In the last 20 years, I’ve observed technology trends, and Tech achievements have risen and fallen from the mainstream. Tech has augmented our lives, and enhanced our human capabilities. Our evolution will continue to be molded by technology and shape humanity for years to come.
Everything you might find on your computer from emails to video are digital assets. Content from providers, team collaboration, push and/or pull asset distribution, and archiving content are the workflows of DAM.
DAM solutions are rapidly going main stream as small to medium sized content providers look to take control of their content from ingestion to distribution. Shared digital assets will continue to grow rapidly. Pressure by stockholders to maximize use of digital assets to grow revenue will fuel initiatives to globally share and maintain digital asset taxonomies. For example, object recognition applied to image, sound and video assets will dynamically add tags to assets in an effort to index ever growing content. If standard taxonomies are not globally adopted, and continually applied to assets, digital content stored will become, in essence, unusable.
All devices across all business verticals will become ‘Smart’ devices with bidirectional data flow. Outbound ‘Smart’ device data flow is funneled into repositories for analysis to produce dashboards, reporting, and rules suggestions.
Inbound ‘Smart’ device data can trigger actions on the device. Several devices may work in concert defined by ‘grouping’ e.g. Home: Environmental. Remote programming updates may be triggered by the analysis of data.
- AI Rules Engine runs on ‘backend’. Rules defined by Induction, through data analysis, and human set parameters, executed in sequence
- Device optimization updates, presets on devices may be tuned based on ‘transaction’ history, feedback from user, and other ‘Smart’ devices.
- Grouped ‘Smart’ devices, e.g. health monitors’ data uploaded, analyzed, and correlating across group. Updated rules, and notifications triggered.
- Manual user commands, ad hoc or scheduled
Cloud ‘Services’ enables scalability on demand, relatively lower cost [CapEx] overhead, offsite redundancy, etc. Provides software solutions companies to rapidly deploy to Dev., Test, and Prod. environments. Gaming, storage, and virtual machines are just a few of the ‘…as a service’ offerings. IoT analysis may reveal a new need for another service.
Integrates user to surrounding environment with overlay images to your eyes to REpresent anything, e.g. Identifies surrounding people with Twitter handle/user name above their heads. Interacts with smartphone for Inbound and outbound data flow. May allow App and OS programmers to enable users to interact with their ‘traditional’ software in new ways, e,g. Microsoft Windows 8+, current interaction with ’tiles’, may shift from a two to three dimensional manipulation and view of the tiles. Tiles (apps) pop up when, through object recognition, predefined characteristics match, e.g. Looking at a bank check sent to you from the mail? Your Bank of America tile / app may ask if you want to deposit the check right now?
As more drones, for example, collect video footage, may be used for people to experience the landscapes, beaches, cities, mountains, and other features of a potential destination, which may lead to tourism. In fact, travel agencies may purchase the V.R. Headsets, and subscribe to a library of V.R. content. Repository platform would need to be created. Specs for the ‘How To’ on collecting V.R. Video footage should be accessible. Hathaway real estate offers a V.R. tour of the house, from their office.
Autonomous Vehicles (Average Consumer or hobbyist)
Driving forces to integrate with society puts pressure on individuals to integrate with the collective social conscious. As digital assets are published, people will lunge at the opportunity to self tag every digital asset both self and community shared assets. Tagging on social media platforms is already going ahead. Taxonomies are built, maintained and shared across social media platforms. Systematically tagged [inanimate] objects occur using object recognition. Shared, and maintained global taxonomies not only store data on people and their associated meta data, (e,g, shoe size, education level completed, HS photo,etc.) but also store meta data about groups of people, relationships and their tagged object data.
The taxonomies are analyzed and correlated, providing better, more concise demographic profiles. These profiles can be used for
- Clinical trials data collection
- Fast identification of potential outbreaks, used by the CDC
- The creation and management of AI produced Hedge Funds
- Solicitation of goods and services
These three dreaded words you are guaranteed to see more and more often. As all aspects of our lives become meta data on a taxonomy tree, the analysis of information will make correlations which drive consumers and members of society ‘out of compliance’. For example, pointers to your shared videos of you skydiving will get added to your personal taxonomy tree. Your taxonomy tree will be available and mandatory to get life insurance from a tier 1 company. Upon daily inspection of your tree by an insurance AI engine, a hazardous event was flagged. Notifications from your life insurance company reminding you ‘dangerous’ activities are not covered on your policy. Two infractions may drive up your premiums.
