Author Archives: pgfeldman

Phil 9.10.19

ASRC GOES 7:00 – 5:30

  • Got a mention in an article on Albawaba – When the Only Option is ‘Not to Play’? Autonomous Weapons Systems Debated in Geneva 
  • Dissertation – more SIH
  • Just saw this: On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
    • We present a method to produce abstractive summaries of long documents that exceed several thousand words via neural abstractive summarization. We perform a simple extractive step before generating a summary, which is then used to condition the transformer language model on relevant information before being tasked with generating a summary. We show that this extractive step significantly improves summarization results. We also show that this approach produces more abstractive summaries compared to prior work that employs a copy mechanism while still achieving higher rouge scores. Note: The abstract above was not written by the authors, it was generated by one of the models presented in this paper.
  • Working on packaging timeseriesML. I think it’s working!

TimeSeriesML

  • I’ll try it out when I get back after lunch
  • Meeting with Vadim
    • Showed him around and provided svn access
  • Model:DLG3501W SKU:6181264

Phil 9.5.19

7:00 –

  • David Manheim (scholar)
    • I work on existential risk mitigation, computational modelling, and epidemiology. I spend time talking about Goodhart’s Law, and have been a #Superforecaster with the Good Judgement Project since 2012.
  • Goodhart’s law is an adage named after economist Charles Goodhart, which has been phrased by Marilyn Strathern as “When a measure becomes a target, it ceases to be a good measure.”[1] One way in which this can occur is individuals trying to anticipate the effect of a policy and then taking actions that alter its outcome
  • Dissertation
  • Continuing TF 2.0 Keras tutorial
    • Had a weird problem where 
      from tensorflow import keras

      made IntelliJ complain, but the python interpreter ran fine. I then installed keras, and IJ stopped complaining. Checking the version(s) seems to be identical, even though I can see that there is a new keras directory in D:\Program Files\Python37\Lib\site-packages. And we know that the interpreter and IDE are pointing to the same place:

      "D:\Program Files\Python37\python.exe" D:/Development/Sandboxes/PyBullet/src/TensorFlow/HelloKeras.py
2019-09-05 11:30:04.694327: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
tf.keras version = 2.2.4-tf
keras version = 2.2.4-tf

Keras

    • This has the implication that instead of : 
      from tensorflow.keras import layers

      I need to have:

      from keras import layers

      I mean, it works, but it’s weird and makes me think that something subtle may be busted…

Phil 9.4.19

7:00 – 5:00 ASRC GOES

Surrogation

Phil 9.3.19 (including install directions for Tensorflow 2.0rc1 on Windows 10)

7:00 – 4:30ASRC GOES

  • Dissertation – Working on the Orientation section, where I compare Moby Dick to Dieselgate
  • Uninstalling all previous versions of CUDA, which should hopefully allow 10 to be installed
  • Still flailing on getting TF 2.0 working. Grrrrr. Success! Added guide below
  • Spent some time discussing mapping the GPT-2 with Aaron

Installing Tensorflow 2.0rc1 to Windows 10, a temporary accurate guide

  • Uninstall any previous version of Tensorflow (e.g. “pip uninstall tensorflow”)
  • Uninstall all your NVIDIA crap
  • Install JUST THE CUDA LIBRARIES for version 9.0 and 10.0. You don’t need anything else

NVIDIA1

NVIDIA2

  • Then install the latest Nvidia graphics drivers. When you’re done, your install should look something like this (this worked on 9.3.19):

NVIDIA3

Edit your system variables so that the CUDA 9 and CUDA 10 directories are on your path:

NVIDIA4

One more part is needed from NVIDIA: cudnn64_7.dll

In order to download cuDNN, ensure you are registered for the NVIDIA Developer Program.

    1. Go to: NVIDIA cuDNN home page
    2. Click “Download”.
  1. Remember to accept the Terms and Conditions.
  2. Select the cuDNN version to want to install from the list. This opens up a second list of target OS installs. Select cuDNN Library for Windows 10.
  3. Extract the cuDNN archive to a directory of your choice. The important part (cudnn64_7.dll) is in the cuda\bin directory. Either add that directory to your path, or copy the dll and put it in the Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10\bin directory

NVIDIA6

Then open up a console window (cmd) as admin, and install tensorflow:

  • pip install tensorflow-gpu==2.0.0-rc1
  • verify that it works by opening the python console and typing the following:

NVIDIA5

if that works, you should be able to have the following work:

import tensorflow as tf
print("tf version = {}".format(tf.__version__))
mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
    tf.keras.layers.Flatten(input_shape=(28, 28)),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5)

model.evaluate(x_test, y_test)

The results should looks something like:

"D:\Program Files\Python37\python.exe" D:/Development/Sandboxes/PyBullet/src/TensorFlow/HelloWorld.py
2019-09-03 15:09:56.685476: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
tf version = 2.0.0-rc0
2019-09-03 15:09:59.272748: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2019-09-03 15:09:59.372341: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531
pciBusID: 0000:01:00.0
2019-09-03 15:09:59.372616: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-09-03 15:09:59.373339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-09-03 15:09:59.373671: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-09-03 15:09:59.376010: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531
pciBusID: 0000:01:00.0
2019-09-03 15:09:59.376291: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-09-03 15:09:59.376996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-09-03 15:09:59.951116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-09-03 15:09:59.951317: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 
2019-09-03 15:09:59.951433: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N 
2019-09-03 15:09:59.952189: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9607 MB memory) -> physical GPU (device: 0, name: TITAN X (Pascal), pci bus id: 0000:01:00.0, compute capability: 6.1)
Train on 60000 samples
Epoch 1/5
2019-09-03 15:10:00.818650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll

   32/60000 [..............................] - ETA: 17:07 - loss: 2.4198 - accuracy: 0.0938
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55328/60000 [==========================>...] - ETA: 0s - loss: 0.3018 - accuracy: 0.9135
56320/60000 [===========================>..] - ETA: 0s - loss: 0.2995 - accuracy: 0.9141
57440/60000 [===========================>..] - ETA: 0s - loss: 0.2980 - accuracy: 0.9143
58400/60000 [============================>.] - ETA: 0s - loss: 0.2961 - accuracy: 0.9148
59552/60000 [============================>.] - ETA: 0s - loss: 0.2941 - accuracy: 0.9154
60000/60000 [==============================] - 4s 65us/sample - loss: 0.2930 - accuracy: 0.9158
... epochs pass ...
10000/1 [==========] - 1s 61us/sample - loss: 0.0394 - accuracy: 0.9778

Phil 9.1.19

Still tired from yesterday’s adventure:

Strava

Thinking about @scottbot’s thread on TalkToATransformner.com. In a way, the GPT-2 and other models are an arrangement of all the text that the system has incorporated. I think I’s like to go through the dictionary, one word at a time, and use that word as a seed for building a low-dimensional threaded term model that we can visually examine, in the same way that I used text from Tymora to show the “belief space” around each room. For example, here are some responses to silence:

  • Lecture, Thursday 17 June 2014, 10:30am
    In the course of our study we will observe the behaviour of animals at two distinct locations – one to an animal’s immediate (neonatal) environment, the other to two distinct environments in its home territory – the home environment in which the animal lives. We will also observe the behaviour of animals in an adjacent environment to each animal we observe in one of these new environments; one for the social or ‘prey’ species and the other for the ‘host’ species.
  • In addition to a few other notable games, like the two I mentioned earlier, the team was able to pick up several top players to form one of the premier teams in the region of Korea. At this time, the team was ranked 11th in the league of legends scene.
  • Sensing my heart beating at a frantic pace, I raised my head to look at the place where the girl’s mouth had been. A large, blue, round hole had appeared there.
  •  キャラクシー 土方の親愛神・レイラン Aamir AB Black Bird Bomb AB Bluebird Blues AB Bomb AB Chuck AB Dashing Wingman AB Green Bird Hal AB Hal AB Matilda AB Red AB Red Bird Red AB The Blues AB White Bird Matilda AB Wingman AB Yellow Bird Chuck ABE Archer Blues ABE Capt’n Bomb ABE Cleric Matilda ABE Fencer Red ABE Guard Captain Pig ABE Knight Red ABE Mage Chuck ABE Pirate Bomb ABE Priest Matilda ABE Royal Guard Pig ABE Trickster Blues ABE Wizard Chuck Abiding Sniper Dragonbound, Myr Absolute Zero Hrungnir Abyssal CyberDragon, Sadalmelik Abyssal 
  • is about what you do, not what you say. And the answer is: it’s not something you should say. In fact, I want you to make an effort to talk to others.
  • I was so excited for my wedding day, and I had to be there. My mom had an idea to hold my wedding in a different room and I made it happen. I had my brother, sister, bridesmaid, and a couple of guys wait in the front. It was so beautiful and relaxing. Thank you, thank you, THANK YOU!

My intuition is that these word sequences can be treated like sequential threads, since they are sentences/paragraphs, and have an implicit sense of time. And like like the room conversations in the temple, that there will be denser and sparser areas on the network/landscape that we might be able to map. If we can build these small pieces, we can then experiment with ways to assemble the larger quilt.

Just to reinforce this idea, I thought about using more specific terms or phrases. Here’s what we get with bird sanctuary. I’d a much more constrained landscape:

  • is open only 24 hours a day and is open on the following holidays:
  • Tower of the Winds – Cave of Wonders – Rune Isle
  • The idea of an animal sanctuary for a big-cat sanctuary is one of the most amazing things that a lot of people will ever come up with that they can’t see in the current environment of wildlife protection. 
  • an annual four-day event that promotes conservation efforts.
  • (2) Pescado Bay Nature Preserve (2) Pacific Coast Aquarium (11) Pacific Grove (1) Pacifica Harbor (1) Philadelphia Zoo (1) Philadelphia Museum of Art (1) Philadelphia World’s Fair (2) Piebald Beach (1) Pinnacle Beach (1) Placid Bay (1) Point Park and Wildlife Management area

Based on David Massad’s tweet, I think the phrases to use are news headlines, that can be compared to some sort of ground truth contained in the story.

 

Phil 8.30.19

7:00 – 4:00 ASRC GOES

  • Dentist!
  • Sent notes to David Lazar and Erika M-T. Still need to ping Stuart Shulman.
  • Did my part for JuryRoom (Eero Mäntyranta)
  • Dissertation – more on State
  • TF 2.0 today? (release notes)
  • Installed! Well – it didn’t blow up… 
    C:\WINDOWS\system32>pip3 install tensorflow-gpu==2.0.0-rc0                                                              Collecting tensorflow-gpu==2.0.0-rc0                                                                                      Downloading https://files.pythonhosted.org/packages/3c/90/046fdf56ba957de792e4132b687e09e34b6f237608aa9fc17c656ab69b39/tensorflow_gpu-2.0.0rc0-cp37-cp37m-win_amd64.whl (285.1MB)                                                                  |████████████████████████████████| 285.1MB 20kB/s                                                                  Collecting absl-py>=0.7.0 (from tensorflow-gpu==2.0.0-rc0)                                                                Downloading https://files.pythonhosted.org/packages/3c/0d/7cbf64cac3f93617a2b6b079c0182e4a83a3e7a8964d3b0cc3d9758ba002/absl-py-0.8.0.tar.gz (102kB)                                                                                                |████████████████████████████████| 112kB ...                                                                       Collecting gast>=0.2.0 (from tensorflow-gpu==2.0.0-rc0)                                                                   Downloading https://files.pythonhosted.org/packages/4e/35/11749bf99b2d4e3cceb4d55ca22590b0d7c2c62b9de38ac4a4a7f4687421/gast-0.2.2.tar.gz                                                                                                      Collecting google-pasta>=0.1.6 (from tensorflow-gpu==2.0.0-rc0)                                                           Downloading https://files.pythonhosted.org/packages/d0/33/376510eb8d6246f3c30545f416b2263eee461e40940c2a4413c711bdf62d/google_pasta-0.1.7-py3-none-any.whl (52kB)                                                                                  |████████████████████████████████| 61kB 4.1MB/s                                                                    Collecting wrapt>=1.11.1 (from tensorflow-gpu==2.0.0-rc0)                                                                 Downloading https://files.pythonhosted.org/packages/23/84/323c2415280bc4fc880ac5050dddfb3c8062c2552b34c2e512eb4aa68f79/wrapt-1.11.2.tar.gz                                                                                                    Collecting grpcio>=1.8.6 (from tensorflow-gpu==2.0.0-rc0)                                                                 Downloading https://files.pythonhosted.org/packages/32/e7/478737fd426798caad32a2abb7cc63ddb4c12908d9e03471dd3c41992b05/grpcio-1.23.0-cp37-cp37m-win_amd64.whl (1.6MB)                                                                              |████████████████████████████████| 1.6MB ...                                                                       Collecting termcolor>=1.1.0 (from tensorflow-gpu==2.0.0-rc0)                                                              Downloading https://files.pythonhosted.org/packages/8a/48/a76be51647d0eb9f10e2a4511bf3ffb8cc1e6b14e9e4fab46173aa79f981/termcolor-1.1.0.tar.gz                                                                                                 Collecting tf-estimator-nightly<1.14.0.dev2019080602,>=1.14.0.dev2019080601 (from tensorflow-gpu==2.0.0-rc0)              Downloading https://files.pythonhosted.org/packages/21/28/f2a27a62943d5f041e4a6fd404b2d21cb7c59b2242a4e73b03d9ba166552/tf_estimator_nightly-1.14.0.dev2019080601-py2.py3-none-any.whl (501kB)                                                      |████████████████████████████████| 501kB ...                                                                       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Installing collected packages: absl-py, gast, google-pasta, wrapt, grpcio, termcolor, tf-estimator-nightly, keras-preprocessing, setuptools, markdown, werkzeug, wheel, protobuf, tb-nightly, opt-einsum, astor, h5py, keras-applications, tensorflow-gpu                                                                                                                 Running setup.py install for absl-py ... done                                                                           Running setup.py install for gast ... done                                                                              Running setup.py install for wrapt ... done                                                                             Running setup.py install for termcolor ... done                                                                         Found existing installation: setuptools 40.8.0                                                                            Uninstalling setuptools-40.8.0:                                                                                           Successfully uninstalled setuptools-40.8.0                                                                          Running setup.py install for opt-einsum ... done                                                                      Successfully installed absl-py-0.8.0 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.23.0 h5py-2.9.0 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 opt-einsum-3.0.1 protobuf-3.9.1 setuptools-41.2.0 tb-nightly-1.15.0a20190806 tensorflow-gpu-2.0.0rc0 termcolor-1.1.0 tf-estimator-nightly-1.14.0.dev2019080601 werkzeug-0.15.5 wheel-0.33.6 wrapt-1.11.2

     

  • Oops: Python 3.7.4 (tags/v3.7.4:e09359112e, Jul 8 2019, 20:34:20) [MSC v.1916 64 bit (AMD64)] on win32
    Type “help”, “copyright”, “credits” or “license” for more information.
    >>> import tensorflow as tf
    2019-08-30 10:23:30.632254: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library ‘cudart64_100.dll’; dlerror: cudart64_100.dll not found
    >>>
  • Spent the rest of the day trying to get “import tensorflow as tf” to work

Phil 8.29.19

ASRC GOES – 7:00 – 4:00

  • Find out who I was talking to yesterday at lunch (Boynton?)
  • Contact David Lazar about RB
  • Participating as an anonymous fish in JuryRoom. Started the discussion
  • Dissertation – started the State section
  • Working on Control and sim diagrams
    • Putting this here because I keep on forgetting how to add an outline/border to an image in Illustrator:

OutlineAI

  1. Place and select an image in the Illustrator document.
  2. Once selected, open Appearance panel and from the Appearance panel flyout menu, choose Add New Stroke:
  3. With the Stroke highlighted in the Appearance panel, choose Effect -> Path -> Outline Object.
  • Anyway, back to our regularly scheduled program.
  • Made a control system diagram
  • Made a control system inheritance diagram
  • Made a graphics inheritance diagram
  • Need to stick them in the ASRC Dev Pipeline document
  • Discovered JabRef: JabRef is an open source bibliography reference manager. The native file format used by JabRef is BibTeX, the standard LaTeX bibliography format. JabRef is a desktop application and runs on the Java VM (version 8), and works equally well on Windows, Linux, and Mac OS X.
  • Tomorrow we get started with TF 2.0

Phil 9.28.19

Politics and computational sociology conference Left 6:45, got there 9:30. Left 9:00-ish, arrived home 10:00

  • Late – it took 2.75 hours to get there. I hope I can find my car…
  • NETWORKS
  • Joseph Shaheen – Target Policy making under the frame of dark networks
    • What is a dark neworks framewook?
    • Oh, no real definition. There are light and gray ones too
    • Centrality is important
    • @josephshaheen
  • Sarah Shugars – The structure of reasoning, inferring conceptual networks
    • What is public opinion – an aggregation of preferences
    • Build a model of individual reasoning
    • What are the nodes – concepts
    • What are the edges – connections between concepts
    • Portrait divergence?
    • @shugars
  • Bruce Desmarais – Network Event History Analysis
    • Bolasso model constant lasso estimatino using bootstrap – sounds like principal component analysis
    • Policy diffusion over time. How do they know that the policies are the same
  • NEWS
  • Jin Woo Kim – The distorting prism of social media
    • Frequent online commenters are unrepresentative of the general public – therefore, more toxic. Feedback loop of likes and toxicity
    • Google Perspective API?
  • Yujin Kim – Polarization in online uncivil comments
    • Lingustic features – partisan language, in-out group pronouns predict incivility?
    • This study used internal NYT data where comments were rejected by the editors? And what does that mean?
  • Maurits van der Ween – Measuring the European public sphere across multiple languages
    • Measure discourse across multiple language over time
    • European identity is maginal and not developing much
    • Imagined Community – Anderson
    • What does it mean to be tightly linked by print?
    • NN translation
    • Topic modeling
  • Pavel Oleinikpc – Finding duplicate stories in local news
    • National news promote polarization due to suppression of local news
    • Need to discriminate between true local news from repackaged national segments
    • Uses closed-caption text
    • Google’s free transcription after 60 minutes per month
    • Normally, teleprompter text is fed into closed caption  unless the text is spontaneous, at which point, the quality drops greatly
    • Locality sensitive hashing?
  • JOURNALISM
  • Sean Fisher – Locating the local
    • Selective exposure – what environmental constraints on news exposure
    • Local news disappear and politics becomes nationalized
    • Will affect how the issue is perceived
    • 3,000 county seats in the US
    • Northeastern developed search terms?
    • No spatial correlations
    • Regression for multi factors, but local searches = local results, national search = national results
  • Andy Guess – Media Literacy <—– This guy
    • WhatsApp fueling fake news in India
    • Calls for media literacy to counter credulous thinking
    • Facebook “news tip” in 2017? Also on WhatsApp.
    • Do these work?
  • Allessandro Vechchiato – Algorithmic bias
    • News delivery Google, social, app, even newspapers is personalized
    • news value vs. entertainment value
    • How bias interacts with self-selection
    • Built news aggregator app
      • Delivers two different biased news feed
      • measure user readership behavior online
    • Bias between hard and soft news
    • Uses patient preferred samples, where users select their preferred bias, and a randomized population to compare
    • Media diets can be manipulated by algorithms that can overcome individual tastes
  • David Lazer – Searching for the truth… <- contact about LMN
    • How much do people access fake news relative to regular news
    • Fake news list Grinberg et al (2019) [repeated violaters of fact checkers]
    • News is defined using a variety of manual and automated methods
  • ATTITUDES AND BELIEF
  • Sarah Dreier – Religiosity and public policy in congress
  • Eric Dunford – Gender Norms and Violent Behavior in a virtual world <
    • Uses Eve Online
    • Six million players
    • Open sandbox – very little restriction on users. Money laundering is a problem
    • 500,000 players
    • Could be used to find nomad/flock/stampede?
  • Nicolas Velasquez – Ecologies of Online Contention: From Hate to Health
    • There is some mapping in physical and network space
    • Movement from untrusted groups to trusted groups in times of uncertainty
    • Policy 4  -fracture groups into smaller groups based on subsumed differences. Fascist vs. racial supremacist
  • Alexandra Siegal – Can Celebrities reduce prejudice? The effect of Mohamed Salah on Islamophobic Attitudes and Behaviors
    • matrix completion method to predict behavior based on surrounding counties. May be useful for satellite diagnosis as well
  • POSTERS

Phil 9.27.19

7:00 – 7:00 ASRC GOES

  • Replied to Antonio with a plan for the software paper
  • Dissertation
    • More Lit Review – finished Dimension Reduction!
  • Set up TF 2.0 – Nope
  • Started writeup of simulator and sent a status to Erik
  • Waikato meeting
    • First room is running
    • Asked Chris to change “Maximum Anonymity” to “Improved Anonymity”
    • Some discussion about experimental design

Phil 8.26.19

7:00 – ASRC GOES

  • Dissertation – working my way through the lit review section
  • Antonio sent a note about Software Impacts, which provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications (OSP) which describe the application of the software to research and the published outputs.
    • Submissions to Software Impacts consist of two major parts:
      • A short descriptive paper of about three pages including an Impact Overview and references to publications where the software has been used
      • An open source software distribution with support material.
    • So, to get things to fit on GitHub, I worked on getting GPM to work with a smaller library – done
  • Discussions with Aaron about using TF 2.0 xformer on GOES sim data
  • Security training – an hour or so
  • Copied the Waikato JuryRoom proposal to PolarizationGame folder

Phil 8.23.19

7:00 – 4:00 ASRC GEOS

  • More Dissertation
    • Continuing lit review
  • Rework BlueSky paper for air traffic? Meeting with T at 10:00
  • Simulation
    • Need to discuss with Aaron the best way to use the data to train the NN and round-trip the outputs so that they can be used to have the ML model issue commands to the RCS system so that given the outputs of one model, the NN can create commands that cause the same outputs in a separate model
  • Wow. It knows/finds syntactically correct Java. From TalkToTransformer.com:
  • Wow

Phil 8.22.19

7:00 – ASRC GOES

ScottW

  • Dissertation
    • Lit review
    • This, from Colin Martindale CogPsy a NN approach. It’s the central piece:
      • it turns out that language is almost entirely metaphorical (Hobbs,
        1983; Lakoff, 1987; Lakoff & Johnson, 1980). Many of these metaphors are
        spatial. Look back at the last sentence. I asked you to think things through. I told you that something turned out. We bring up topics. We put them on the table. If you could argue with me, Lakoff and Johnson (1980) point out that we would have a war: you might try to attack and shoot down my arguments. I would try to defend them by trying to demolish your position and counterattacking. Lakoff’s argument is that if we took all the metaphors out of language, there would be virtually nothing left. (p 212)
  • More control systems – first pass is working!

RunningSim

InputVector

Phil 8.21.19

City Arts & Lectures: Privacy and Technology

  • This week, a conversation about privacy, ethics, and organizing in the world of technology.Who benefits from the lack of diversity in the tech industry? Does artificial intelligence reflect the biases of those who create it? How can we push for regulation and transparency?  These are some of the questions discussed by our guests, Meredith Whittaker, co-founder of AI Now at NYU and the founder of Google’s Open Research Institute; and Kade Crockford, Director of the ACLU Massachusetts’ Technology and Liberty Program. They appeared at the Sydney Goldstein Theater in San Francisco on June 7, 2019.

7:00 – 8:00 ASRC GOES

  • Printed out some business cards for JuryRoom
  • Antonio has submitted the manuscript – created a TAAS account and verified that its there
  • Dissertation
    • Finished 0.5 pass at chapter 1!
  • Goddard today
    • See if I can get a permanent card? Done!
    • More control system work
  • Meeting with Wayne
    • Send the as-delivered TAAS paper and cover letter. Done
    • Work on getting the ML/Weapons paper reformatted tomorrow
    • Send chapter one of the dissertation
    • I’ll then start sending the chapters as I “complete” them, and we’ll see how it’s going. If the dissertation seems to be coming together well, then we might switch strategies to a from a content-centric to a coherence-centric approach.