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Since its introduction more than six decades ago by Claude E. Shannon information theory has guided with two
performance bounds, namely source-entropy H and channel capacity C, the design of sourced intelligence-space
compressors for communication systems, where the units of intelligence-space are 'mathematical' binary digit (bit) units
of a passing of time uncertainty nature. Recently, motivated by both a real-world radar problem treated in the first part of
the present paper series, and previous uncertainty/certainty duality studies of digital-communication and quantizedcontrol
problems by the author, information theory was discovered to have a 'certainty' time-dual that was named
latency theory. Latency theory guides with two performance bounds, i.e. processor-ectropy K and sensor consciousness
F the design of processing intelligence-time compressors for recognition systems, where the units of intelligence-time
are 'mathematical' binary operator (bor) units of a configuration of space certainty nature. Furthermore, these two
theories have been unified to form a mathematical latency-information theory (M-LIT) for the guidance of intelligence
system designs, which has been successfully applied to real-world radar. Also recently, M-LIT has been found to have a
physical LIT (P-LIT) dual that guides life system designs. This novel physical theory addresses the design of motion
life-time and retention life-space compressors for physical signals and also has four performance bounds. Two of these
bounds are mover-ectropy A and channel-stay T for the design of motion life-time compressors for communication
systems. An example of a motion life-time compressor is a laser system, inclusive of a network router for a certainty, or
multi-path life-time channel. The other two bounds are retainer-entropy N and sensor scope I for the design of retention
life-space compressors for recognition systems. An example of a retention life-space compressor is a silicon
semiconductor crystal, inclusive of a leadless chip carrier for an uncertainty, or noisy life-space sensor. The eight
performance bounds of our guidance theory for intelligence and life system designs will be illustrated with practical
examples. Moreover, a four quadrants (quadrants I and III for the two physical theories and quadrants II and IV for the
two mathematical ones) LIT revolution is advanced that highlights both the discovered dualities and the fundamental
properties of signal compressors leading to a unifying communication embedded recognition (CER) system architecture.
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