https://www.grassland.network/ https://github.com/grasslandnetwork/ (version 0.1)
Grassland is an anonymous, peer-to-peer network of open source, computer vision software that can take any video feed and gives everyone on the network a permissionless, (politically) stateless, and indelible public record of the activities of any person, by allowing one to view any region of the globe in a 3D "god view" mode similar to the games SimCity® or Civilization®, but with the ability to rewind time and view their entire history.
Nash EquilibriumIt's structured so as to be inescapable by any one party (preventing them forming an asymmetry) as long as there remain other parties acting in their own self-interest (Nash Equilibrium
[1]).
2D To 3DNo sensors, SLAM or point clouds needed. Each instance of the software acts as a contributing node in the network. By giving a node access to any fixed perspective, 2-D camera feed, it converts it into a 3-D, searchable, simulated re-creation of events in the part of the world it's viewing using OpenStreetMap 3D. It's a dispassionate, non-human, semi-omniscient, public frame of reference that also incentivises nodes with a digital, financial reward.
Proof-of-WorkCamera frames aren't stored in the database, just the information gathered from each frame, which includes among other things object identification, object geospatial information, a timestamp, a SHA hash of the frame and a
hash chain of the activations of certain hidden layers[2] of the CNN during object detection. The frames themselves are only needed for a little while after for random confirmations and then they can be discarded. It's astronomically improbable to have hashed those hidden activations into the correct digest unless those hidden layers were actually computed, the "proof-of-work".
Grassland's digital coin is a fungible cryptographic token backed by this proof of AI computation.Steadily Increasing Detail And DifficultyCurrent computational requirements are low as it's only necessary to detect and track people and cars now but that will increase over time.
Every few months, nodes must download the next version of the network's deep learning model. Which will recognize and track more objects and activities in order to discern more and more about those objects. So over time the network becomes an increasingly accurate and harder to fabricate representation of the real world.
Why The Heck Did You Build This?A few months ago, I just wanted to turn my neighbourhood into a game of Civilization. But I needed a way to incentivize other people to join without having to trust their cameras and that they weren't faking data... Having designed a proof-of-work for computer vision, I realized we could do so much more... Grassland takes such a unilateral and fait accompli approach to data as an answer to the power asymmetry enjoyed by corporations and governments with respect to all the data they have on the public. This only serves to encourage social manipulation, lies, propaganda, fake news and a trickle-down reality. Data is too valuable for powerful organizations not to hoard and use to their advantage. Well-meaning consumer data laws only protect us from ethical organizations and organizations who just lack the resources to skirt them, but not from the hackers who've already taken that data. Neither is there any conceivable benefit from the public having limited or warped information about our ever changing and complex political, social and (rapidly being destroyed) natural environment. So the only option left is to "burn the forest", "scorch the earth" and level the playing field, as it were, in a manner that's inescapable. While also providing an economic incentive to do so and seeing if it catches on.
For more information ->
https://www.grassland.network/ &&
https://github.com/grasslandnetwork/[1].
https://en.wikipedia.org/wiki/Nash_equilibrium [2].
https://www.spiedigitallibrary.org/ContentImages/Journals/NEUROW/5/1/011008/FigureImages/NPH_5_1_011008_f002.png
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