GSAW today

• The community is very much on the implementation part of ML. Aerospace corporation is doing some really nice work merging synthetic and actual data to detect threat anomalies. Slingshot is doing really nice data fusion
• I had an interesting ide come to me during the panel. It might be possible to train a large Transformer model on all mission telemetry from launch to sunset for all satellites. Then you could do zero-shot detection on new data, just like the GPT-3 does.

GPT-Agents

• Working on getting the meta information back to the summary tab – done
• Run all models – done
• I think I know how I want to try the mapping.
  • Use a prompt that should produce a list of nouns in order
  • Have the temp set reasonably high and for repetition to be low
  • Look at the output text and look for a N-N-N… pattern. Select those as nodes and stop when the pattern changes
  • Repeat and increment the edge weight for each redundant connection
  • Trim the leaf nodes with low counts

SBIR

• Ping Clay about how much of my time I can bill based on current rates
• Create generic multidimensional vectors for training
• Yannic Kilcher’s walkthrough of Attention Is All You Need