This citizen proposal suggests a technology and real-world application for training citizens to secure our borders just as safely (if not safer) but with fewer resources, with technology and hardware securely provided with love by Nebulous Labs.
border security, jobs
BRIEF: A new application of aural encryption allows generating a stream of musical notes which represent a small pool of known, variable actions. This technology then is applied in this proposal in combination with subjects that have a strong musical recall to result in faster communication rates over a novel radio insertion, allowing such subjects to instinctively react from audio cues. Finally, our advanced Swordsman AI is used to analyze subject environments and dictate bodily actions via auditory responses with a delay of less than 100ms.
To view our “Encryption: Concept to Sound” proposal, click [here].
Sourced from high-skill video game players, cross referenced to remove any known streamers. Citizens with SNPs Rs4630083, Rs9854612, and Rs13146789 have shown a significant presence in projected candidates.
A single DCVR-01 circular training space is required per subject, styled to a depth of twelve meters as our patent-pending Dojo Field. Arranged in a full circle around the subject, up to 48 Training Pods may be placed. As the training proceeds, these Pods may be moved further out. Subjects should also be fit with a virtual reality headset compatible with Fruit Trainer.
Each Training Pod serves as a Fruit Generator within our Fruit Trainer simulation, and subjects perceive them as holes through which fruit¹ may be forcefully ejected. Fruit Trainer plays like a game, through which a subject may see our success confidence for their training as a “score” as they improve and progress.
Each training session begins with an EHLO whistle, necessary for Pavlovian priming. Fruits are then launched from Training Pods at an increasing frequency, requiring the subject to “slice” through each fruit in the air using their VRS². As each fruit is launched, metadata for that launch is encoded into a note which plays over the subject’s headset. The encryption of this metadata can be found outlined in full in the Appendix A files, and a sample training model has been provided (at approximately 30% efficiency of our latest-generation models) for development.
Within this model, the loudness, pitch, timbre, and duration are used to encode spacial information for rotational angle, height, distance, and blade angle. Blade speed is acutely dictated through the flow or speed of neighboring nodes, and movement can be dictated through “dummy” notes placed out of reach based on prior movement patterns. A frequency shift keyring can be used to “re-train” subjects if more efficient encoding schemes are discovered.
Training is defined complete when a subject is able to complete all rounds without visual input. One on one meetings for subjects with certified master swordsmen or a visual representation of our Swordsman AI are also available from within Fruit Trainer, and subjects may be assigned a sensei of the administrator’s choice. We expect training to complete in approximately 1–3 years, pending individual differences in musical recall and muscle memory retention.
Upon successful training, subjects may be fitted with a persistent two-way radio and offered one of many roles under border security. If selected as a skirmisher or scout, our swordmaster AI can analyze nearby radio waves to build an exact model of nearby solids and provide predictive audio dictating how a subject should immediately act. This information is relayed to the subject instantly via an always-connected audio stream.
This system results in more safety for border patrol in general due to the effectiveness of our master swordsman AI in skirmishes (which is predicted to reduce border casualties by at least 30% within the first year!), but also provides an added sense of 360-degree awareness for everyone protecting us from the Outside in all situations.
Since no visual information is necessary for action, subjects may be physically present on the border or dictating actions remotely through a BDbot. Swords were specifically chosen as a weapon due to their existing BDbot integrations, their cost compared to more resource-heavy weapons, their attack length, and their efficiency within the control of a master. BDbots that don’t have to restock supplies should be capable of cutting more than 60% off their low-value time, leading to longer and more thorough patrols and fewer blindspots.
PRIMARY DATA USES
In parallel with the first subjects to complete training, we plan to begin training a separate locomotion model for border patrol use based on human audio-physical input-output measured from subjects on the job. We expect a local singularity after approximately 300,000 man-hours, and this model will be shared with the Department of Borders at no additional cost. At that point, DoB will have an exclusive resale contract drawn up for 4 years.
OTHER DATA USES
Other users have submitted the following additional data uses. They are not part of the original proposal and are provided courtesy of PROP.
– [Pec cell sale]—This training simulation looks like it’ll be a rigorous…
– [Border stream] — Since we’re planning on having more BDbots on the…
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Our border has long since been a terrifying reminder of the Outside. A large border means a large surface area and attack vector, which means more moving pieces that can be made vulnerable. This proposal suggests a solution that normalizes several job roles and provides a streamlined approach to longevity through standardization, increased efficiency, and lower costs. Lower costs create more jobs, and more jobs securing the border means more security for the rest of us, too.
¹ Fruit used includes, but is not limited to, apples, oranges, peaches, ash balls, coconuts, mangos, avocados, bananas, apricots, blueberries, charberries, strawberries, and blackberries. “Fruit” not guaranteed to be fruit. We reserve the rights to change fruit used at any time.
² VRS, or Virtual Reality Swords are weighted batons for building muscle memory. They have no sharp edge, ensuring the necessary safety of our subjects. Cost to print is approximately 1 wood unit per 50 VRS, and 1 steel unit per 600 VRS.
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