Compression at the Edge
Official Schedule Context
- Date/time: 2026-07-01 · 2:50pm-3:10pm
- Track/room: Local AI · Track 4
- Speaker(s): Chris Alexiuk, Daniel Han, Asma Beevi, Merve Noyan, Parth Sareen
- Session type/status: session · confirmed
Official Description
Compression at the Edge examines how smaller weights, faster inference, and constrained-memory
deployments are making capable local AI more practical. The panel explores where compressed models
already beat cloud on latency, privacy, cost, or control, what breakthroughs would unlock broader
adoption, and how open model tooling is shaping the edge AI stack. Moderator: Chris Alexiuk
(NVIDIA). Panelists: Daniel Han (Unsloth), Asma Beevi (NVIDIA), Merve Noyan (Hugging Face), Michael
Chiang (Ollama).
Related YouTube Video
Self-Training Agents: Hermes Agent, HF Traces, Skills, MCP & Finetuning — Merve Noyan, Hugging Face (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).
Transcript Status
Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.
People
Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.
Slide Evidence
- Slide-only cropped deck: youtube OV56RddyFuU dense slides (20 viable slide images).
- Related slide/OCR pages:
- youtube OV56RddyFuU dense slides
- youtube OV56RddyFuU reconstructed slides
- youtube OV56RddyFuU slides
- Slide-derived terms:
model,skills,models,gguf,hermes,community,datasets,text,local,llama.cpp,inference,image,search,spaces,jobs,setup,claude,some