Eugene Yan
A speaker presented on system design for recommendation systems and search at the San Francisco Big Analytics meetup, sharing recorded video and slides. The talk was delivered in July 2021. The presentation covers engineering approaches for building recommendations and search infrastructure.
Why real-time RecSys? What does the system design look like in industry? How to build an MVP?
MLOps Community - System Design for RecSys & Search
Eugene Yan · 4 years ago
DataScience SG Meetup - RecSys, Beyond the Baseline
Eugene Yan · 6 years ago
AI Engineer 2025 - Improving RecSys & Search with LLM techniques
Eugene Yan · 1 year ago
RecSys 2021 - Papers and Talks to Chew on
Eugene Yan · 4 years ago
RecSys 2022: Recap, Favorite Papers, and Lessons
Eugene Yan · 3 years ago
RecSys 2022 Keynote - Is the Juice Worth the Squeeze?
Eugene Yan · 3 years ago
The daily briefing
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TLDRocket
21 July 2026
The open-weight AI model market hit an inflection point today as Alibaba and Kimi released trillion-parameter competitors that challenge the closed-model orthodoxy—just as Washington moved to restrict them. Alibaba's Qwen 3.8 Max (2.4 trillion parameters) and Kimi K3 (2.8T) are going open-weight, with K3 ranking first on Frontend Web App Arena and fourth on agentic benchmarks, signaling that scale and transparency can coexist. The timing matters: while U.S. policymakers weigh layered restrictions on Chinese open models, technical experts are pushing back hard, arguing that closed gardens actually hurt security and competition more than they help. The real fragmentation risk isn't technical—it's regulatory.
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