Phil 4.12.16

7:00 – 6:00 VTX

  • At the poster session yesterday, I had a nice chat with Yuanyuan about her poster on Supporting Common Ground Development in the Operation Room through Information Display Systems. It turns out that she is looking at information exchange patterns in groups independent of content, which is similar to what I’m looking at. We had a good discussion on group polarization and what might happen if misinformation was introduced into the OR. It turns out that this does happen – if the Attending Physician becomes convinced that, for example, all the instruments have been removed from the patient, the rest of the team can become convinced of this as well and self-reinforce the opinion.
  • Scanned through Deindividuation Effects on Group Polarization in Computer-Mediated Communication: The Role of Group Identification, Public-Self-Awareness, and Perceived Argument Quality. The upshot appears that individuation of participants acts as a drag on group polarization. So the more the information is personalized (and the more that the reader retains self awareness) the less the overall group polarization will move.
  • I’ve often said that humans innately communicate using stories and maps (Maps are comprehended at 3-4.5 years, Stories from when?). The above would support that stories are more effective ways of promoting ‘star’ information patterns. This is all starting to feel very fractal and self similar at differing scales…
  • Looking for children’s development of story comprehension led to this MIT PhD Thesis: TOWARD A MODEL OF CHILDREN’S STORY COMPREHENSION. Good lord – What a Committee: Marvin Minsky (thesis supervisor), Professors Joel Moses and Seymour Papert (thesis committee), Jeff Hill, Gerry Sussman, and Terry Winograd.
  • ———————
  • While reading Deep or Shallow, NLP is Breaking Out, I learned about word2vec. Googling led to Deeplearning4j.org, which has its own word2vec page, among a *lot* of other things. From their home page:
    • Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is designed to be used in business environments, rather than as a research tool. Skymind is its commercial support arm.
    •  Deeplearning4j aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers. DL4J is customizable at scale. Released under the Apache 2.0 license, all derivatives of DL4J belong to their authors.
    •  By following the instructions on our Quick Start page, you can run your first examples of trained neural nets in minutes.
  • The word vector alternative is from the Stanford NLP folks: GloVe: Global Vectors for Word Representation. The link also has trained (extracted?) word vectors.
  • Testing the behavior of query construction and search results. Fixing stupid bugs. Testing more. Lathering, rinsing and repeating.
  • Some good discussions with Aaron on inferencing and toxicity profiles. Basically taking the outputs and determining correlations with the inputs. Which led to a very long day.
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