The end of inattention blindness.

The textbook definition of inattentional blindness is “the failure to notice a fully-visible, but unexpected object because attention was engaged on another task, event, or object”.[1] It is also the definition of human cognition and experiential modes of relating to the everyday world. The video “A movie perception test – conversation” illustrates how movie perception works.[2] Whoever you ask, no one is able to perceive the most obvious switches and changes. They are obvious to all, in retrospect. Not taking. In everything, not being aware of every separate movement in our proximity is vital to our mental wellbeing and survival. As our perception itself is not continuous, neither is our attention.

Two trends, one focused on edge and one on cloud are converging to train AI and Machine Learning to develop a continuous real-time full vision capability; “large scale cloud hosted AI and ML platforms offered by AWS and Google make it much easier for app developers to integrate AI and ML in their app” [3] and the lowering. Of cost. In microprocessors enables ML on devices training software recognition with cheap webcams to become as performative as high end camera solutions.

These trends build a full attentional vison. They create a new ontology, a way of perceiving that was either not existent, or not able of action based on its capabilities.

I argue this is political.


[1] http://www.scholarpedia.org/article/Inattentional_blindness

[2] http://www.theinvisiblegorilla.com/videos.html

[3] https://towardsdatascience.com/ai-capabilities-in-image-recognition-7d79...

more iot news