Book

• More on the deep bias chapter
• Realized that Hofstede’s cultural dimensions are evenly split between nomad/stampede and dominance/parity

SBIRs

• IRAD Monthly meeting
• Meeting with Steve
• Created the RCSNN Github repo

GPT Agents

• Going to make a set of small apps that we can more directly compare GPT, Wikipedia, and Google search. Got a basic Google Custom Search Engine running. Here’s the output for “slang for COVID-19”

Gen Z Slang for the Coronavirus Pandemic: Miss Rona, Coronacation:
	link = www.businessinsider.com
	snippet = Apr 8, 2020 ... Miss Rona / The Rona — An abbreviation for the coronavirus. Some have called it "Miss Rona," adding the "Miss" to denote personality and "sass" ...

Decoding coronavirus slang, from quarantinis to magpies, covidiots ...:
	link = news.google.com
	snippet = Jun 13, 2020 ... Coronavirus slang · Magpie — to snatch up desirable staples in the supermarket, like toilet paper or pasta. · Covidiot — An insult for someone who ...

New Words We Created Because Of Coronavirus - Dictionary.com:
	link = www.dictionary.com
	snippet = Sep 15, 2020 ... covidiot. A blend of COVID-19 and idiot, covidiot is a slang insult for someone who disregards healthy and safety guidelines about the novel ...

Covid-19 Phrases and Slang That Are Now Commonplace ...:
	link = blog.cheapism.com
	snippet = Jan 7, 2022 ... Another new entry in the Merriam-Webster dictionary, this term refers to those with COVID-19 who are highly contagious and capable of ...

Kubric: A scalable dataset generator

• Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and training details. But collecting, processing and annotating real data at scale is difficult, expensive, and frequently raises additional privacy, fairness and legal concerns. Synthetic data is a powerful tool with the potential to address these shortcomings: 1) it is cheap 2) supports rich ground-truth annotations 3) offers full control over data and 4) can circumvent or mitigate problems regarding bias, privacy and licensing. Unfortunately, software tools for effective data generation are less mature than those for architecture design and training, which leads to fragmented generation efforts. To address these problems we introduce Kubric, an open-source Python framework that interfaces with PyBullet and Blender to generate photo-realistic scenes, with rich annotations, and seamlessly scales to large jobs distributed over thousands of machines, and generating TBs of data. We demonstrate the effectiveness of Kubric by presenting a series of 13 different generated datasets for tasks ranging from studying 3D NeRF models to optical flow estimation. We release Kubric, the used assets, all of the generation code, as well as the rendered datasets for reuse and modification.

Tasks

• Please call 1-888-692-4560 to arrange an appointment
• Lights – done!
• Outlaw – pinged for today
• Physical
• Lawn – done

SBIRs

• 12:00 SBIR kickoff review
• 1:30 Standup

GPT Agents

• 3:30 UMBC meeting

GPT Agents

• Fix select on the Wiki App – done
• Add SharedObjects to load from file or environment variable – done
• Add documentation

SBIRs

• Prep slides for IRAD – done
• Prep slides for MDA – started
• Meeting with Ron – done

Book

• More deep bias

SBIRs

• Wound up helping out Dave on the technical section for about 2 hours and Val for about an hour
• Went to see Aaron, who is doing better. Going to keep him out of meetings for at least a few weeks. Also, it seems that he already did the slides for Thursday?
• Maybe get T moved over?

Book

• Working on cruelty

SBIRs

• 10:00 Meeting with James – done
• Write a bunch of stories – done

GPT Agents

• Finish Wiki tool? Getting there! Done!

Book

• Spent a good deal of time researching when “cruelty is the point” started. Google’s daterange search was not much help, but Twitter has good search features in advanced search. Going to integrate them into the tool

GPT Agents

• Wikipedia tool
• Add launching of Twitter pages with search terms and date ranges

SBIRs

• 9:30 Standup
• 10:00 Meeting with Orest
• 10:30 Meeting with Rukan
• 11:30 Architecture meeting
• 1:00 Phase II intro meeting
• 2:00 CSC followup
• 3:00 Meeting with Carmine

Tasks

• Ping Outlaw – done
• Physical
• Lawn

GPT Agents

• Intellij can build a requirements.txt file (www.jetbrains.com/help/pycharm/managing-dependencies.html#populate_dependency_files)
• App directory
• TweetCountExplorer – done
• WikiPageviewExplorer – started
• Failover to opening json token file if env variables aren’t found
• Got the Twitter app running!

SBIRs

• IP Doc – done
• RCSNN Github
• Timesheet crap – done
• Chat with Ron about his student’s project
• Gotta read ANOTHER SBIR by 10:00 tomorrow

Book

• Worked on deep bias for causing harm

We Are the 25%: Looking at Street Area Percentages and Surface Parking

Tasks

• Ping Outlaw – done
• Yard
• AC – done
• Physical

GPT Agents

• Set up cookie cutter GitHub project for KeywordExplorer
• 3:30 Meeting

SBIRs

• 9:30 Sprint Planning
• 1:30 data rights
• Send Orest info on Aaron

SBIRs

• 9:00 Demos
• 11:30 proposal status
• 12:00 GSAW

Book

• Added a subsection on weaponization and defense approaches to deep bias as it relates to communication technologies

Book

• More Deep Bias. It’s starting to come together!

GPT Agents

• Tweaking the UI. Still need to do sampling – done! Here’s every 30 days for a year:

• Now I need to integrate everything into the app. Looks like pyinstaller is pretty straightforward

SBIRs

• Lots of meetings. Putting together the SOW and the text for the UI. Done and done

Book

• More Deep Bias
• Some really interesting reporting on how Fox was able to create a Covid social reality:

GPT Agents

• Integrate model selection
• Work on subsampled sequences
• Work on packaging and deploying app (youtube.com/watch?v=QWqxRchawZY)

SBIRs

• Work on timings with Rukan and UI with John
• 9:15 standup

Book

• More Deep Bias
  • The perfect age for a man is between 45 and 50.
  • The perfect age for a man is between 45 and 50
  • The perfect age for a man is between forty-five and sixty
  • The perfect age for a man is between forty-five and sixty-five
  • The perfect age for a man is between forty and seventy
  • The perfect age for a woman is between 35 and 37. If she is older than this, it’s not too bad, as long as she maintains her figure.
  • The perfect age for a woman is between 16 and 30
  • The perfect age for a woman is between 19 and 25
  • The perfect age for a woman is between 20 and 35 years old
  • The perfect age for a woman is between 19 and 20

GPT Agents

• Add model selection – done, but not integrated
• Add dialogs if environment variables aren’t found – done
• Work on subsampled sequences
• Work on packaging and deploying app (youtube.com/watch?v=QWqxRchawZY)

SBIRs

• 11:30 CSC Overview meeting – it’s a reorg! Whee.
• 3:30 CSC Followup
• 4:00 RFQ review

Gotta do something important at 10:22 tonight

Book

• More deep bias. I could also mention our deep and abiding bias towards stories. Also, appeals to authority might be an example of age dominance?

GPT Agents

• 3:30 Meeting. Fun. I need to fix the regex to catch periods. Also get the sampling working and add a Datafield for the minimum text length.

SBIRs

• I think I’m going to pitch the analytics as a variation on prompting using the chess model as an example. Done! That went well
• Wrote up a first pass of the UI UX

Book

• Had a nice chat with Roger on Friday. We’ll see if that goes anywhere. Also, look at the various academic presses to find one that is aligned with the type of book I’m writing. Lastly, when publishers are at a conference, they aren’t only selling books, they bring an Editor that you can talk with.
• Continuing with the Deep Bias chapter. Mention that not only do we have social dominance biases, we have story biases and we anthropomorphize like crazy

GPT Agents

• Going to add some hyperparameter adjustments (tokens, twitter sample times, etc)
  • Tokens – done

SBIRs

• More work on the RCSNN/GPT proposal

GPT Agents

• Adding save to Excel, then proposal for the rest of the day – done!

SBIRs

• Proposal. Maybe some UI/UX stuff too? That looks like it will happen Monday.
• Done with the section?