diff --git a/qdrant-landing/content/articles/cars-recognition.md b/qdrant-landing/content/articles/cars-recognition.md index f3274058f..fa4a9933b 100644 --- a/qdrant-landing/content/articles/cars-recognition.md +++ b/qdrant-landing/content/articles/cars-recognition.md @@ -1,5 +1,5 @@ --- -title: "Fine-Tuning Image Similarity Search with Quaterion" +title: "Fine Tuning Similar Cars Search" short_description: "How to use similarity learning to search for similar cars" description: Learn how to train a similarity model that can retrieve similar car images in novel categories. social_preview_image: /articles_data/cars-recognition/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/detecting-coffee-anomalies.md b/qdrant-landing/content/articles/detecting-coffee-anomalies.md index 658ffd3ad..f5737dcae 100644 --- a/qdrant-landing/content/articles/detecting-coffee-anomalies.md +++ b/qdrant-landing/content/articles/detecting-coffee-anomalies.md @@ -1,5 +1,5 @@ --- -title: "Metric Learning for Anomaly Detection with Few Labels" +title: "Metric Learning for Anomaly Detection" short_description: "How to use metric learning to detect anomalies: quality assessment of coffee beans with just 200 labelled samples" description: Practical use of metric learning for anomaly detection. A way to match the results of a classification-based approach with only ~0.6% of the labeled data. social_preview_image: /articles_data/detecting-coffee-anomalies/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/embedding-recycler.md b/qdrant-landing/content/articles/embedding-recycler.md index e74122e4a..edd798744 100644 --- a/qdrant-landing/content/articles/embedding-recycler.md +++ b/qdrant-landing/content/articles/embedding-recycler.md @@ -1,5 +1,5 @@ --- -title: "Layer Recycling: Faster Fine-Tuning via Cached Layers" +title: "Layer Recycling and Fine-tuning Efficiency" short_description: Tradeoff between speed and performance in layer recycling description: Learn when and how to use layer recycling to achieve different performance targets. preview_dir: /articles_data/embedding-recycling/preview diff --git a/qdrant-landing/content/articles/faq-question-answering.md b/qdrant-landing/content/articles/faq-question-answering.md index 82775d359..6d37e3c74 100644 --- a/qdrant-landing/content/articles/faq-question-answering.md +++ b/qdrant-landing/content/articles/faq-question-answering.md @@ -1,5 +1,5 @@ --- -title: "Fine-Tune FAQ Question Answering with Quaterion" +title: "Q&A with Similarity Learning" short_description: A complete guide to building a Q&A system with similarity learning. description: A complete guide to building a Q&A system using Quaterion and SentenceTransformers. social_preview_image: /articles_data/faq-question-answering/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/fastembed.md b/qdrant-landing/content/articles/fastembed.md index 50acbaab5..215ac9299 100644 --- a/qdrant-landing/content/articles/fastembed.md +++ b/qdrant-landing/content/articles/fastembed.md @@ -1,5 +1,5 @@ --- -title: "FastEmbed: Fast ONNX Text Embeddings in Python with Qdrant" +title: "FastEmbed: Qdrant's Efficient Python Library for Embedding Generation" short_description: "FastEmbed: Quantized Embedding models for fast CPU Generation" description: "Learn how to accurately and efficiently create text embeddings with FastEmbed." social_preview_image: /articles_data/fastembed/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/gridstore-key-value-storage.md b/qdrant-landing/content/articles/gridstore-key-value-storage.md index d88ff65f9..6d5784dae 100644 --- a/qdrant-landing/content/articles/gridstore-key-value-storage.md +++ b/qdrant-landing/content/articles/gridstore-key-value-storage.md @@ -1,5 +1,5 @@ --- -title: "Gridstore: Qdrant's Custom Key-Value Storage Engine" +title: "Introducing Gridstore: Qdrant's Custom Key-Value Store" short_description: "Why and how we built our own key-value store." description: "Why and how we built our own key-value store. A short technical report on our procedure and results." preview_dir: /articles_data/gridstore-key-value-storage/preview diff --git a/qdrant-landing/content/articles/langchain-integration.md b/qdrant-landing/content/articles/langchain-integration.md index 9e50a826e..aa56b5d80 100644 --- a/qdrant-landing/content/articles/langchain-integration.md +++ b/qdrant-landing/content/articles/langchain-integration.md @@ -1,5 +1,5 @@ --- -title: "LangChain Question Answering with Qdrant and OpenAI" +title: "Using LangChain for Question Answering with Qdrant" short_description: "Large Language Models might be developed fast with modern tool. Here is how!" description: "We combined LangChain, a pre-trained LLM from OpenAI, SentenceTransformers & Qdrant to create a question answering system with just a few lines of code. Learn more!" social_preview_image: /articles_data/langchain-integration/social_preview.png diff --git a/qdrant-landing/content/articles/metric-learning-tips.md b/qdrant-landing/content/articles/metric-learning-tips.md index fed5a2713..c576e89bf 100644 --- a/qdrant-landing/content/articles/metric-learning-tips.md +++ b/qdrant-landing/content/articles/metric-learning-tips.md @@ -1,5 +1,5 @@ --- -title: "Metric Learning: Train Matching Models Without Labels" +title: "Metric Learning Tips & Tricks" short_description: How to train an object matching model and serve it in production. description: Practical recommendations on how to train a matching model and serve it in production. Even with no labeled data. # external_link: https://vasnetsov93.medium.com/metric-learning-tips-n-tricks-2e4cfee6b75b diff --git a/qdrant-landing/content/articles/miniCOIL.md b/qdrant-landing/content/articles/miniCOIL.md index 71a47f28d..1dd073565 100644 --- a/qdrant-landing/content/articles/miniCOIL.md +++ b/qdrant-landing/content/articles/miniCOIL.md @@ -1,5 +1,5 @@ --- -title: "miniCOIL: Lightweight Sparse Neural Retrieval Beyond BM25" +title: "miniCOIL: on the Road to Usable Sparse Neural Retrieval" short_description: "Our attempt to learn from drawbacks of modern sparse neural retrievers" description: "Introducing miniCOIL, a lightweight sparse neural retriever capable of generalization." social_preview_image: /articles_data/minicoil/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/modern-sparse-neural-retrieval.md b/qdrant-landing/content/articles/modern-sparse-neural-retrieval.md index 352f83d7b..93ba3969d 100644 --- a/qdrant-landing/content/articles/modern-sparse-neural-retrieval.md +++ b/qdrant-landing/content/articles/modern-sparse-neural-retrieval.md @@ -1,5 +1,5 @@ --- -title: "Sparse Neural Retrieval Explained" +title: "Modern Sparse Neural Retrieval: From Theory to Practice" short_description: "" description: "A comprehensive guide to modern sparse neural retrievers: COIL, TILDEv2, SPLADE, and more. Find out how they work and learn how to use them effectively." preview_dir: /articles_data/modern-sparse-neural-retrieval/preview diff --git a/qdrant-landing/content/articles/muvera-embeddings.md b/qdrant-landing/content/articles/muvera-embeddings.md index c3e0e9cc7..d2f3ce164 100644 --- a/qdrant-landing/content/articles/muvera-embeddings.md +++ b/qdrant-landing/content/articles/muvera-embeddings.md @@ -1,5 +1,5 @@ --- -title: "MUVERA Embeddings: Faster Multi-Vector Retrieval in Qdrant" +title: "MUVERA: Making Multivectors More Performant" short_description: "Making multi-vector retrieval more efficient by approximating it with single-vector search" description: "Multi-vector representations are superior to single-vector embeddings in many benchmarks. MUVERA embeddings aim to solve the problem of slow multi-vector search by creating a single-vector representation that approximates the multi-vector representation. This single vector can be used for fast initial retrieval using traditional vector search methods, and then the multi-vector representation can be used for reranking the top results." preview_dir: /articles_data/muvera-embeddings/preview diff --git a/qdrant-landing/content/articles/neural-search-tutorial.md b/qdrant-landing/content/articles/neural-search-tutorial.md index e99f29c1e..4c1bf5a95 100644 --- a/qdrant-landing/content/articles/neural-search-tutorial.md +++ b/qdrant-landing/content/articles/neural-search-tutorial.md @@ -1,5 +1,5 @@ --- -title: "Neural Search Tutorial: Build a Service with BERT & Qdrant" +title: "Neural Search 101: A Complete Guide and Step-by-Step Tutorial" short_description: Step-by-step guide on how to build a neural search service. description: Discover the power of neural search. Learn what neural search is and follow our tutorial to build a neural search service using BERT, Qdrant, and FastAPI. # external_link: https://blog.qdrant.tech/neural-search-tutorial-3f034ab13adc diff --git a/qdrant-landing/content/articles/qa-with-cohere-and-qdrant.md b/qdrant-landing/content/articles/qa-with-cohere-and-qdrant.md index 022d69af4..f45bb8fe3 100644 --- a/qdrant-landing/content/articles/qa-with-cohere-and-qdrant.md +++ b/qdrant-landing/content/articles/qa-with-cohere-and-qdrant.md @@ -1,5 +1,5 @@ --- -title: "Question Answering with Cohere Embeddings and Qdrant" +title: "Question Answering as a Service with Cohere and Qdrant" short_description: "End-to-end Question Answering system for the biomedical data with SaaS tools: Cohere co.embed API and Qdrant" description: "End-to-end Question Answering system for the biomedical data with SaaS tools: Cohere co.embed API and Qdrant" social_preview_image: /articles_data/qa-with-cohere-and-qdrant/social_preview.png diff --git a/qdrant-landing/content/articles/search-as-you-type.md b/qdrant-landing/content/articles/search-as-you-type.md index 5577557f9..36ac634d6 100644 --- a/qdrant-landing/content/articles/search-as-you-type.md +++ b/qdrant-landing/content/articles/search-as-you-type.md @@ -1,5 +1,5 @@ --- -title: "Search-as-You-Type: Millisecond Semantic Search in Rust" +title: "Semantic Search As You Type" short_description: "Instant search using Qdrant" description: To show off Qdrant's performance, we show how to do a quick search-as-you-type that will come back within a few milliseconds. social_preview_image: /articles_data/search-as-you-type/preview/social_preview.jpg diff --git a/qdrant-landing/content/articles/serverless.md b/qdrant-landing/content/articles/serverless.md index cfc547437..a73344564 100644 --- a/qdrant-landing/content/articles/serverless.md +++ b/qdrant-landing/content/articles/serverless.md @@ -1,5 +1,5 @@ --- -title: "Serverless Semantic Search with Rust, AWS Lambda & Qdrant" +title: "Serverless Semantic Search" short_description: "Need to setup a server to offer semantic search? Think again!" description: "Create a serverless semantic search engine using nothing but Qdrant and free cloud services." social_preview_image: /articles_data/serverless/social_preview.png diff --git a/qdrant-landing/content/articles/what-is-quantization.md b/qdrant-landing/content/articles/what-is-quantization.md index 2955f2627..85b4c5210 100644 --- a/qdrant-landing/content/articles/what-is-quantization.md +++ b/qdrant-landing/content/articles/what-is-quantization.md @@ -1,5 +1,5 @@ --- -title: "What is Vector Quantization? Scalar, Product & Binary Methods" +title: "What is Vector Quantization?" draft: false slug: what-is-vector-quantization short_description: What is Vector Quantization? Methods & Examples