can be extend by select supermodel fans and therefore live on and become increasingly more engaging long after the original master mashies are posted to the cloud, as illustrated by the adjacent fan mashies.