Showing posts with label EAdelman. Show all posts
Showing posts with label EAdelman. Show all posts

Wednesday, September 21, 2022

Looping Images and Sounds

 

Looping Images and Sounds

Evoke Deep Learning Promise

Rotating Comic Characters

Offer

Deep Learning Practice

 

Current psychological research relates that over-dependence on device/computer screens can lead to short attention spans, with our visual speed crushing our inherent listening capability.  Yet, we still rely heavily on multiple screens for our daily pursuits.

How can we maintain our exposure to the myriad of screen images, with multiple details on split visual fields, and yet use them even further to benefit and escalate us? 

Although our visual memory can dominate with this screen adhesion, our auditory memory (listening) then suffers, out-of- sync.  Unable to integrate auditory, we can only focus on singular image-memory intake. One-item-at-a-time; primarily, visually.

 However, we can remedy this imbalance, and put laborious visual screen intake to our advantage. But, that is, if we agree to undertake the needed effort required; admitting that a better focused, integrated, memory spans has personal value. 

Question:  Why do I need Deep Learning rehearsal looping practice to obtain higher memory spans? I have plenty to do with my screen life as it is, and there are many simple brain games available.

Answer:  Because most jobs now require procedural training with an eye for detail, management acumen. Everyday life demands require fast organizational self-management. Furthermore, our daily life and work productivity could suffer, especially if procedural listening and instructions are required.

 Change needed.

Call in comic characters to the rescue -- inanimate 3D objects become activated

Looping images and sounds can strengthen our minds. Continuous rehearsal segments will affect the frontal brain cortex for improved working memory [1] required to quickly learn procedures. Okay, what will comprise these segments?

 Looping comic characters.

Five specific characters, in a researched and practiced program, entered the rehearsal paradigm stage.  Although they varied in gender, appearance, personality, and temperament, nonetheless, remained non-distracting, timed objects.

But, soon they went to work, becoming free to loop repetively with interplay.[2] Their assignment was mental skill sequencing practice, fundamental to following oral and written directions and procedures.

The looped motion interaction evolves into its own reinforced learning [3] for the participant. Each spoken entity creates a visual and sound unit to reinforce the preceding segment, as Leonardo noted in the early 1500s, Renaissance. [4]

The visual facial patterns become oriented in space-time creating their own local motion/sound/visual energy.[5]

Question. How will these objects create auditory memory integration with Deep Learning features? 
Answer: Through 5th Dimension counter point, [6] or parallel thought [7]

Question:  What is the 5th Dimension aspect? Is it strictly an assumption?
Answer:  The 5th D formulates as a result of combining the first four dimensions that had decades of scientifically documented mechanisms. The three common dimensions now create four and five added complex dimensions into one serial, cumulative, conception.

All five progressive dimensions each had years of scientific, well-documented, authenticated research and practice. [8]

1st Dimension – flat objects

2nd Dimension – cartoons

3rd Dimension – cubism, 3-D

4th Dimension – 4D - quantum sound and image sounds, into higher memory span loops over time and space distances (complex segmented layers in a smooth flow field). [9]

5th Dimension – 5D - layers of looped thought creates Counterpoint known as parallel thinking[10]. The constant looping span rehearsal formulates Deep Learning practice.



[1]  Kandel, E. R. (2012). The age of insight. New York: Random House.

[2]  Hofstader, D. (1979). Gödel, Escher, Bach: The eternal golden braid. New York: Basic Books. p. 239.

[3] Wayner. P. (Sept. 5, 2022). What is Reinforcement Learning?  How AI Trains Itself. MetaTech Online Events.

[4] Shlain, L. (1991). Art and physics: Parallel visions in space time, light. New York: William Morrow. p. 433.

[5] Adelman E. H. (August 1991). Mechanisms for Motion Perception.  Optics and Photonics News, pp. 24-30.

[6] Rumelhart, D. E., McClelland, J. and the PDP Research Group. (1986).  Parallel distributed processing:  Explorations in the micro structure of cognition.  Cambridge, MA: MIT Press

[7]  Erland, J. K. Erland, (February 4, 1986; copyright TXu 225 862). Contrapuntal Thinking and Definition of Sweeping Thoughts.

[8] Erland, J. K. (Fall 2000). Brain-Based Longitudinal Study Reveals Subsequent High Academic Achievement Gain for Low-Achieving, Low Cognitive Skills, Fourth Grade Students. Journal of Accelerated Learning and Teaching. 25, (3&4) pp.5-48. ERIC ED # 453-553. & # CS 510 558. https://Books.Google.com/jankuypererland page 41,

[9] Learning Visual Groups from Co-occurrences in Space and Time. (2016). Isola, P., Zoran, D., Krishnan, K., Adelson, E. H., International Conference on Learning Representations, workshop paper. Abstract PDF

[10]  Erland, J. K. (1986), (February 4, 1986; copyright TXu 225 862). Contrapuntal Thinking and Definition of Sweeping Thoughts.