Generative Encoding

1. This presentation opens an exploration of the notion that a EDO may be generated by more than one generative structure. The Pile encoding “degeneracy” (having more than one possible state) may be further constrained by some type of “non-locality” (group utility function) so that, within a specific context, the selected generative structure has two optimization processes. The first creates a sufficient EDO that by itself can perform the proper services such as “expression”, “accounting transmission”, “re-creation”. The second creates EDOs within a community where transmission rates are reduced due to prior specification, within the community, of elements of the encoding. Questions to be answered. Is EDO encoding actually degenerate? I am assuming that the answer is yes. What performance issues arise to compare the class of all EDO encoding? Individual Pile encoding may not “benefit” from “prior knowledge”, however we are attempting to provide “expression”, “accounting transmission”, “re-creation” services. Also, the encoding of complex (audio and visual) data may have optimization functions that are best defined over a large number of individual fame encoding.

2. Generative Encapsulated Digital Object • Service Interface based on SOA Reference Model • Generative Encoding compresses/makes-private/instruments Service Interface Generative Encoding Note, we may wish to “make-private” within a trust circle, and for a limited duration. The reasons are numerous, but we need to talk about each of these reasons.

3. On “making-private” within a trust circle, and for a limited duration. • The trust circle could be the “extent to which a digital property has been licensed for use”. The term “useExtent” is an essential part of the KravTek branding. • UseExtent following the notion of trust circle, and may have an underlying encodingCore • EncodingCores provide a type of real time access policy, since an entire trust circle will undergo periodic revision of encodingCores. The benefits for redevelopment of a community encodingCores include • Security: an encodingCore can be developed specifically to hid, at least in real time, from anyone not in the trust circle that ability to interpret specific generative structure. Effect to de-code may be significant. • Commonalities: It is possible that the structure of a specific interaction will have important commonalities when measured in the encodingCore. • Utility function driven optimization: Optimization is often locally defined (such as the plain vanilla Pile encoding ), and yet this local definition is not likely optimal in terms of a class of global utility functions. The utility functions themselves may change over time.

4. “expression”, “accounting transmission”, “re-creation” services The encodingCore service interface will respond to the following: Expression: The encoded source will express as a digital stream that has the same “play” properties as the encoded source. Accounting transmission: All expression and re-creation events are logged internally to the EDO (expression history). The transmission of this log is made to the KOS service interface. Re-creation: Any EDO can be expressed of the purpose of changing the encoding. This may happen as part of an optimization of the common encodingCore available to a community or trust circle.

5. Service Interface Service Interface Service Interface Generative Encoding Generative Encoding Generative Encoding Evolving encodingCore • Stratified Architecture • (the ideal) • Within a given trust circle and for a period of time, a single compression dictionary is shared. • EDO encodingCore is shared in common between participants while transmissions between collaborating trust circles are occurring. This common core acts like a natural language, and has the ability to generate any digital product * * It is entirely possible that two different cores might generate the same EDO, so there is a question of selection based on shared constraints within a community of EDOs.

6. Service Interface Service Interface EncodingCore Service Interfaces define a standard format for the expression of data, and gives to these formats an expected interpretation. The encodingCore communicates, via its own service interface, with other encodingCores. The communication optimizes certain functions related to IP property, compression and privacy. Stratification means that no direct interaction (entanglement) develops between the EDO (KOS) service interface and the EDO (TOS) interface occurs.

7. Service Interface Service Interface Service Interface Generative Encoding Generative Encoding Generative Encoding External facing service interface(s) requires KOS (knowledge operating systems) architecture, which we are not addressing in this presentation. However, a set of common principles are to be enforced. These common principles are required so that we simplify the conceptualization of stratified theory. The difference between KOS and TOS (transaction operating system) is that in the KOS the invariant encoding mechanism is considered to be in the minds of humans, whereas in the TOS the encoding mechanism is in the encodingCore.

8. To use or not to use? In any of the steps discussed in : http://www.pilesys.com/new/Documents/TheOriginalPileEngineDemystified.pdf There are more than one choices, and thus there are choice points and “reasons why” decisions might be made one way of another. The choice points can be informed by service decisions, following a generalization of some of the OASIS SOA standards. The actual choice can be made based on human interjection or by some computed optimization made by the TOS (transaction operating system)

9. A first task is to exam the current implementation, which I assume is indicated here. EDO

10. What does managed mean ? By layers, do we mean that each layer has an interface that is both up – down and horizontal ? What is the function(s) of the space wrapper? Here is my critical question. If we assume that each EDO “has a space”, we mean that a specific lattice has been created that is generative of a video (for example). Given a different EDO, encoding a different video; are there obvious endpoints (whose selection is seen as a specific invariance selected to grow the generative structure). Given only local information, are there parts of the relational structure that are in common between the two spaces? Second question: Can the generative encoding be constructed so that we have an increasing “common core” shared by transmissions with a trust circle.