Sharon Zhou
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- AWS re:Invent
- Cassandra Summit
- Data + AI Summit
- Data Council
- ODSC (Open Data Science Conference)
- PyTorch Conference
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | breakout | Customer Insights: Scaling Real-World AI with AMD (sponsored by AMD) as AMD Join a dynamic customer panel to hear how leading organizations are accelerating real-world AI workloads using AMD powered solutions on AWS. From generative AI…Show lessJoin a dynamic customer panel to hear how leading organizations are accelerating real-world AI workloads using AMD powered solutions on AWS. From generative AI and large language models to recommendation systems, panelists will share firsthand experiences deploying AMD’s latest technology in production. | Video |
| Oct 22, 2025 | PyTorch Conference 2025 | PyTorch Conference | keynote | Keynote Panel Discussion: Hardwares & Accelerators as AMD | |
| Jun 9, 2025 | Data + AI Summit 2025 | Data + AI Summit | speaker | Composing High-Accuracy AI Systems With SLMs and Mini-Agents as Lamini This session is repeated. For most companies, building compound AI systems remains aspirational. LLMs are powerful, but imperfect, and their non-deterministic…Show lessThis session is repeated. For most companies, building compound AI systems remains aspirational. LLMs are powerful, but imperfect, and their non-deterministic nature makes steering them to high accuracy a challenge. In this session, we’ll demonstrate how to build compound AI systems using SLMs and highly accurate mini-agents that can be integrated into agentic workflows. You'll learn about breakthrough techniques, including: memory RAG, an embedding algorithm that reduces hallucinations using embed-time compute to generate contextual embeddings, improving indexing and retrieval, and memory tuning, a finetuning algorithm that reduces hallucinations using a Mixture of Memory Experts (MoME) to specialize models with proprietary data. We’ll also share real-world examples (text-to-SQL, factual reasoning, function calling, code analysis and more) across various industries. With these building blocks, we’ll demonstrate how to create high accuracy mini-agents that can be composed into larger AI systems. | |
| Apr 22, 2025 | Data Council 2025 | Data Council | talk | RAGs to Riches: Engineering the Future of LLM Systems GenAI & agents as Lamini | |
| Oct 29, 2024 | ODSC West 2024 | ODSC (Open Data Science Conference) | keynote | Untitled as Lamini | |
| Dec 12, 2023 | Cassandra Summit 2023 | Cassandra Summit | keynote | Teaching LLMs New Knowledge as Lamini Imbuing an LLM with new knowledge goes beyond just querying it (prompt-engineering and RAG). |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Chip Huyen | 3 | — | 2025 |
| Jerry Liu | 3 | — | 2025 |
| AMIT RUSTAGI | 2 | — | 2025 |
| Anush Elangovan | 2 | — | 2025 |
| Aparna Dhinakaran | 2 | — | 2025 |
| Chao Wang | 2 | — | 2025 |
| Chintan Patel | 2 | — | 2025 |
| Christopher Hallenbeck | 2 | — | 2025 |
| Cole Bowden | 2 | — | 2025 |
| Craig Wiley | 2 | — | 2025 |
| Elias DeFaria | 2 | — | 2025 |
| Franck Pachot | 2 | — | 2025 |
| Gleb Mezhanskiy | 2 | — | 2025 |
| Jason Wu | 2 | — | 2025 |
| Jeff Boudier | 2 | — | 2025 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.