Tangerine’s Media Innovation Spec 2018 will have a secondary effect, on cognitive computing.
The purpose of media is to support the thought process, to help us understand things. Media will continue evolving for this purpose. Tangerine’s Spec will play an important part in making media a more energetic and able companion to thought and understanding, and will do so both for human, and machine, cognition.
What will cognitive systems (like IBM Watson) “see”, when they parse multi-media/data environments enhanced by our media innovation spec?
Machine (and human) cognitive systems find/reveal (or generate) connection, or correlation, between diverse and otherwise disconnected fragments of information. Through correlation, understanding grows, meaning is found, the essence, of situations, is pinpointed. Consequently, cognitive systems develop appropriate response to query, and they develop impetus, to appropriate action.
The latter, action, is beyond the scope of our work, as action involves a complex array of factors comprising the sum of “intent”, “purpose”, “opportunity”, “consequence”, “agency”, “will”, and many other such things. We’re focused rather on question and response, or “qa” (question and answer).
The power of cognitive systems is the power of meaningful discourse, dialog, conversation — between people and machine cognitive systems — conversation that generates meaningful answers to complex questions that don’t have pre-defined answers.
The media fusion that we can put into the hands of designers and builders everywhere as they think, act, and work (when our spec is implemented), can produce a new kind of data environment, one that amplifies the possibility of detecting relevant correlations that span a variety of different, and otherwise previously disconnected, data and media types, information bits and fragments.
Providing therefore for greater connectivity, our media fusion makes more fertile ground for cognition, a richer field in which the mind (human and machine) goes to work, where understanding grows.
In a highly complex and always changing data environment — like the real world, full of people, actions, tasks, and myriad data — cross-data-type correlations normally are not easy to detect. And so, machine intelligence has difficulty gaining traction in these kinds of environments. Gaining traction for cognitive systems in complex spatial visual environments though is precisely the possibility worth pursuing.
The fusion of spatial media (models), and the articulate act of “taking a closer look” (“drawing”, as it evolves via Tangerine’s Spec), will make correlation (the fuel of cognition) more discoverable and therefore more accessible to cognitive systems. We can develop the methods that will give cognitive systems adequate traction in spatial visual data sets where today they mostly spin their wheels.
We can help realize the full power of machine intelligence in these domains. I know where to begin this investigation into what happens at the intersection of cognitive systems and Tangerine Media.