BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Denver
BEGIN:DAYLIGHT
DTSTART:20260308T030000
TZOFFSETFROM:-0700
TZOFFSETTO:-0600
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:MDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20261101T010000
TZOFFSETFROM:-0600
TZOFFSETTO:-0700
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:MST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260908T020806Z
UID:3086AF94-532A-4518-B0C7-87819A3CF9F9
DTSTART;TZID=America/Denver:20260921T183000
DTEND;TZID=America/Denver:20260921T200000
DESCRIPTION:“Certainty in an Uncertain AI Age” addresses one method of 
 verifying the responses of various Large Language Models (LLMs) like Claud
 e\, ChatGPT\, and Copilot. By using prompt templates and agentic AI\, user
 s can understand and respond to the inherent biases in every LLM. A simple
  agentic framework will be provided.\n\nAgenda: \n“Certainty in an Uncer
 tain AI Age” addresses one method of verifying the responses of various 
 Large Language Models (LLMs) like Claude\, ChatGPT\, and Copilot. By using
  prompt templates and agentic AI\, users can understand and respond to the
  inherent biases in every LLM. A simple agentic framework will be provided
 .\n\nDowntown Paninos - 604 N Tejon Street\, Colorado Springs\, Colorado\,
  United States\, 80903
LOCATION:Downtown Paninos - 604 N Tejon Street\, Colorado Springs\, Colorad
 o\, United States\, 80903
ORGANIZER:smehalingam@binghamton.edu
SEQUENCE:7
SUMMARY:Certainty in an Uncertain AI Age
URL;VALUE=URI:https://events.vtools.ieee.org/m/575789
X-ALT-DESC:Description: <br /><p>&ldquo\;Certainty in an Uncertain AI Age&r
 dquo\; addresses one method of verifying the responses of various Large La
 nguage Models (LLMs) like Claude\, ChatGPT\, and Copilot. By using prompt 
 templates and agentic AI\, users can understand and respond to the inheren
 t biases in every LLM. A simple agentic framework will be provided.</p><br
  /><br />Agenda: <br /><p>&ldquo\;Certainty in an Uncertain AI Age&rdquo\;
  addresses one method of verifying the responses of various Large Language
  Models (LLMs) like Claude\, ChatGPT\, and Copilot. By using prompt templa
 tes and agentic AI\, users can understand and respond to the inherent bias
 es in every LLM. A simple agentic framework will be provided.</p>
END:VEVENT
END:VCALENDAR