[homework] 🐖 EA, Corporate Piglets 🐷 & Linear Regression

[Chartiza]

Think

• [x] Read the Kissinger-Schmidt-Huttenlocher thinkpiece on how ChatGPT heralds an intellectual revolution on a grand scale: Wall Street Journal Link or non-paywalled link
• [x] Read Sam Altman's plan for ChatGPT here: https://openai.com/blog/planning-for-agi-and-beyond
• [x] Watch John Oliver's special on ChatGPT and AI: https://www.youtube.com/watch?v=Sqa8Zo2XWc4
• [x] Watch Abigail Thorn's special on Effective Altruism: https://youtu.be/Lm0vHQYKI-Y - Effective Altruism has influenced folks like:
  • Elon Musk and Peter Thiel, who co-founded OpenAI (who created ChatGPT) - Wired link or non-paywalled link
  • Jaan Tallinn (https://en.wikipedia.org/wiki/Jaan_Tallinn#Other_tenures)
  • Shane Legg and Demis Hassabis who created DeepMind (New York Times link and non-paywalled link)
• [x] Read https://www.bbc.com/news/world-asia-china-57268111 -- and reflect on how this was one of the first three data journeys we covered in the first lecture on data thinking.

As you read, ask:

• Can you back up every statement they make?
• Can you clearly define every word written?
• How might data thinking principles apply?
• Do you agree or disagree? Why?
• How do you feel about what is happening now? Feel free to share reflections on Zulip :)

See an example of such critiques here or here.

• [x] Read or watch this introduction to the command line or shell: https://missing.csail.mit.edu/2020/course-shell/

Ask

• [x] Ask ChatGPT for help completing this homework (ask it to summarize any of the above articles or videos, ask for help understanding, ask to explain lines of code, etc!)

Do

• [x] Watch the lecture recording from March 2, 2023
• [x] Review the whiteboard from class: https://www.figma.com/file/5o0fDhQuOBnKAd3gyFi6Ty/230302-logistic-regression-and-version-control-and-latex
• [x] Review the GitHub codespace repository: https://github.com/onefact/datathinking.org-codespace/ (e.g. try running it using the same environment.yml file we created!)
• [x] Review the Jupyter notebook from lecture and rerun it in your codespace: https://github.com/onefact/datathinking.org-codespace/blob/main/notebooks/230302-logistic-regression-math-equation-and-code.ipynb
• [x] use linear regression to analyze the data you visualized in the first homework. You will need to follow the same steps (e.g. ask ChatGPT, write the equation, translate the equation to code, run and debug the code -- all vital data thinking skills :).
• [x] Post a visualization on Zulip of a plot illustrating your linear regression on the data you used for the first homework.
• [x] Post the permalink to the jupyter notebook you created as a comment on this homework here in GitHub issues

[Chartiza]

https://github.com/Chartiza/LifeCost_vs_LifeQuality/blob/main/PriceVsQual.ipynb

[Chartiza]

Added linear regression https://github.com/Chartiza/LifeCost_vs_LifeQuality/blob/main/LinReg.ipynb