Category Archives: Phil

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 1.20.20

Transformers from Scratch

  • Transformers are a very exciting family of machine learning architectures. Many good tutorials exist, but in the last few years transformers have mostly become simpler, so that it is now much more straightforward to explain how modern architectures work. This post is an attempt to explain directly how modern transformers work, and why, without some of the historical baggage.

Dissertation

  • Folding in Wayne’s edits
    • Made the Arendt paragraph of velocity less reflective and more objective.
    • TODO: Defend facts to opinion with examples of language, framing, what is interesting, etc.-done
    • TODO: Heavy thoughts, light and frivolous, etc. We ascribe these, but they are not there – done
    • TODO: We have a MASSIVE physical bias. Computers don’t. Done
    • TODO: COmputers and people must work together
  • Title case all refs (Section, Table, etc) – done
  • \texttt all urls (reddit, etc) – done
  • search for and / or slashes
  • Fix underlines as per here– done!
    % for better underlining
    \usepackage[outline]{contour}
    \usepackage{ulem}
    \normalem % use classical emph
    
    \newcommand \myul[4]{%
    	\begingroup%
    	\renewcommand \ULdepth {#1}%
    	\renewcommand \ULthickness {#2}%
    	\contourlength{#3}%
    	\uline{\phantom{#4}}\llap{\contour{white}{#4}}%
    	\endgroup%
    }

     

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

Phil 1.16.20

Optuna: An open source hyperparameter optimization framework to automate hyperparameter search

  • Medium writeup. It looks like this is Bayesian, and is better than hyperopt?

7:00 – 5:00 ASRC GOES

  • Dissertation
    • Starting to add Wayne’s comments
    • Finished the intro, starting motivation
  • NSOF Meeting with Isaac & Bruce
    • Still looking at the optimal scenario to use the current simulators (running over a weekend) to generate data
    • Data sets are used to train and evaluate, then progressively simplified until they can no longer recognize the source data. This will let us estimate the fidelity of the simulations we need.
  • JuryRoom meeting. Looking into adding UX faculty. Meeting is expanding to 6:00 – 8:00

Phil 1.15.20

I got invited to the TF Dev conference!

The HKS Misinformation Review is a new format of peer-reviewed, scholarly publication. Content is produced and “fast-reviewed” by misinformation scientists and scholars, released under open access, and geared towards emphasizing real-world implications. All content is targeted towards a specialized audience of researchers, journalists, fact-checkers, educators, policy makers, and other practitioners working in the information, media, and platform landscape.

  • For the essays, a length of 1,500 to 3,000 words (excluding footnotes and methodology appendix) is appropriate, but the HKS Misinformation Review will consider and publish longer articles. Authors of articles with more than 3,000 words should consult the journal’s editors before submission.

7:00 – ASRC GOES

  •  Dissertation
    • It looks like I fixed my LaTeX problems. I went to C:\Users\phil\AppData\Roaming\MiKTeX\2.9\tex\latex, and deleted the ifvtex folder. Re-ran, things installed, and all is better now
    • Slides
  • GOES
    • Pinged Isaac about the idea of creating scenarios that incorporate the NASA simulators
    • Meeting
  • GSAW
    • Slides
    • Speakers presenting in a plenary session are scheduled to speak for 15 minutes, with five additional minutes allowed for questions and answers from the audience
    • Our microphones work best when the antenna unit is clipped to a belt and the microphone is attached near the center of your chest.
    • We are NOT providing network capabilities such as WiFi. If you require WiFi, you are responsible for purchasing it from the hotel and ensuring that it works for the presentation.
    • Charts produced by the PC version of Microsoft PowerPoint 2013, 2016 or 365 are preferred
    • . In creating your slides, note that the presentation room is large and you should consider this in your selection of larger fonts, diagram size, etc. At a minimum, a 20-point font is recommended
  • GPT-2 – Maybe do something with Aaron today?

Phil 1.14.20

7:00 – 5:00 ASRC GOES/PhD

  • Finishing touches on the dissertation. Need to lint the bibtex – done
    • The work machine is not behaving. Had to move to Overleaf
  • Call commonvision to schedule printing and binding – done
  • Order some thumb drives – done
  • Meeting with Don. Discovered that he’s a digital format guy. Discovered that the Lit Review was missing from the exec summary
  • Corresponding with Thom. Hardcopy. Meeting still on Friday?

Phil 1.11.20

On the Relationship between Self-Attention and Convolutional Layers

  • Recent trends of incorporating attention mechanisms in vision have led researchers to reconsider the supremacy of convolutional layers as a primary building block. Beyond helping CNNs to handle long-range dependencies, Ramachandran et al. (2019) showed that attention can completely replace convolution and achieve state-of-the-art performance on vision tasks. This raises the question: do learned attention layers operate similarly to convolutional layers? This work provides evidence that attention layers can perform convolution and, indeed, they often learn to do so in practice. Specifically, we prove that a multi-head self-attention layer with sufficient number of heads is at least as powerful as any convolutional layer. Our numerical experiments then show that the phenomenon also occurs in practice, corroborating our analysis. Our code is publicly available.
  • I’ve just started to think about how machines and humans could serve as different attention heads, which is why we concentrate into populations with shared features. Attention, given the right conditions, may be an emergent phenomena. Need to look at Kauffman.

Dissertation

  • More Forward – done!
  • Dedication – done
  • Acknowledgements – started!
  • Sometime between the end of the forward and meeting with Aaron, move over to the new template