4. Traditional Video vs. Intelligent Video
To illustrate, in broad strokes, the mechanics behind Steve’s scenario, imagine a 3-minute excerpt from his weight-loss video program that can be broken down into the following sections:
- a). the trainer counts aloud for a set of 25 jumping jacks (50 seconds)
- b). she offers encouragement while repositioning onto the floor (10 seconds)
- c). she counts aloud for a set of 35 push ups (50 seconds, ‘2 units’ up)
- d). she provides instruction while rotating onto her back (10 seconds)
- e). she counts aloud for 30 crunches (50 seconds, ‘1 unit’ down)
- f). she sits and takes a sip of water, preparing for the next set (10 seconds)
An exercise sequence such as this, like many other real-time instructional formats (e.g. cooking, music lessons, etc.), can be divided into two main categories:
- active content, in which synchronicity provides value for the audience;
- transitional content (ie. “negative space”), in which it does not.
With that in mind, here are two graphics that compare and contrast the functionality of the fitness video sequence described above, first in traditional video form:
And now, in intelligent video form, this graphic represents Steve’s video path as described above:
BUT, the crucial difference here between traditional video form vs. intelligent video form is that, in the case of the latter, there are 26 additional ways Steve could uniquely experience this 3-minute sequence.
Quantifying this data shows that significant disparities arise in scope of content, even with just 3 layers, 3 stacks, and 1 pivot per transition (3:3:1):
In other words, if 1 unit = 6 seconds, then traditional video form only gives Steve access to 180 seconds of content over the span of the 3-minute sequence, while intelligent video form gives Steve potential access to 468 seconds of content for the same duration of time.
Significant disparities arise in complexity, even with just 3 layers, 3 stacks, and 1 pivot per transition (3:3:1):