The Hallway Track
14 tracked signals on embeddings.
Google releases EmbeddingGemma 2, a sub-billion open model unifying text, image, video, and audio embeddings on-device.
“a picture of a cat, the word cat, and the sound of a cat are all mapped close to each other in a shared high-dimensional embedding space”
Agentic AI demands a new enterprise data category—agent context—forcing storage to become systems of context.
“Storage needs to evolve. It needs to move from being what we've always known as a system of record, to now a system of context.”
Google releases EmbeddingGemma 2 under Apache 2.0, enabling portable open-weight embeddings
“I don't think it makes sense to use a closed, proprietary, hosted-only model.”
Google DeepMind releases EmbeddingGemma 2, an open lightweight multimodal embedding model
Gemma 4's per-layer embeddings boost model performance without increasing compute parameters
“It's a very nice way to increase the performance of the model without actually increasing parameters because these parameters are stored on flash storage.”
TurboQuant compresses agent retrieval embeddings to 3-4 bits, cutting memory cost 5x without degrading search quality.
“Today, we will see how you can cut memory cost of agent retrieval five times without breaking your search.”
SQL Server 2025 adds native vector search enabling semantic, meaning-based queries beyond keyword matching.
“But vector search is completely different uh in the sense uh that it really is a search for meaning.”
Microsoft's CAF-aligned Azure AI landing zone delivers enterprise RAG at millions-of-documents scale
“The result is a grounded response traceable to enterprise data, not a hallucination.”
Microsoft SQL Server adds native DiskANN vector search alongside traditional relational data
Use LLM-hallucinated tags plus vector embeddings to match against large existing vocabularies
llm 0.33 adds composable templates, per-call embedding keys, and reasoning summary options
Hugging Face launches OlmoEarth Studio embedding exports for downstream analysis
Hugging Face introduces multi-vector late interaction embedding support in Sentence Transformers
Hugging Face releases guidance on training multi-vector embedding models with Sentence Transformers