Chores:
- Call Jim Donnie’s
- Schedule oil change
SBIRs
- Finishing and submitting CUI paper
- 4:30 Book club
- Installed an ancient printer driver and it worked!
GPT Agents
- 2:00 LLM Meeting
Chores:
SBIRs
GPT Agents
The eclipse was cool. Even with clouds, it’s magical:

That’s the view to where the sun is still shining. We could also see the eclipse faintly through the clouds, which must have been how most people saw it before rapid travel. The light was so faint, it was easy to imagine the sun and the moon fighting. I swear I saw sparks.
SBIRs
Prepping to go to the Eclipse! The forecast is looking pretty good!

SBIRs
GPT Agents
Dont you (forget NLP): Prompt injection with control characters in ChatGPT
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5:00 power washer
CUI 2024 paper:
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GPT Agents
Need to move the crown appointment
Review board faults Microsoft for ‘cascade’ of errors in China hack
SBIRs
Call powerwasher
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Pick up the truck if the rain stays away this morning – done!
Good Organizational Lobotomy writeup: The Descent of Elon Musk
SBIRs
GPT Agents
AI experts: Racist audio of Baltimore County principal’s voice is fake – The Baltimore Banner
Example: Pandas Excel output with a chart
##############################################################################
#
# An example of converting a Pandas dataframe to an xlsx file with a chart
# using Pandas and XlsxWriter.
#
# SPDX-License-Identifier: BSD-2-Clause
# Copyright 2013-2024, John McNamara, jmcnamara@cpan.org
#
import pandas as pd
# Create a Pandas dataframe from some data.
df = pd.DataFrame({"Data": [10, 20, 30, 20, 15, 30, 45]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter("pandas_chart.xlsx", engine="xlsxwriter")
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name="Sheet1")
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets["Sheet1"]
# Create a chart object.
chart = workbook.add_chart({"type": "column"})
# Get the dimensions of the dataframe.
(max_row, max_col) = df.shape
# Configure the series of the chart from the dataframe data.
chart.add_series({"values": ["Sheet1", 1, 1, max_row, 1]})
# Insert the chart into the worksheet.
worksheet.insert_chart(1, 3, chart)
# Close the Pandas Excel writer and output the Excel file.
writer.close()
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GPT Agents
Here’s Google’s generative API/playground/documentation site: Vertex AI
SBIRs

On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial
Tasks
SBIRs
Just realized that Fritz Lang’s Metropolis is an example of a deepfake/KillerApp:
…the false Maria unleashes chaos throughout Metropolis, driving men to murder and stirring dissent among the workers.
https://en.wikipedia.org/wiki/Metropolis_(1927_film)
Deepfake Kari Lake video shows coming chaos of AI in elections
Drove back from Greenville NC yesterday. Eleven hours or so. Electric cars are still not common on the long stretches between cities. I live in the Baltimore/DC region, and I’d say 1 in 20 cars that I see on the roads at this point is electric, with a big mix of manufacturers. Still mostly Teslas. On my drive, I only saw Teslas, and not very many of them. Charging infrastructure is solid. Leaving with a full charge, it required 2 SuperCharger recharges to cover the 535 miles. Probably $20 in electricity? And autopilot makes everything much nicer, though you always have to be ready for phantom braking.
Need to ping Mario, Ossi, and James about Eclipse coordination
IUI 2024 Notes
Information visualization and Visual Analytics

25% confident
Applications of Language Models
Generative AI: Theory and Applications
Got accepted for my talk at the 92nd MORS symposium!
IUI 2024 Notes
I had an interesting chat yesterday with Ossi about Active Measures Leading up to and since October 7. We need some time to sit down and talk. My sense is that all sides have been under prolonged external influence for a long time with the specific intent to raise the political temperature so that exactly this situation happened.
Keynote: Prof. Krzysztof Gajos (check Google Scholar for references)
HCAI, Bias and Fairness in AI
AI Tools, User Interfaces and Interaction
AI for Health
Dinner Banquet – fun 🙂
Had a thought for the day. For a learning assignment, have students build a context prompt that lets an LLM answer a question on the rubric correctly. Bonus points if the models is able to answer a question that is outside the domain where a raw LLM has struggled. This way you have a project that requires students learning the topic, and also exposes them to weaknesses and strengths of LLMs. Not sure if this is a good idea, but it could be worth poking at.
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