Category Archives: Talks

Phil 6.1.20


It’s all been a bit much recently, so yesterday I took advantage of the wonderful weather and went on a long ride with a few friends.

D20 – Nagged Zach with this image. He responses generally were “It is generally pretty optimistic around here”, and “According to google is is getting better. I wonder where their data comes from”.


GPT-2 Agents

  • Still some debugging. added output of the raw move files to find games better
  • Dates aren’t right either – fixed
  • Added some better triggering of the print_board method
  • WOW! I mean it shouldn’t be that surprising, but the pgn is wrong. Going to add a flag for games with problem moves. Then I think I should be able to generate text.


  • Put paper in the right format (word?)
  • Create the slides. Verify the speaking duration – done. It’s 20 minuts, I think probably 15 for talk and 5 for questions
  • Found the technical paper repo. Looks like I didn’t have to worry about length!
  • Uploaded! Just use the info in the email from GVSETS Tech Session Admin

Google is profiting from dozens of websites that peddle hoaxes and conspiracy theories about Covid-19, according to a Tech Transparency Project (TTP) investigation, revealing a major hole in the company’s claims that it’s fighting misinformation about the pandemic.


Phil 5.28.20

GPT-2 Agents

  • Back to bug hunting today’s job is to figure out why this:
    1. Nf3 Nf6 2. g3 c5 3. Bg2 Nc6 4. O-O e5 5. e4 Nxe4 6. Re1 Nf6 7. Nxe5 Be7 8. c4
    O-O 9. Nc3 Nxe5 10. Rxe5 d6 11. Re1 Be6 12. Bxb7 Rb8 13. Bg2 Bxc4 14. d4 Be6 15.
    b3 Rb4 16. dxc5 dxc5 17. Qxd8 Rxd8 18. Ba3 Rbb8 19. Na4 Rdc8 20. Rac1 Nd7 21.
    Bd5 Bxd5 22. Rxe7 Bc6 23. Nxc5 Nxc5 24. Rxc5 a6 25. f4 h6 26. Kf2 Bb5 27. Ke3
    Rd8 28. Rcc7 Rd3+ 29. Ke4 Rd2 30. Rxf7 Re8+ 31. Kf5 Bd3+ 32. Kg4 Rxh2 33. Rxg7+
    Kh8 34. Bd6 Rf2 35. Bc5 Rd2 36. Bb4 Rc2 37. Rxc2 Kxg7 38. Rc7+ Kg6 39. Rc6+ Kf7
    40. Rxh6 Re2 41. Rd6 Re3 42. Kh4 Be2 43. g4 Rf3 44. Rd4 Rf2 45. Kg5 1-0
  • breaks the system.
  • So I never added logic to see if the path was clear for a move. The game has a move where white rook moves from e1 to e5 and then back. For the move back, the system looks for the closest rook, which is actually at a1, as the search algorithm works. But that way is actually blocked by the white bishop and white queen. It should take the clear path and discard blocked paths. I think this fix is pretty straightforward


  • Wrote the test, but I’m not sure if it’s right. We’ll test tomorrow:
        def check_if_clear(self, loc:Tuple, candidate:Tuple, piece:PIECES) -> bool:
            if piece == PIECES.WHITE_PAWN or piece == PIECES.BLACK_PAWN:
                return True
            if piece == PIECES.WHITE_KNIGHT or piece == PIECES.BLACK_KNIGHT:
                return True
            if piece == PIECES.WHITE_KING or piece == PIECES.BLACK_KING:
                return True
            c_col_i = self.char_index.index(candidate[0])
            c_row_i = self.num_index.index(candidate[1])
            l_col_i = self.char_index.index(loc[0])
            l_row_i = self.num_index.index(loc[1])
            col_dist = l_col_i - c_col_i
            row_dist = l_row_i - c_row_i
            dist = max(abs(col_dist), abs(row_dist))
            col_vec = 0
            row_vec = 0
            if col_dist != 0:
                col_vec = col_dist/dist
            if row_dist != 0:
                row_vec = row_dist/dist
            col_i = l_col_i
            row_i = l_row_i
            for i in range(dist):
                num = self.num_index[row_i]
                char = self.char_index[col_i]
                pos = (char, num)
                p = self.get_piece_at(pos)
                if p != PIECES.NONE:
                    return False
                col_i += col_vec
                row_i += row_vec
            return True



  • More paper writing
    • Finished the first pass of section 2, which describes the whole model.

Phil 5.27.20

Drop off the truck today!

Agents and expensive information

  • Antonio sent a note asking if I’d be interested in contributing to a chapter. Sent him this response:
    • There is something that I’d like to explore that might fit. It’s the idea that in most environments, agents (animal, human, machine, etc.) are incentivized to cheat. I think this is because information is expensive to produce, but essentially free to copy. The problem is that if all the agents cheat, then the system will collapse because the agents become decoupled from reality (what I call a stampede). So the system as a whole is incentivized to somehow restrict cheating.
    • I think this could be very interesting to work through, but I don’t have a model (or even an approach really) developed that would describe it. I think that this might be related to game theory, though I haven’t found much in the literature.

GPT-2 Agents

  • Working on building a text corpora. Going to add a search for “Opening” and “Variation” which I’ll try before using the DB version – done
  • Having some problem that starts after a few games. Found the culprit game. Will work on tomorrow. It might be tied to a linefeed?


  • Working on the GVSETS paper and slide deck

Phil 5.11.20

Cut my hair for the second time. It looks ok from the front…

I’m also having dreams with crowds in them. Saturday night I dreamed I was at some job with a lot of people in a large building. Last night I dreamed I was sharing a dorm at the Naval Academy?

A foolproof way to shrink deep learning models

  • Train the model, prune its weakest connections, retrain the model at its fast, early training rate, and repeat, until the model is as tiny as you want. 

Graph Neural Networks (GNN)

  • Graph neural networks (GNNs) are connectionist models that capture the dependence of graphs via message passing between the nodes of graphs. Unlike standard neural networks, graph neural networks retain a state that can represent information from its neighborhood with arbitrary depth.


  • Zach’s having issues getting the map to work on mobile
  • Need to start pulling off controlled entities like China and Diamond Princess
  • Made a duplicate of the trending code to play with

GPT-2 Agents

  • More PGNtoEnglish
  • I have pawns and knights moving!


  • With expanded text!
    • ‘Fred Van der Vliet moves white pawn from d2 to d4’
    • ‘Loek Van Wely moves black knight from g8 to f6’


  • Continue with NoiseGAN
  • Isolating noise. Done!


  • Now I need to subsample to produce the training and test sets. Seems to be working
  • Fitting the timeseries sampling into the GAN


  • Try training the GAN?


  • Community Spaces for Interdisciplinary Science and Engagement
    • Dr. Lisa Scheifele is an Associate Professor at Loyola University Maryland and head of the Build-a-Genome research network, where her research focuses on designing and programming cells for new and complex functions. She is also Executive Director at the Baltimore Underground Science Space (BUGSS) community lab. BUGSS provides unique and creative projects to members of the public who have few other opportunities to engage with modern science. As an informal and nontraditional science space, BUGSS’ activities blend biotechnology research, computational tools, artistic expression, and design principles to accomplish interdisciplinary projects driven by community interest and need.

Phil 4.14.20

Fix siding from wind!


  • I want to try taking a second derivative of the rates to see what it looks like. There may be common features in the pattern of rates, or of the slopes of the regressions changing over time
  • I’m also getting worried about countries that don’t report well. I’d like to be able to use rates from neighboring countries as some kind of check
  • Work with Zach on cleanup and map integration?

COVID Twitter

  • Finished ingesting the new data. It took almost 24 hours


  • Finished first pass of the introduction. Still at 14 pages


Phil 4.1.20

Working from home has a different rhythm. I work in segments with home chores mixed in. Today I’m doing this at 6:00, along with some coding. Then some morning exercise, breakfast, and work till noon. Ride, lunch and more work till about 3:00. By that time my brain is broken, and I take a break and do light chores. Today I may finally get my road bike ready for spring. Then simple work like commenting for a few hours. In the evenings I find I like watching shows about competent people fixing things and making them better. Bitchin’ Rides is extremely soothing.


  • Fixing dates
  • integrating the estimated deaths from rate and current deaths as area under the curve until zero.
  • Work on documentation. Also make sure word wrap works
  • This. Is. Bad.


  • Once more, this is Italy. What I’ve done is round-tripped the rates to produce an estimate of total deaths. If calculating rates is taking the derivative, calculating a death prediction is integration. So, if the calculations are right, and Italy is at zero new deaths around April 17th, the toll is around 27 thousand total deaths. That’s 0.04% of the population. If those numbers hold for the US at 327 million, that’s a total of 145,550. The White House is estimating numbers of 100,000 to 240,000, which means their average prediction is that we will fare worse than Italy.
  • Fixed bugs, worked with Zach, made progress. Aaron is starting to appear again!


  • Tweak John’s slides
  • More on saving and restoring docker containers. I think I’m close. Then install InfluxDB and test if I can see the dashboard
  • Still having problems. I can create, run, add, delete, and tag the images, but I can’t run them. I think I’m getting ahead of myself. Back to reading


So it turns out that I was doing everything right but the load. Here’s how it works

  1. docker run container -it –name imagename some-os /bin/sh
  2. Install what needs to be installed. Poke around, save things, etc
  3. docker container commit imagename modified-os
  4. docker save modified-os> modified-os.tar
  5. docker rmi modified-os
  6. docker load < modified-os.tar
  7. docker run container -it –name imagename modified-os /bin/sh




Phil 1.30.20

7:00 – 5:00 ASRC GOES

  • Antonio created an Overleaf project for ACSOS. Fixed the widthg of all the figures. Need to fix the tables and equations
  •  Dissertation
    • Fix the > \pagewidth equations
    • Slides
    • Get the timeline prev work slide updated for Kauffman, Martindale, and Bacharach (how did I do number lines?
  • Add December to status and send to T
  • Finish slide deck and paperwork for GSAW – done, I think
  • Meetings at NSOF
    • 1:30 Isaac
      • More discussion about simulators. We’re going to try running multiple sims this weekend with all even number wheels degraded at 20%, 40%, 60%, and 80% and compare them to 100%
      • In future, set up synchronized tasks so we can run more often and iterate across all wheels
      • Reviewed slides. Making small fixes
    • 2:00 regular status

Phil 1.29.20

7:00 – 8:00 ASRC GOES

  • The Office of Inspector General conducted a review of the Chicago Police Department’s risk models known as the Strategic Subject List and Crime and Victimization Risk Model. CPD received $3.8 million in federal grants to develop these models, which were designed to predict the likelihood an individual would become a “party to violence”, i.e. the victim or offender in a shooting. The results of SSL were know n as “risk scores” while CVRM produced “risk tiers.” In August 2079, CPD informed OIG that it intended to decommission its PTV risk model program and did so on November l, 2079. The purpose of this advisory is to assess lessons learned and provide recommendations for future implementation of PTV risk models.
  • In “Towards a Human-like Open-Domain Chatbot”, we present Meena, a 2.6 billion parameter end-to-end trained neural conversational model. We show that Meena can conduct conversations that are more sensible and specific than existing state-of-the-art chatbots. (Google blog post)
  • Defense
    • Slides – started lit review
    • Drop off dissertation with Wayne
  • GSAW
    • Tweak slides – trying to get a good AIMS overview slide so I can
    • Walkthrough with T
    • Paperwork
  • GOES Meetings
    • Influx DB (Influx 2.0) is a high-performance data store written specifically for time series data. It allows for high throughput ingest, compression and real-time querying. InfluxDB is written entirely in Go and compiles into a single binary with no external dependencies. It provides write and query capabilities with a command-line interface, a built-in HTTP API, a set of client libraries (e.g., Go, Java, and JavaScript) and plugins for common data formats such as Telegraf, Graphite, Collectd and OpenTSDB. 
    • The plan is to have the sim place data from the sim into the Influx DB and have the dashboard display the plots
    • This will generate data: file:///D:/GOES/AIMS4_UI_Mock/3satellite-instrument-analysis.html?page=reportpage&channel=5&status=error, once the demo is unzipped into D:/GOES
  • Meeting with Wayne
    • Dropped off the dissertation
    • Got the reader form signed. Just needs Shimei and Aaron
    • Discussed slides. Can skim the parts that would be review from the proposal and status (but put a slide that says this)
    • Feb 10 as walkthrough? 6:00?

Phil 1.28.20

Make appt. to pick up Dad on Friday after PhD day – done

  • 655 West Baltimore St, Baltimore 21201

protest_mapThis Interactive Guide to Protest Campaigns around the World uses data on all violent and nonviolent campaigns around the world with maximalist claims from 1945–2014 and is based on the NAVCO 1.2 database, recently released by Erica Chenoweth and Christopher Wiley Shay. The data extend on the NAVCO data project, which you can read about (and download) at the project’s Dataverse.

Here’s a bird’s eye view of six state-backed information operations on Twitter, and how they evolved over the last decade. This research was funded by the Mozilla Foundation by an Open Source Support Award.

7:00 – 5:00 ASRC GOES

  • Defense
    • More slides
    • Picked up printed versions and dropped off copies with Shimei, Aaron, and Thom
  • GSAW
    • Change intro slide on GSAW to triangle of data, accuracy, and reliability – done
    • Reworked and tweaked. Walkthrough with T tomorrow.

Phil 1.23.2020

7:00 – 6:00 ASRC GOES

Check Copenhagen Wheel serial number for this recall

  • Get comments back to Antonio tonight! – done
  •  Dissertation
    • Writing chapter summaries
      • Research design – done
      • Simulation – done
      • Adversarial herding – done
      • Belief space cartography – done
      • Human study – done
      • Discussion – done
      • Conclusions – done!
      • Sent pdfs to common vision. Need to set the pdfs out with a note tomorrow morning
    • Caught up with Wayne a bit and commented out the “Why this is HCC section” Keep it for a backup slide though
  • Very interesting Invisibilia on AI
  • GSAW prep
    • Registration
  • Told Aaron about OpML 20. It’s only two pages and due on Feb 25. Maybe a quick writeup of Optevolver?

Phil 1.22.20

7:00 – 6:00 ASRC GOES

Check Copenhagen Wheel serial number for this recall

Contact Dreamhost about missing folders – done Fixed!

Phil 1.21.20

7:00 – 6:00 ASRC GOES

  • Dissertation
    • Chasing TODOs
    • TODO: Add transition paragraph (ch_background.tex) – done
    • TODO: stiff, moving platform (ch_background.tex) – done
    • TODO: clarify multicellular vs individuals vs dangerous stampedes Connect the lists. (sec_biological_basis.tex) – done
  • GSAW prep
    • Tix and hotel
  • TF Dev Conf
    • Tix and hotel

Phil 1.17.20

An ant colony has memories that its individual members don’t have

  • Like a brain, an ant colony operates without central control. Each is a set of interacting individuals, either neurons or ants, using simple chemical interactions that in the aggregate generate their behaviour. People use their brains to remember. Can ant colonies do that? 

7:00 – ASRC

  •  Dissertation
    • More edits
    • Changed all the overviews so that they also reference the section by name. It reads better now, I think
    • Meeting with Thom
  • GPT-2 Agents
  • GSAW Slide deck