7:00 – 7:00 ASRC NASA AIMS

• Added lit review section to the dissertation, and put the seven steps of sectarianism in.
• Spent most of yesterday helping Aaron with TimeSeriesML. Currently working on a JSON util that will get a value on a provided path
• Had to set up python at the module and not project level, which was odd. Here’s how: www.jetbrains.com/help/idea/2016.1/configuring-global-project-and-module-sdks.html#module_sdk
• Done!

      def lfind(self, query_list:List, target_list:List, targ_str:str = "???"):
          for tval in target_list:
              if isinstance(tval, dict):
                  return self.dfind(query_list[0], tval, targ_str)
              elif tval == query_list[0]:
                  return tval
  
      def dfind(self, query_dict:Dict, target_dict:Dict, targ_str:str = "???"):
          for key, qval in query_dict.items():
              # print("key = {}, qval = {}".format(key, qval))
              tval = target_dict[key]
              if isinstance(qval, dict):
                  return self.dfind(qval, tval, targ_str)
              elif isinstance(qval, list):
                  return self.lfind(qval, tval, targ_str)
              else:
                  if qval == targ_str:
                      return tval
                  if qval != tval:
                      return None
  
      def find(self, query_dict:Dict):
          # pprint.pprint(query_dict)
          result = self.dfind(query_dict, self.json_dict)
          return result
  
  

• It’s called like this:

  ju = JsonUtils("../../data/output_data/lstm_structure.json")
  # ju.pprint()
  result = ju.find({"config":[{"class_name":"Masking", "config":{"batch_input_shape": "???"}}]})
  print("result 1 = {}".format(result))
  result = ju.find({"config":[{"class_name":"Masking", "config":{"mask_value": "???"}}]})
  print("result 2 = {}".format(result))

• Here’s the results:

  result 1 = [None, 12, 1]
  result 2 = 666.0

• Got Aaron’s code running!
• Meeting with Joel
  • A quicker demo that I was expecting, though I was able to walk through how to create and use Corpus Manager and LMN. Also, we got a bug where the column index for the eigenvector didn’t exist. Fixed that in JavaUtils.math.Labeled2DMatrix.java
• Meeting with Wayne
  • Walked through the JASSS paper. Need to make sure that the lit review is connected and in the proper order
  • Changed the title of the dissertation to
    • Stampede Theory: Mapping Dangerous Misinformation at Scale
  • Solidifying defense over the winter break, with diploma in the Spring
  • Mentioned the “aikido with drones” concept. Need to make an image. Actually, I wonder if there is a way for that model to be used for actually getting a grant to explore weaponized AI in a way that isn’t directly mappable to weapons systems, but is close enough to reality that people will get the point.
  • Also discussed the concept of managing runaway AI with the Sanhedrin-17a concept, where unanimous agreement to convict means acquittal.  Cities had Sanhedrin of 23 Judges and the Great Sanhedrin had 71 Judges (link: https://en.wikipedia.org/wiki/Sanhedrin) en.wikipedia.org/wiki/Sanhedrin
    • Rav Kahana says: In a Sanhedrin where all the judges saw fit to convict the defendant in a case of capital law, they acquit him. The Gemara asks: What is the reasoning for this halakha? It is since it is learned as a tradition that suspension of the trial overnight is necessary in order to create a possibility of acquittal. The halakha is that they may not issue the guilty verdict on the same day the evidence was heard, as perhaps over the course of the night one of the judges will think of a reason to acquit the defendant. And as those judges all saw fit to convict him they will not see any further possibility to acquit him, because there will not be anyone arguing for such a verdict. Consequently, he cannot be convicted.