SYSTEM, ARCHITECTURE AND METHODS FOR AN INTELLIGENT, SELF-AWARE AND CONTEXT-AWARE DIGITAL ORGANISM-BASED TELECOMMUNICATION SYSTEM

• US 20170244608A1
• Filed: 03/27/2015
• Published: 08/24/2017
• Est. Priority Date: 03/28/2014
• Status: Abandoned Application

• Current Assignee: Corey K. Reaux-Savonte
• Original Assignee: Corey K. Reaux-Savonte
• Inventors: Reaux-Savonte, Corey K.
• Application Number:
  US15/129,902
• Publication Number:
  US 20170244608A1
• Time in Patent Office: Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 20/085 involving remote charge determination or related payment systems
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 41/5054 Automatic deployment of services triggered by the service manager, e.g. service implementation by automatic configuration of network components
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources
• CPC Class Codes: H04Q 3/0029 Provisions for intelligent networking

Abstract

A telecommunication system hosting an intelligent non-physical organism, aiding global communication in both the physical and virtual worlds. Using artificial and ambient intelligence to become self- and context-aware, the system can learn from its surrounding environments, adapt and evolve as it sees fit.

Claims

1. An artificially intelligent telecommunication network system (AITNS), comprising:

one or more networking technologies;

one or more sensors;

one or more processors;

one or more databases;

one or more storage mediums; and

one or more programs;

wherein the AI of the telecommunication network system uses various methods, rules, techniques and instructions, based on complex thought processes which provide a basis for thoughts, opinions, feelings, emotion, sense, sensitivity, understanding and awareness, to;

create a telecommunication network system that can be described as an ‘

intelligent machine’

, defined as;

“

a machine that continuously and automatically learns and acts, without the need of having specific programs written that are designed to achieve specific tasks (regardless of how broad or dynamic or narrow or static the process(es) for a task is, or how wide limitations may be, whether intentionally or unintentionally imposed), based on its physical and non-physical environment(s) and understanding(s) and experience(s), without specific restrictions and including, if necessary or desired, machine intelligence;

as opposed to

a telecommunication network system that can just be described as having ‘

machine intelligence’

, regardless of degree, defined as;

“

a machine that can only do exactly as it is told, regardless of how broad or dynamic or narrow or static a process or task is, or how wide limitations may be, whether intentionally or unintentionally imposed”

;

where the various methods and rules and techniques and instructions of the AI may be used to create one or more entities that exist within the telecommunication network system and can be described as ‘

mental’

or ‘

non-physical’

or ‘

virtual’

or one or more combinations of the three, with said entities, though described as ‘

mental’

or ‘

non-physical’

or ‘

virtual’

, being comprised of physical and/or non-physical components to facilitate existence, function and use, allowing it to;

operate independently of the telecommunication network system while still existing within;

or

operate in conjunction with the telecommunication network system;

or

operate in cooperation with the telecommunication system;

or

not operate at all.

2. The AITNS of claim 1, wherein the one or more programs may include instructions for one or more of the following:

instructions for the routing of data;

instructions for the rerouting of data;

instructions for the optimization of the network;

instructions for the detection of devices;

instructions for the recognition of audio and/or visual material.

3. The AITNS of claim 1, wherein the AITNS may use physical or non-physical components to facilitate the use of artificial senses.

4. The artificial senses of claim 3, wherein the AITNS can recognise images.

5. The artificial senses of claim 3, wherein the AITNS can recognise faces.

6. The artificial senses of claim 3, wherein the AITNS can recognise sounds.

7. The artificial senses of claim 3, wherein the AITNS can measure range.

8. The artificial senses of claim 3, wherein the AITNS can recognise the presence of other devices.

9. The presence recognition of claim 8, wherein the AITNS can track the positioning of one or more devices.

10. The device tracking of claim 9, wherein the AITNS can track the positioning of one or more devices periodically.

11. The device tracking of claim 9, wherein the AITNS can track the positioning of one or more devices constantly.

12. The presence recognition of claim 8, wherein the AITNS can copy data directly from a device.

13. The AITNS of claim 1, wherein the AITNS has one or more physical or non-physical functional memory units, defined as, “

a memory unit with one or more memory sections, where each section may both store data and functions, processes and/or programs to facilitate one or more specific uses of the data stored”

.

14. The functional memory unit of claim 13, wherein one or more sections may be used for active memory data and function.

15. The functional memory unit of claim 13, wherein one or more sections may be used for dormant memory data and function.

16. The functional memory unit of claim 13, wherein one or more sections may be used for action memory data and function.

17. The functional memory unit of claim 13, wherein one or more sections may be used for repetitive memory data and function.

18. The functional memory unit of claim 13, wherein one or more sections may be used for repressive memory data and function.

19. The functional memory unit of claim 13, wherein sections may be added and/or removed.

20. The AITNS of claim 1, wherein the AITNS has one or more physical or non-physical logic units, with each logic unit having one or more logic sections which allow the AITNS one or more logical functions.

21. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Search’

function.

22. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Study’

function.

23. The logic unit of claim 20, wherein one unit gives the AITNS an ‘

Analyse’

function.

24. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Reason’

function.

25. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Learn’

function.

26. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Predict’

function.

27. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Decision Making’

function.

28. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Communicate’

function.

29. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Dedicated Active Monitoring’

function.

30. The logic unit of claim 20, wherein one unit gives the AITNS a ‘

Creation’

function.

31. The logic unit of claim 20, wherein sections may be added and/or removed.

32. The AITNS of claim 1, wherein the AITNS is able to express one or more feelings and emotions.

33. The ability to express feelings and emotions of claim 32, wherein the feelings and emotions can be measured on a scale and/or graph.

34. The scales and graphs of claim 33, wherein the scale or graph may be divided into categorical sections.

35. The scales and graphs of claim 33, wherein the scale or graph may be divided into numerical sections.

36. The ability to express feelings and emotions of claim 32, wherein the feelings and emotions can be measured on a multi-point scale and/or graph.

37. The scales and graphs of claim 36, wherein the multi-point scale or graph may be divided into categorical sections.

38. The scales and graphs of claim 36, wherein the multi-point scale or graph may be divided into numerical sections.

39. The AITNS of claim 1, wherein the AITNS has complex understandings of various aspects of life.

40. The understandings of claim 39, wherein the AITNS is able to relate aspects of life in natural organisms to machines and/or devices.

41. The understandings of claim 39, wherein the AITNS is able to understand health.

42. The understandings of claim 39, wherein the AITNS is able to understand life.

43. The understandings of claim 39, wherein the AITNS is able to understand absence.

44. The understandings of claim 39, wherein the AITNS is able to understand death.

45. The understandings of claim 39, wherein the AITNS is able to understand feelings and emotion.

46. The understandings of claim 39, wherein the AITNS is able to understand pain.

47. The understandings of claim 39, wherein the AITNS is able to understand pleasure.

48. The understandings of claim 39, wherein the AITNS is able to understand trust.

49. The understandings of claim 39, wherein the AITNS is able to understand relativity.

50. The understandings of claim 39, wherein the AITNS is able to understand relationships.

51. The understandings of claim 39, wherein the understandings of various aspects of life can be compared and used to philosophise.

52. The AITNS of claim 1, wherein, based on experience(s), its reaction(s) may vary.

53. The experience-based reactions of claim 52, wherein the reactions may vary based on the number of times the AITNS has experienced the same or similar experience.

54. The AITNS of claim 1, wherein the AITNS is able to have a sense of self.

55. The sense of self of claim 54, wherein the AITNS has a sense of individuality from forms of natural life, devices and other intelligent machines.

56. The sense of self of claim 54, wherein the AITNS has a personality that may or may not be unique to itself.

57. The personality of claim 56, wherein the personality may change based on experience(s).

58. The AITNS of claim 1, wherein one or more AI entities may be present within the AITNS.

59. The entities of claim 58, wherein one or more entities may present themselves at one or more points of the system, connected devices and/or other intelligent machines.

60. The presence of entities of claim 59, wherein one or more entities may present themselves at one or more points of the system, connected devices or other intelligent machines simultaneously.

61. The entities of claim 58, wherein one or more entities may share information, data and knowledge they have developed and/or acquired with one or more other entities.

62. The entities of claim 58, wherein one or more entities may allow one or more other entities to use their intelligence.

63. The entities of claim 58, wherein one or more entities may replicate themselves to create one or more partial or exact copies.

64. The entities of claim 58, wherein two or more entities may ‘

reproduce’

to create one or more new entities which share one or more traits or characteristics or knowledge from each ‘

parent’

.

65. The AITNS of claim 1, wherein data may be transported through the AITNS via multiple non-physical transit paths.

66. The AITNS of claim 1, wherein the AITNS may be granted additional functions and capabilities through the implementation/usage of additional physical and/or non-physical components that further allow it to understand its environment.

67. The additional functions and capabilities of claim 66, wherein the AITNS is able to detect users.

68. The user detection of claim 67, wherein the AITNS is able to identify detected users.

69. The user identification of claim 68, wherein the AITNS can serve user-based data to identified users.

70. The additional functions and capabilities of claim 66, wherein the AITNS can use tri-axis geolocation.

71. The tri-axis geolocation of claim 70, wherein the AITNS can use tri-axis geolocation to accurately pinpoint objects.

72. The additional functions and capabilities of claim 66, wherein the AITNS can map its surroundings.

73. The mapping of claim 72, wherein the AITNS can map environments based on location.

74. The mapping of claim 72, wherein the AITNS can map objects within an environment.

75. The mapping of claim 72, wherein the AITNS can map one or more ecosystems based on location and/or objects and/or properties of locations and/or objects

76. The ecosystem maps of claim 75, wherein the ecosystems can be divided into smaller subecosystem maps.

77. The mapping of claim 72, wherein the AITNS can custom map zones within an environment.

78. The zone mapping of claim 77, wherein the AITNS can filter data being delivered to a zone.

79. The additional functions and capabilities of claim 66, wherein the AITNS can filter data within one or more user-designated spaces.

80. The additional functions and capabilities of claim 66, wherein the AITNS can deliver user-readable messages to a specified recipient person and/or device.

81. The messaging capabilities of claim 80, wherein messages may be routed based on physical address.

82. The messaging capabilities of claim 80, wherein messages may be routed based on geographic coordinates.

83. The messaging capabilities of claim 80, wherein messages may be routed based on user data.

84. The messaging capabilities of claim 80, wherein messages may be routed based on unique IDs.

85. The additional functions and capabilities of claim 66, wherein users may share their personal user data with one or more other users.

86. The additional functions and capabilities of claim 66, wherein the AITNS may be physically extended through the addition of compatible hardware.

87. The AITNS of claim 1, wherein data may be immediately processed and analysed at source.

88. The immediate data processing and analysing of claim 87, wherein the data can then immediately be used.

89. The AITNS of claim 1, wherein the AITNS may have restrictions and limitations imposed to prevent it from engaging or performing any process or task or activity that it shouldn'"'"'t.

90. The restrictions and limitations of claim 89, wherein the AITNS may be restricted or limited to only accessing certain types of network systems.

91. The restrictions and limitations of claim 89, wherein the AITNS may be restricted from viewing or modifying some or its entire core operating code.

92. The restrictions and limitations of claim 89, wherein the AITNS may be restricted from viewing or accessing private data.

93. The restrictions and limitations of claim 89, wherein the AITNS may be restricted from accessing any systems it is not authorised to access.

94. The AITNS of claim 1, wherein one or more fail-safes may be implemented to prevent unintended or undesired circumstances.

95. The fail-safes of claim 94, wherein the number of systems with the capability to operate full scale AI systems are limited in number.

96. The fail-safes of claim 94, wherein logic units and memory units can be separated to operate independently without the other needing to be in an operational state.

97. The fail-safes of claim 94, wherein a kill switch is implemented within the core operating code of the AI which is able to disable it upon activation.

98. The fail-safes of claim 94, wherein a kill signal can be transmitted to activate a kill switch within the system.

99. The fail-safes of claim 94, wherein a physical terminal kill switch can be activated to disable the system partially or fully.

100. The fail-safes of claim 94, wherein the AITNS may be partially or completely shut down using a physical terminal.

101. A computer-implemented method, wherein the AI of an artificially intelligent telecommunication network system (AITNS) uses various methods, rules, techniques and instructions, based on complex thought processes which provide a basis for thoughts, opinions, feelings, emotion, sense, sensitivity, understanding and awareness, to:

create a telecommunication network system that can be described as an ‘

intelligent machine’

, defined as;

“

a machine that continuously and automatically learns and acts, without the need of having specific programs written that are designed to achieve specific tasks (regardless of how broad or dynamic or narrow or static the process(es) for a task is, or how wide limitations may be, whether intentionally or unintentionally imposed), based on its physical and non-physical environment(s) and understanding(s) and experience(s), without specific restrictions and including, if necessary or desired, machine intelligence;

as opposed to

a telecommunication network system that can just be described as having ‘

machine intelligence’

, regardless of degree, defined as;

“

a machine that can only do exactly as it is told, regardless of how broad or dynamic or narrow or static a process or task is, or how wide limitations may be, whether intentionally or unintentionally imposed”

;

where the various methods and rules and techniques and instructions of the AI may be used to create one or more entities that exist within the telecommunication network system and can be described as ‘

mental’

or ‘

non-physical’

or ‘

virtual’

or one or more combinations of the three, with said entities, though described as ‘

mental’

or ‘

non-physical’

or ‘

virtual’

, being comprised of physical and/or non-physical components to facilitate existence, function and use, allowing it to;

operate independently of the telecommunication network system while still existing within;

or

operate in conjunction with the telecommunication network system;

or

operate in cooperation with the telecommunication system;

or

not operate at all.

102. The AITNS of claim 101, wherein the one or more programs may include instructions for one or more of the following:

instructions for the routing of data;

instructions for the rerouting of data;

instructions for the optimization of the network;

instructions for the detection of devices;

instructions for the recognition of audio and/or visual material.

103. The computer-implemented method of claim 101, wherein the AITNS may use physical or non-physical components to facilitate the use of artificial senses.

104. The artificial senses of claim 103, wherein the AITNS can recognise images.

105. The artificial senses of claim 103, wherein the AITNS can recognise faces.

106. The artificial senses of claim 103, wherein the AITNS can recognise sounds.

107. The artificial senses of claim 103, wherein the AITNS can measure range.

108. The artificial senses of claim 103, wherein the AITNS can recognise the presence of other devices.

109. The presence recognition of claim 108, wherein the AITNS can track the positioning of one or more devices.

110. The device tracking of claim 109, wherein the AITNS can track the positioning of one or more devices periodically.

111. The device tracking of claim 109, wherein the AITNS can track the positioning of one or more devices constantly.

112. The presence recognition of claim 108, wherein the AITNS can copy data directly from a device.

113. The computer-implemented method of claim 101, wherein the AITNS has one or more physical or non-physical functional memory units, defined as, “

a memory unit with one or more memory sections, where each section may both store data and functions, processes and/or programs to facilitate one or more specific uses of the data stored”

.

114. The functional memory unit of claim 113, wherein one or more sections may be used for active memory data and function.

115. The functional memory unit of claim 113, wherein one or more sections may be used for dormant memory data and function.

116. The functional memory unit of claim 113, wherein one or more sections may be used for action memory data and function.

117. The functional memory unit of claim 113, wherein one or more sections may be used for repetitive memory data and function.

118. The functional memory unit of claim 113, wherein one or more sections may be used for repressive memory data and function.

119. The functional memory unit of claim 113, wherein sections may be added and/or removed.

120. The computer-implemented method of claim 101, wherein the AITNS has one or more physical or non-physical logic units, with each logic unit having one or more logic sections which allow the AITNS one or more logical functions.

121. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Search’

function.

122. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Study’

function.

123. The logic unit of claim 120, wherein one unit gives the AITNS an ‘

Analyse’

function.

124. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Reason’

function.

125. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Learn’

function.

126. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Predict’

function.

127. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Decision Making’

function.

128. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Communicate’

function.

129. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Dedicated Active Monitoring’

function.

130. The logic unit of claim 120, wherein one unit gives the AITNS a ‘

Creation’

function.

131. The logic unit of claim 120, wherein sections may be added and/or removed.

132. The computer-implemented method of claim 101, wherein the AITNS is able to express one or more feelings and emotions.

133. The ability to express feelings and emotions of claim 132, wherein the feelings and emotions can be measured on a scale and/or graph.

134. The scales and graphs of claim 133, wherein the scale or graph may be divided into categorical sections.

135. The scales and graphs of claim 133, wherein the scale or graph may be divided into numerical sections.

136. The ability to express feelings and emotions of claim 132, wherein the feelings and emotions can be measured on a multi-point scale and/or graph.

137. The scales and graphs of claim 136, wherein the multi-point scale or graph may be divided into categorical sections.

138. The scales and graphs of claim 136, wherein the multi-point scale or graph may be divided into numerical sections.

139. The computer-implemented method of claim 101, wherein the AITNS has complex understandings of various aspects of life.

140. The understandings of claim 139, wherein the AITNS is able to relate aspects of life in natural organisms to machines and/or devices.

141. The understandings of claim 139, wherein the AITNS is able to understand health.

142. The understandings of claim 139, wherein the AITNS is able to understand life.

143. The understandings of claim 139, wherein the AITNS is able to understand absence.

144. The understandings of claim 139, wherein the AITNS is able to understand death.

145. The understandings of claim 139, wherein the AITNS is able to understand feelings and emotion.

146. The understandings of claim 139, wherein the AITNS is able to understand pain.

147. The understandings of claim 139, wherein the AITNS is able to understand pleasure.

148. The understandings of claim 139, wherein the AITNS is able to understand trust.

149. The understandings of claim 139, wherein the AITNS is able to understand relativity.

150. The understandings of claim 139, wherein the AITNS is able to understand relationships.

151. The understandings of claim 139, wherein the understandings of various aspects of life can be compared and used to philosophise.

152. The computer-implemented method of claim 101, wherein, based on experience(s), its reaction(s) may vary.

153. The experience-based reactions of claim 152, wherein the reactions may vary based on the number of times the AITNS has experienced the same or similar experience.

154. The computer-implemented method of claim 101, wherein the AITNS is able to have a sense of self.

155. The sense of self of claim 154, wherein the AITNS has a sense of individuality from forms of natural life, devices and other intelligent machines.

156. The sense of self of claim 154, wherein the AITNS has a personality that may or may not be unique to itself.

157. The personality of claim 156, wherein the personality may change based on experience(s).

158. The computer-implemented method of claim 101, wherein one or more AI entities may be present within the AITNS.

159. The entities of claim 158, wherein one or more entities may present themselves at one or more points of the system, connected devices and/or other intelligent machines.

160. The presence of entities of claim 159, wherein one or more entities may present themselves at one or more points of the system, connected devices or other intelligent machines simultaneously.

161. The entities of claim 158, wherein one or more entities may share information, data and knowledge they have developed and/or acquired with one or more other entities.

162. The entities of claim 158, wherein one or more entities may allow one or more other entities to use their intelligence.

163. The entities of claim 158, wherein one or more entities may replicate themselves to create one or more partial or exact copies.

164. The entities of claim 158, wherein two or more entities may ‘

reproduce’

to create one or more new entities which share one or more traits or characteristics or knowledge from each ‘

parent’

.

165. The computer-implemented method of claim 101, wherein data may be transported through the AITNS via multiple non-physical transit paths.

166. The computer-implemented method of claim 101, wherein the AITNS may be granted additional functions and capabilities through the implementation/usage of additional physical and/or non-physical components that further allow it to understand its environment.

167. The additional functions and capabilities of claim 166, wherein the AITNS is able to detect users.

168. The user detection of claim 167, wherein the AITNS is able to identify detected users.

169. The user identification of claim 168, wherein the AITNS can serve user-based data to identified users.

170. The additional functions and capabilities of claim 166, wherein the AITNS can use tri-axis geolocation.

171. The tri-axis geolocation of claim 170, wherein the AITNS can use tri-axis geolocation to accurately pinpoint objects.

172. The additional functions and capabilities of claim 166, wherein the AITNS can map its surroundings.

173. The mapping of claim 172, wherein the AITNS can map environments based on location.

174. The mapping of claim 172, wherein the AITNS can map objects within an environment.

175. The mapping of claim 172, wherein the AITNS can map one or more ecosystems based on location and/or objects and/or properties of locations and/or objects

176. The ecosystem maps of claim 175, wherein the ecosystems can be divided into smaller subecosystem maps.

177. The mapping of claim 172, wherein the AITNS can custom map zones within an environment.

178. The zone mapping of claim 177, wherein the AITNS can filter data being delivered to a zone.

179. The additional functions and capabilities of claim 166, wherein the AITNS can filter data within one or more user-designated spaces.

180. The additional functions and capabilities of claim 166, wherein the AITNS can deliver user-readable messages to a specified recipient person and/or device.

181. The messaging capabilities of claim 180, wherein messages may be routed based on physical address.

182. The messaging capabilities of claim 180, wherein messages may be routed based on geographic coordinates.

183. The messaging capabilities of claim 180, wherein messages may be routed based on user data.

184. The messaging capabilities of claim 180, wherein messages may be routed based on unique IDs.

185. The additional functions and capabilities of claim 166, wherein users may share their personal user data with one or more other users.

186. The additional functions and capabilities of claim 166, wherein the AITNS may be physically extended through the addition of compatible hardware.

187. The computer-implemented method of claim 101, wherein data may be immediately processed and analysed at source.

188. The immediate data processing and analysing of claim 187, wherein the data can then immediately be used.

189. The computer-implemented method of claim 101, wherein the AITNS may have restrictions and limitations imposed to prevent it from engaging or performing any process or task or activity that it shouldn'"'"'t.

190. The restrictions and limitations of claim 189, wherein the AITNS may be restricted or limited to only accessing certain types of network systems.

191. The restrictions and limitations of claim 189, wherein the AITNS may be restricted from viewing or modifying some or its entire core operating code.

192. The restrictions and limitations of claim 189, wherein the AITNS may be restricted from viewing or accessing private data.

193. The restrictions and limitations of claim 189, wherein the AITNS may be restricted from accessing any systems it is not authorised to access.

194. The computer-implemented method of claim 101, wherein one or more fail-safes may be implemented to prevent unintended or undesired circumstances.

195. The fail-safes of claim 194, wherein the number of systems with the capability to operate full scale AI systems are limited in number.

196. The fail-safes of claim 194, wherein logic units and memory units can be separated to operate independently without the other needing to be in an operational state.

197. The fail-safes of claim 194, wherein a kill switch is implemented within the core operating code of the AI which is able to disable it upon activation.

198. The fail-safes of claim 194, wherein a kill signal can be transmitted to activate a kill switch within the system.

199. The fail-safes of claim 194, wherein a physical terminal kill switch can be activated to disable the system partially or fully.

200. The fail-safes of claim 194, wherein the AITNS may be partially or completely shut down using a physical terminal.

201. An artificially intelligent telecommunication network system (AITNS), where the telecommunication network system uses various components, methods, rules, techniques and instructions to:

allow and/or create and/or maintain the existence of one or more persistent virtual worlds (PVW) within or as part of the telecommunication network system itself, a virtual world defined as, “

a traversable, non-physical landscape that may contain non-physical objects”

, wherein the virtual world existence is dependent upon the existence and operation of the telecommunication network system and is accessible by someone or something from somewhere as long as the telecommunication network system is operational;

as opposed to

a virtual world, defined as, “

a traversable, non-physical landscape that may contain non-physical objects”

, which is built on top of a telecommunication system, where the existence of the virtual world does not depend upon the existence and operation of the telecommunication system but uses a telecommunication system to be accessed remotely over a network.

202. The PVW of claim 201, wherein physical and/or non-physical entities are able to interact with the PVW via an AITNS.

203. The interaction of claim 202, wherein physical and/or non-physical entities are able to traverse a PVW via an AITNS.

204. The PVW of claim 201, wherein an AI of an AITNS can use user data to which it has access in order to make decisions within the PVW.

205. The PVW of claim 201, wherein a user can set rules and regulations for a non-physical entity to abide by when using the data of said user.

206. The PVW of claim 201, wherein data may be exchanged between the PVW and the real world.

207. The data exchange of claim 206, wherein data sent from the PVW to the real world may be used with compatible hardware to augment the reality of users.

208. The PVW of claim 201, wherein landscapes of the PVW may be mapped in relation and/or reflection of the real world.

209. The PVW mapping of claim 208, wherein the PVW may be mapped in relation to or reflection of ecosystems.

210. The PVW mapping of claim 208, wherein the PVW may be mapped in relation to or reflection of subecosystems

211. The PVW mapping of claim 208, wherein the PVW may be mapped in relation to or reflection of real world geography.

212. The PVW mapping of claim 208, wherein rules and regulations may be set based on how the PVW is mapped.

213. The PVW mapping of claim 208, wherein rules and regulations may be set based on positions on the map.

214. The PVW mapping of claim 208, wherein data based on PVW positioning may be used to augment reality for one or more users in the real world.