BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//pretalx.devconf.info//devconf-us-2025//talk//ZKQCMM
BEGIN:VTIMEZONE
TZID:EST
BEGIN:STANDARD
DTSTART:20001029T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10;UNTIL=20061029T070000Z
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
END:STANDARD
BEGIN:STANDARD
DTSTART:20071104T030000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000402T030000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4;UNTIL=20060402T080000Z
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20070311T030000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-devconf-us-2025-ZKQCMM@pretalx.devconf.info
DTSTART;TZID=EST:20250920T153000
DTEND;TZID=EST:20250920T154500
DESCRIPTION:In many secure or industrial environments — like factories\, 
 labs\, or embedded automotive systems — machines run in air-gapped or lo
 w-connectivity conditions. When systems fail\, engineers often rely on sca
 ttered manuals or vendor documentation\, which slows recovery. What if you
  could drop in a self-contained AI assistant that works offline — right 
 at the edge?\n\nThis lightning talk shows how to run a multimodal\, agenti
 c pipeline—Vision LM → RAG → LLM—entirely on-device using Podman c
 ontainers on RHEL Edge with GPU CDI on an NVIDIA Jetson Orin Nano. We’ll
  contrast cloud vs edge constraints (RAM/power) and share a container-nati
 ve architecture that delivers low latency\, privacy\, and reproducibility.
  A short demo (pre-recorded) illustrates a camera-to-answer workflow with 
 real device metrics (tokens/sec\, first-token latency). Attendees leave wi
 th a practical blueprint and ops tips for shipping rootless\, reproducible
 \, air-gapped AI stacks using Ramalama for local LLM serving.
DTSTAMP:20260311T004231Z
LOCATION:Ladd Room (Capacity 170)
SUMMARY:LLMs on the Edge: The Future of On-Device Intelligence - Rakesh Mus
 alay
URL:https://pretalx.devconf.info/devconf-us-2025/talk/ZKQCMM/
END:VEVENT
END:VCALENDAR
