Tasks

• Spanish!

SBIRs

• Aim to finish commenting code today
• Spent too much time making a better placeholder callback:

def implement_me(self):
    """
    A callback to point to when you you don't have a method ready. 
    Prints "implement me!" to the output and
    an abbreviated version of the call stack to the console
    :return:
    """
    #self.dprint("Implement me!")
    self.dp.dprint("Implement me! (see console for call stack)")
    fi:inspect.FrameInfo
    count = 0
    for fi in inspect.stack():
        filename = re.split(r"(/)|(\\)", fi.filename)
        print("Call stack[{}] = {}() (line {} in {})".format(count, fi.function, fi.lineno, filename[-1]))
        count += 1

• 9:15 Standup
• Aaron has topic clustering working:

GPT Agents

• Put together a doc with existing and new prompts (“Vaccines are”, “Vaccines are a”, “I/We/<other groups> think that vaccines are”)
• I need to do some research on if the API can really do this, but I’d like to make the new corpus of threaded tweets that are pulled because they mention general terms like “COVID”, “VIRUS”, and “VACCINE”, then train the models and drill down. I still like the idea of training monthly models starting in Nov 2019 to present.
• It does look like threads have more engagement and would be harder for bots to generate.
  • Change in Threads on Twitter Regarding Influenza, Vaccines, and Vaccination During the COVID-19 Pandemic: Artificial Intelligence–Based Infodemiology Study
  • Automatically Identifying Fake News in Popular Twitter Threads
• I learned how to make a thread so I can look for it: