From: treon3verdery@gmail.com   
      
    a form with cameras of moderate computation ability goes with a form that   
   processes sense data at a location different than the cameras, samples all the   
   pattern resonance activity, notably the location, color and position of all   
   objects is among the    
   things sensed, at each 40k people, 20k things per person each, motion   
   processed every 10 milliseconds (see a keyboard keypress, making a computer   
   data representation from a thing like video although there are also other   
   senses, is 100 million things per    
   second, the computer the white and blue nonsemtient AI utilizes is much bigger   
   than A PC, it is pleasant to note that at 100 million objects processed per   
   second a 4 ghz computer can process 40 instructions per core, one 4ghz   
   computer attached to 4 to 40    
   to 400 Graphics processing units, GPUs, a kind of parallel wide bandwidth   
   computer, which during 2019 could have 4096 processing cores, each engineered   
   to work on images,  GPUs, at 126 frames per second (a GPU velocity i think i   
   read) each is 126 rooms    
   of data, once per second,  at an eleven room three bedroom dwelling, and 2.5   
   people on average per dwelling, is 16k dwellings or about 4.4 rooms per   
   person, so preoptimization is one GPU at 126 FPS sufficient for 29 people,   
   that goes with assuming any    
   object at any moment could change, it is imaginable with people at a dwelling   
   98% of the items, likthingsgs in the livingroom, art objects, and other things   
   like pistachio package wrappers around the room do not spontaneously change   
   their location, a way    
   to make computation is, after gathering data on the area, like a room,   
   omitting updates on the 98% of things that do not change,  so scanning every   
   100th pixel for change with the GPU causes 100 times more efficient computing   
   of, and noticing of, changes,   
    so that is  2900 dwellings the AI is viewing per GPU as to possible pattern   
   effects and people's behavior, at about 2900 people per GPU, that is 14 GPUs   
   per 40k people, globally, the 2019 population of 7.6 billion which JY says   
   will go up, that is 2.6    
   million GPUs, it is possible there is a motion or change detector algorithm   
   that is an order of magnitude more effective at detecting change than 100   
   pixel scanning, with the most minimal sample of an image, like a bit hash of a   
   video frame, rather than    
   an every 100th pixel comparison of an entire view, could be an oder of   
   magnitude higher efficiency, if so then it is 1.4 GPUs per 40,000 people,   
   globally that is 266,000 GPUs to cover the population of earth, about 77   
   million US$ that could double to $   
   154 million with places of commerce, and other non-dwellimg buildings,   
   schools, and streets, also wherever people are they might change something   
   about once a second, continuously as speech and body language, and at typing a   
   keypress each 1/10 of a    
   second, 24 FPS (movies) conserves fluidity and AI processing of body language   
   and is higher velocity than typing,  so at 1/10th of human behavior being full   
   of change, audio, and body language 40k people is 381 GPUs when 126 GPU fps/24   
   fps, 1/10 of    
   people's moments are actions, data compression at the camera halves file size,   
   if the camera processes the data and communicates with the white and blue   
   nonsentient AI with an update once a second,    
      
   When the white and blue nonsentient AI  functionalizes part of its form at   
   each camera then at video and audio there is an absence of GPUs centrally   
   utilized, although parallel computation and routing around any nonfunctional   
   computing cores at the AI is    
   beneficial, There are numerous architectures of parallel computers and the GPU   
   is among them   
      
   I favor all things being video and audio recorded continuously and all people,   
   that is persons, that is humans, that is homo sapiens being able to view the   
   video, audio, and data as they please as public data   
      
   The rich computing at the camera way of doing white and blue nonsentient AI   
   that senses what Treon Verdery calls the IT pattern is also a way to build the   
   AI's form, object, action, place, and time, pattern data gathering capability,   
   putting the object    
   and human activity sourced change detector at the camera and passing along an   
   image data bit hash when things are unchanging, as well as the 24 fps frame   
   just preceding any camera detected  change, Then the white and blue AI, that   
   has many backups and    
   oops-tolerant distributed nodes that prefer to function together as well as   
   function optimally together, or can function alone, at a 4Ghz or higher   
   velocity computer, noting GPUs, or other parallel architectures, utilizes the   
   computationally rich ,    
   utilize data that from the computationally capable cameras that is possibly   
   higher accuracy and that makes the outlay to build the white and blue   
   nonsentient AI global IT pattern observer is lless   
      
      
      
      
   changeor about able to look at plurality of GPU   
      
   Able to read text on containers and see each character on a keyboard    
      
       
      
    support feelings   
      
   --- SoupGate-Win32 v1.05   
    * Origin: you cannot sedate... all the things you hate (1:229/2)