Category Archives: Writing

Phil 5.24.19

7:00 – 3:30 ASRC GEOS

Phil5.23.19

7:00 – 5:00 ASRC GEOS

  • Saw 4×3000 with David and Roger last night. The VR lab seems to be a thing. Need to go down and have a chat, possibly about lists, stories, maps and games
  • Found the OECD Principles on Artificial Intelligence. I haven’t had a chance to actually *read* any of it, but I did create a “Treaty Lit” folder in the Sanhedrin folder and put pdf versions of them. I ran my tool over them and got the following probe:
    • state cyber cybercrime agree united china mechanism
  • Putting that into Google Scholar returns some good hits as well, though I haven’t gotten a chance to do anything beyond that.
  • JASSS paper
    • Changing “consensus” to “alignment”, and breaking many paragraphs. I think the setup of the space in the introduction is better now.
  • Got caught up on NESDIS. Worked some on the slide deck, which I finally got back. Scheduled a walkthrough with T tomorrow
  • GEOS AI/ML meeting at NSOF. Still trying to figure out roles and responsibilities. I think the Sanhedrin concept will help Bruce formalize our contributions.

Phil 5.16.18

7:00 – 9:00 ASRC GEOS/AIMES

  • Worked on the slides a bit
  • Adding changes to the JASSS paper
  • Waiting for meeting
  • Meeting went well, I think? Funding appears to be solid, and I’m now a “Futurist”
  • Meeting with Shimei’s group. Fatima might be interested in ML summer work
  • Meeting with Aaron. Fleshed out the Sanhedrin-17a concept

Phil 5.14.19

7:00 – 8:00 ASRC NASA GEOS-R

  • More Dissertation
  • Break out the network slides to “island” (initial state), “star” (radio) “cyclic star” (talk radio), “dense” social media
  • MatrixScalar
  • 7:30 Waikato meeting.
    • Walked through today’s version, which is looking very nice
    • Went over tasking spreadsheets

Phil 5.13.19

7:00 – 3:00 ASRC NASA GEOS-R

Phil 5.7.19

7:00 – 8:00 ASRC NASA GOES-R

  • Via CSAIL: “The team’s approach isn’t particularly efficient now – they must train and “prune” the full network several times before finding the successful subnetwork. However, MIT professor Michael Carbin says that his team’s findings suggest that, if we can determine precisely which part of the original network is relevant to the final prediction, scientists might one day be able to skip this expensive process altogether. Such a revelation has the potential to save hours of work and make it easier for meaningful models to be created by individual programmers and not just huge tech companies.”
    • From the abstract of The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
      : We find that a standard pruning technique naturally uncovers subnetworks whose initializations made them capable of training effectively. Based on these results, we articulate the “lottery ticket hypothesis:” dense, randomly-initialized, feed-forward networks contain subnetworks (“winning tickets”) that – when trained in isolation – reach test accuracy comparable to the original network in a similar number of iterations. The winning tickets we find have won the initialization lottery: their connections have initial weights that make training particularly effective. 
    • Sounds like a good opportunity for evolutionary systems
  • Finished with text mods for IEEE letter
  • Added Kaufman and Olfati-Sabir to the discussion on Social Influence Horizon
  • Started the draft deck for the tech summit
  • More MatrixScalar
    • Core functions work
    • Change test and train within the class to input and target
    • Create a coordinating class that loads and creates test and train matrices
  • JuryRoom meeting
    • Progress is good enough to start tracking it. Going to create a set of Google sheets that keep track of tasks and bugs

Phil 5.6.19

7:00 – 5:00 ASRC GOES-R

  • Finished the AI/ML paper with Aaron M over the weekend. I need to have him ping me when it goes in. I think it turned out pretty well, even when cut down to 7 pages (with references!! Why, IEEE, why?)
    • Sent a copy to Wayne, and distributed around work. Need to put in on ArXiv on Thursday
  • Starting to pull parts from phifel.com to make the lit review for the dissertation. Those reviews may have had a reason after all!
    • And oddly (though satisfying), I wound up adding a section on Moby-Dick as a way of setting up the rest of the lit review
  • More Matrix scalar class. Basically a satisfying day of just writing code.
  • Need to fix IEEE letter and take a self-portrait. Need to charge up the good camera

Phil 5.3.19

8:00 – 5:00 ASRC AIMES

  • I may need to do something Star Wars-ish tomorrow
  • Didn’t get the Google AI for Social Good. Sigh
  • Working on the MatrixScalar class
    • use np.array as core type?
    • Good progress. I can build a scaled, square matrix
    • Need to add a log(x)/10X scale/rescale

Phil 4.26.19

7:00 – 4:00 ASRC TL

Phil 4.25.19

7:00 – 9:00 ASRC TL

  • Looks like I’ll be giving a talk at the PM Summit in June on misinformation. Need to put together a 30 minute talk
    • Need to come up with a short description. Something along the lines of misinformation happens at all scales, from international news to groupthink leading to the shuttle Columbia launch decision. This talk will show the common patterns that can identify misinformation behaviors and ways to disrupt these “belief stampedes”.
  • Ping Joel and see if I can coordinate him and Wayne…
    • Sent email and made a doodle
  • Continuing with AI whitepaper
  • Walk through webGL classes with Zach – done
  • ML meeting – walked through the differences between heart attack (ischemic insults) and heart failure
  • Meeting with Aaron M. More discussions of how the paper should go. He’s like a section on how things like latent space hacking can wind up in other areas

Phil 4.23.19

7:00 – 5:30 ASRC TL

  • Reading Army of None and realizing that incorporating AI is a stampede theory and diversity issue:
    • This makes Aegis less like a finished product with a few different modes and more like a customizable system that can be tailored for each mission. Galluch explained that the ship’s doctrine review board, consisting of the officers and senior enlisted personnel who work on Aegis, begin the process of writing doctrine months before deployment. They consider their anticipated missions, intelligence assessments, and information on the region for the upcoming deployment, then make recommendations on doctrine to the ship’s captain for approval. The result is a series of doctrine statements, individually and in packages, that the captain can activate as needed during deployment. (Page 164)
    • Doctrine statements are typically grouped into two general categories: non-saturation and saturation. Non-saturation doctrine is used when there is time to carefully evaluate each potential threat. Saturation doctrine is needed if the ship gets into a combat situation where the number of inbound threats could overwhelm the ability of operators to respond. “If World War III starts and people start throwing a lot of stuff at me,” Galluch said, “I will have grouped my doctrine together so that it’s a one-push button that activates all of them. And what we’ve done is we’ve tested and we’ve looked at how they overlap each other and what the effects are going to be and make sure that we’re getting the defense of the ship that we expect.” This is where something like Auto-Special comes into play, in a “kill or be killed” scenario, as Galluch described it. (Page 164)
    • Extensive testing goes into ensuring that it works properly. Once the ship arrives in theater, the first thing the crew does is test the weapons doctrine to see if there is anything in the environment that might cause it to fire in peacetime, which would not be good. This is done safely by enabling a hardware-level cutout called the Fire Inhibit Switch, or FIS. The FIS includes a key that must be inserted for any of the ship’s weapons to fire. When the FIS key is inserted, a red light comes on; when it is turned to the right, the light turns green, meaning the weapons are live and ready to fire. When the FIS is red—or removed entirely—the ship’s weapons are disabled at the hardware level. (Page 165)
    • But the differences run deeper than merely having more options. The whole philosophy of automation is different. With Aegis, the automation is used to capture the ship captain’s intent. In Patriot, the automation embodies the intent of the designers and testers. The actual operators of the system may not even fully understand the designers’ intent that went into crafting the rules. The automation in Patriot is largely intended to replace warfighters’ decision-making. In Aegis, the automation is used to capture warfighters’ decision-making. (Page 165)
    • Hawley argued that Army Patriot operators train in a “sham environment” that doesn’t accurately simulate the rigors of real-world combat. As a result, he said “the Army deceives itself about how good their people really are. . . . It would be easy to believe you’re good at this, but that’s only because you’ve been able to handle the relatively non-demanding scenarios that they throw at you.” Unfortunately, militaries might not realize their training is ineffective until a war occurs, at which point it may be too late. (Page 171)
    • Hawley explained that the Aegis community was partially protected from this problem because they use their system day in and day out on ships operating around the globe. Aegis operators get “consistent objective feedback from your environment on how well you’re doing,” preventing this kind of self-deception. The Army’s peacetime operating environment for the Patriot, on the other hand, is not as intense, Hawley said. “Even when the Army guys are deployed, I don’t think that the quality of their experience with the system is quite the same. They’re theoretically hot, but they’re really not doing much of anything, other than just monitoring their scopes.” Leadership is also a vital factor. “Navy brass in the Aegis community are absolutely paranoid” about another Vincennes incident, Hawley said. (Page 171)
  • Working on JASS paper
  • Working on AI paper
  • Long chat with Eric H