Helene response hampered by misinformation, conspiracy theories
- Officials have sought to tamp down the misinformation that has continued to spread online. The Federal Emergency Management Agency has been updating a webpage seeking to dispute common rumors, while the North Carolina Department of Public Safety has done the same, writing that authorities were “working around-the-clock to save lives and provide humanitarian relief.”
AI-Generated Pro-North Korean TikToks Are Also Bizarre Ads for Supplements
- The ads also use an interesting blend of AI-generated cover images and real images within the slideshow itself. And not all of the ads are about North Korea. Some of them use AI-generated images of Taylor Swift and Jennifer Aniston to shill the supplements, while other slideshows are spreading disinformation about Mpox, are about TikTok trends like “demure,” or claim the supplements are “better than Ozempic.”
Sample ballot of Baltimore County
Grants
- Finish review 14 – Done and submitted!
SBIRs
- Work on LM white paper with Aaron?
- 3:00 Demo kickoff meeting – mostly figuring out what resources (compute, screens, etc) will be needed
GPT Agents
- Work on paper. Wrote the script to convert footnotes to citations. It works well! Had a few issues getting raw strings to behave:
from tkinter import filedialog
import re
from typing import List, Dict
def load_file_to_list(filename:str) -> List:
print("opening {}".format(filename))
try:
with open(filename, 'r') as file:
lines = file.readlines()
return [line.strip() for line in lines]
except FileNotFoundError:
print("Error: File '{}' not found".format(filename))
return []
def save_list_to_file(l:List, filename:str):
print("opening {}".format(filename))
s:str
try:
with open(filename, 'w') as file:
for s in l:
file.write("{}\n".format(s))
except FileNotFoundError:
print("Error: File '{}' not found".format(filename))
return []
filename = filedialog.askopenfilename(filetypes=(("tex files", "*.tex"),), title="Load tex File")
if filename:
filename2 = filename.replace(".tex", "_mod.tex")
filename3 = filename.replace(".tex", "_mod.bib")
# open the pdf file
l:List = load_file_to_list(filename)
p1 = re.compile(r"\\footnote{\\url{(.*?)}}")
p2 = re.compile(r"https://([^/]*)")
s1:str
s2:str
s3:str
l2 = []
cite_dict = {}
count = 1
for s1 in l: # Get each line in the file
#print(s1)
m1 = p1.findall(s1) # find all the footnote urls
for s2 in m1:
#print("\t{}".format(s2))
m2 = p2.match(s2) # pull out what we'll use for our cite
s3 = m2.group(1).strip('www.')
s3 = "{}_{}".format(s3, count)
#print("\t\t{}".format(s3))
olds = r"\footnote{\url{"+s2+"}}"
news = r"\cite{"+s3+"}"
#print("olds = {}[{}], news = {}".format(olds, s1.find(olds), news))
s1 = s1.replace(olds, news)
cite_dict[s3] = s2
l2.append(s1)
print(s1)
save_list_to_file(l2, filename2) # write the modified text to a new file
l2 = []
for key, val in cite_dict.items():
s = "@misc{"+key+",\n"
s += '\tauthor = "{Last, First}",\n'
s += '\tyear = "2024",\n'
s += '\thowpublished = "\\url{'+val+'}",\n'
s += 'note = "[Online; accessed 07-October-2024]"\n}\n'
print(s)
l2.append(s)
save_list_to_file(l2, filename3) # write the citation text to a .bib file
