Tokens In, Engagement Out: Training LLM-Recommenders
Devansh Tandon
- When
- Tuesday, June 3010:45 AM – 11:05 AM · 20 min
- Where
- Track 7San Francisco, CA · imported from ai.engineer's public schedule feed
Speaker
Principal Product Manager, Meta
Devansh Tandon works on AI Research & Product at Meta, leading AI & recommendations teams. He is a founding member of a new AI research group (Meta Recommendation Systems Research) to develop LLM foundation models & recommendation systems across Meta: to power Instagram, Facebook, Ads. Previously, Devansh led ML/AI teams at Google for 7 years, building the largest ML models across Ads, Search, Discover, YouTube, Gemini. He worked on YouTube's recommendation engine, which drives 70% of video watch time for 2 billion+ daily active users. At DeepMind, he incubated a new generative recommendation system using Gemini, and published multiple research papers. Devansh graduated Magna Cum Laude from Yale University, with a BS in Computer Science and Economics.
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For developers: this programme is open data — JSON, iCal, schedule XML and an MCP endpoint.Show endpointsHide
- JSONEvery published session and speaker, in one request./aie-worldsfair-2026-import/feed.json
- iCalSubscribe in Google, Apple or Outlook Calendar./aie-worldsfair-2026-import/feed.ics
- Schedule XMLfrab / pentabarf — the format conference apps import./aie-worldsfair-2026-import/feed.xml
- MCP + RESTPoint Claude at the programme. OpenAPI 3.1 included./agents
No key, no signup, CORS open. Everything here is generated from the same data the organisers edit.