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.
The ideas in my book (free on Apple Books, and in PDF for download), when used and implemented by software companies, will change/evolve the nature of “drawing” (the nature of its expression, changing the way that we “draw attention to”, “take a closer look”), as well as the nature of drawing’s fusion within models, moving beyond the first generation drawing-model fusions that began (with my work at the time at Bentley Systems) in 2012. The new evolutions described in my book, now, for software developers, will bring change also to the basic nature of digital modeling, the basic means by which we engage/interact with modeled environments, while presenting also new means for contribution in the field of cognitive computing. This slide deck (5 slides) gives a short intro to the book, Tangerine Media Innovation Spec 2018