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Jo Kristian Bergum

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titleconferencedate
AI is here – time to throw away our search engines?Berlin Buzzwords 20262026-06-07
Claims that AI simply replaces search get tested with concrete techniques: use vector embeddings for multimodal data, apply BM25 + rerank by computing…
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Agentic Retrieval: Building Self-Optimizing Search SystemsBerlin Buzzwords 20262026-06-07
Claims that agents compress relevance feedback from months to seconds and can tune scoring, schema and indexing in real time, demonstrated by Hornet’s…
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Boosting Ranking Performance with Minimal SupervisionBerlin Buzzwords 20232023-06-18
With just three labeled queries and documents, an LLM (including open-source 3B models or GPT-style APIs) generates synthetic questions for every document…
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The Debate Returns (with more vectors): Which Search Engine?Berlin Buzzwords 20232023-06-18
Five open-source engines compare concrete tradeoffs: one reports 48 billion vectors indexed in a single cluster and adds GPU-accelerated embedding inference…
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AI-powered Semantic Search; A story of broken promises?Berlin Buzzwords 20222022-06-12
Semantic vector search often fails out of domain: models trained on MS MARCO: 9M passages, 500k labels, 3,600 test queries give great in-domain results but…
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The Debate: Which Search Engine?Berlin Buzzwords 20212021-06-15
Three engines compared by concrete claims and limits: Vespa advertises native tensor support, ANN with HNSW and hybrid term+vector ranking, true real‑time…
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Search and Sushi; Freshness CountsBerlin Buzzwords 20212021-06-15
Open source Vespa implements a mutable in‑memory index backed by an immutable disk index and a transaction log so updates are durable and immediately visible…
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