The present disclosure describes an automated, cognitive based computing system using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, configured to dynamically manage transmission of information between communication nodes. The communication nodes comprise orbital nodes positioned in orbit above earth and terrestrial nodes coupled with earth interconnected via a hybrid mesh network topology. One or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, determine a target terrestrial node to receive information initially stored on a first orbital node; determine transmission conditions between the target terrestrial node and the first orbital node based on output signals from sensors; dynamically determine whether transmission conditions between the first orbital node and the target terrestrial node prevent optical transmission of the information directly from the first orbital node to the target terrestrial node; and, responsive to a determination that transmission conditions prevent optical transmission of the information to the target terrestrial node from the first orbital node, automatically transmit the information along an alternate route between the first orbital node and the target terrestrial node, wherein the alternate route includes transmission between some orbital node and an alternative target terrestrial node other than the target terrestrial node.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An automated, cognitive based computing system using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, configured to dynamically manage transmission of information via optical communication signals between orbital and terrestrial communication nodes interconnected via a hybrid mesh network topology, the communication nodes comprising orbital nodes positioned in orbit above earth and terrestrial nodes coupled with earth, the system comprising: one or more sensors configured to dynamically generate output signals conveying information related to transmission conditions between nodes; and one or more physical computer processors configured by computer readable instructions to: automatically determine a target terrestrial node to receive information initially stored on a first orbital node; dynamically determine transmission conditions between the target terrestrial node and the first orbital node based on the output signals; determine whether transmission conditions between the first orbital node and the target terrestrial node prevent optical transmission of the information directly from the first orbital node to the target terrestrial node; and responsive to a determination that transmission conditions prevent optical transmission of the information to the target terrestrial node from the first orbital node, automatically transmit the information along an alternate route between the first orbital node and the target terrestrial node, wherein the alternate route includes transmission between some orbital node and an alternative target terrestrial node other than the target terrestrial node interconnected via a hybrid mesh network topology. 2. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions are configured such that transmission between some orbital node and the alternative target terrestrial node includes transmission from the first orbital node to the alternative terrestrial node interconnected via a hybrid mesh network topology. 3. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, are configured such that transmission between some orbital node and the alternative target terrestrial node includes transmission from a second orbital node to the alternative terrestrial node interconnected via a hybrid mesh network topology. 4. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, dynamically determine transmission conditions between the transmitting orbital node and the alternative terrestrial node interconnected via a hybrid mesh network topology. 5. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, are configured such that the information initially stored on the first orbital node is dynamically communicated to other orbital nodes and/or terrestrial nodes via optical communication signals interconnected via a hybrid mesh network topology. 6. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions , are configured such that the information initially stored on the first orbital node is not communicated to other orbital nodes and/or terrestrial nodes via radio frequency (RF) signals. 7. The system of claim 1, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions , are configured such that the transmission conditions include one or more of ambient weather conditions or operational conditions of individual nodes interconnected via a hybrid mesh network topology. 8. An optical communication system composed of automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, configured to automaticaIIy manage transmission of information between communication nodes interconnected via a hybrid mesh network topology, the system comprising: orbital nodes positioned in orbit above earth configured to communicate with each other and terrestrial nodes by transmitting and receiving optical communication signals; terrestrial nodes coupled with earth configured to dynamically communicate with each other and the orbital nodes by transmitting and receiving optical communication signals, the terrestrial nodes including a target terrestrial node and an alternative target terrestrial node; and one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions configured by computer readable instructions to facilitate transmission and receipt of the optical communication signals by the orbital nodes and the terrestrial nodes such that, responsive to transmission conditions preventing optical communication signals from communicating information initially stored on a first orbital node to the target terrestrial node directly from the first orbital node, the one or more physical computer processors dynamically facilitate transmission of the information along an alternate route between the first orbital node and the target terrestrial node, wherein the alternate route includes transmission of optical signals between some orbital node and the alternative target terrestrial node interconnected via a hybrid mesh network topology. 9. The system of claim 8, wherein the orbital nodes and the terrestrial nodes are configured such that the optical communication signals are laser light beams. 10. The system of claim 8, wherein the orbital nodes and the terrestrial nodes are configured such that the optical communication signals have a frequency between about 186 THz and about 197 THz. 11. The system of claim 8, wherein the orbital nodes and the terrestrial nodes are configured such that the optical communication signals have a wavelength of between about 1500 nm and about 1650 nm. 12. The system of claim 8, wherein the orbital nodes are satellites. 13. The system of claim 8, wherein the one or more automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions are configured such that the transmission conditions include ambient weather conditions. 14. A method for dynamically managing transmission of information between communication nodes based on automated, cognitive based physical computing processors, using artificial intelligence (AI) and machine learning algorithms to sense, predict, and infer network conditions, the communication nodes comprising orbital nodes positioned in orbit above earth and terrestrial nodes coupled with earth interconnected via a hybrid mesh network topology, the method comprising: dynamically generating output signals conveying information related to transmission conditions between nodes; determining a target terrestrial node to receive information initially stored on a first orbital node; determining transmission conditions between the target terrestrial node and the first orbital node based on the output signals; determining whether transmission conditions between the first orbital node and the target terrestrial node prevent optical transmission of the information directly from the first orbital node to the target terrestrial node; and responsive to a determination that transmission conditions prevent optical transmission of the information to the target terrestrial node from the first orbital node, transmitting the information via optical communication signals dynamically along an alternate route between the first orbital node and the target terrestrial node, wherein the alternate route includes transmission of optical communication signals between some orbital node and an alternative target terrestrial node other than the target terrestrial node.