Have you heard of Smart dust, 4D printing, Neuromorphic hardware, Serverless PaaS & FaaS, Conversational user interfaces, Augmented data discovery, Edge computing, NGDLE, Prescriptive analytics? Who has not!? Gartner or similar buzzword hype factories provide us with an excellent service of establishing intrigue among business captains and capital navigators of the world; as cutting edge development is concentrated more and more in information technologies sector. We at the laboratory, have difficulty following on certain, sometimes misunderstood, technologies, in regard to actual aplicability in different business sectors and commercial value.

To be clear, it is not authors intent to deemphasize certain interesting emerging technologies. Technology production, from basic research to commercialised solutions development is important. But how can layman benefit directly from this future popular lingo?

Do not miss on these conversation starters:

  • Smart dust
    Tiny microelectromechanical systems (MEMS) operating at near or at the nanoscale, defined as 1 to 100 nm, that are now generally at design stage were conceptioned primarily with battlefield use in mind.  Such microdevices in form of sensor networks, micro robots, or other devices are able to wirelessly communicate with central decision making platform or organise between themselves according to given set of rules.
  • 4D printing
    Also known as 4D bioprinting, active origami, customizable smart materials, or shape-morphing systems; 4d printing uses similar tecqhniques as 3D printing, adding the 4th dimension with transformation of the form in time or in certain conditions, for example, temperure sensitivity and other chemical components reactivity (object submersed in water of certain temperature changes structure and function).
  • Neuromorphic hardware
    In this bottom-up approach scientist are looking at biological neural networks and trying to figure out their principle of operation in order to design computer hardware based on these similarities with human brain. The assumption here is that nature’s own evolutionary design is the best model for computing, decision making, behaviour emulation…  should be imitated in its entirety. Artificial intelligence’s greater processing power needs, with simulating human brain, will require this design approach. These theories of the behavior of neural microciruits need extensive testing.
  • Serverless PaaS & FaaS
    “Serverless” is a bit missleading, as most aproaches in this field utilize the underused resources of existing servers in a manner that provides enough persistence and decentralisation for robust performance and constant availability of functions and platforms on demand.
  • Conversational user interfaces
    …so, chat-bots? Well, this is a promise of much more. CUI’s provide opportunity for the user to communicate with the computer in their natural language rather than in a syntax (CLI) or layout (GUI) specific commands. It is a take on emotion and sentiment context reactive computers interfaces to understand, analyze and create meaning from human language.
  • Augmented data discovery
    ADD is an emerging field in big data and analytics. In 2017, Gartner described this in a report as the trend topic in the area of ​​Data & Analytics. Augmented Data Discovery (ADD) describes tools that allow the user to easily visualize, analyze, and analyze data without the help of IT or data experts. There are still very few intuitive tools that can be understood as ADD software but the demand is there.
  • Edge computing
    “Edge computing is a method of optimizing applications or cloud computing systems by taking some portion of an application, its data, or services away from one or more central nodes (the core) to the other logical extreme (the edge) of the Internet which makes contact with the physical world or end users (wikipedia). To paraphrase: most heavyveight processing and presentation of data from sensors is done on client’s device by more or less fat clients; in this manner, depending less on central server infrastructure. Edge computing is sometimes congruent with fog computing.
    Next generation digital learning envirments is what could replace learning management platforms. The NGDLE is an ecosystem of interconnected and customizable applications that support digital learning through five aspects: interoperability; personalization; analytics, advising, and learning assessment; collaboration; and accessibility and universal design in order to establish cost and time efective quality transfer of knowledge to students and employees.
  • Prescriptive analytics
    In a linear extent from descriptive, diagnostic and predictive analytics to prescriptive analytics – actionable analitycs that provide quality improvements, service enhancements, cost reductions and productivity increases. This approach is know from conventional machine and equipment maintenance. These kind of automated process also creates more work, by triggering a series of phone calls, emails, and other “out-of-band” activities.

Leave a Reply