Noe Achache
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- Ezequiel Lanza21 talks
- Stanko Kuveljic5 talks
- Jeff Vestal5 talks
- Andreas Kollegger16 talks
- Jeroen Overschie4 talks
- Anindita Sinha Banerjee5 talks
| title | conference | date |
|---|---|---|
| AI Development Lifecycle: Learnings of What Changed with LLMs | Big Data & RPA Conference Europe 2024 | 2024-11-19 |
Claim: proof‑of‑concepts with LLMs are trivial but evaluation becomes the bottleneck; neglecting evaluation blocks production. Built a RAG pipeline for hotel… | ||
| Towards a deeper understanding of retrieval and vector databases | PyData Paris 2024 | 2024-09-25 |
Practical takeaways: a deduplication pipeline runs on 15 million images using DinoV2 image embeddings into an HNSW-backed vector DB, exposing that prefiltering… | ||
| RAG for a Medical Company: Technical and Product Challenges AI & Data | Sunny Tech 2024 | 2024-07-04 |
Explains building a Retrieval-Augmented Generation (RAG) system for a medical company's drug documentation aimed at physicians, using embedding models, vector… | ||
| RAG for a medical company: the technical and product challenges | PyData London 2024 | 2024-06-14 |
A RAG for the Vidal is built to let doctors query drug monographs and it uses Chainlit with a vector-backed pipeline over Qdrant and Langsmith. Naive… | ||
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