nidhinkumarblog.nidhin.dev·14 hours agoFirestore Vector SearchOn Google I/O - 24, Firebase team has introduced Search with Vector embeddings using Firestore. What is RAG? You will be get better results from LLM when you put more information in it. such as writing some long prompts and get the better result for ...Discussfirestore
Kevin NaidooProkevincoder.co.za·May 7, 2024Machine learning for web developersAs someone who works 90% of the time on web-related projects; data science, and machine learning were not my core competencies or areas of interest for most of my career. In the past 2 years, machine learning has become a vital component of my toolbo...Discuss·30 readsMachine Learning
Farzad Sunavalafarzzy.hashnode.dev·Apr 26, 2024FeaturedA Closer Look at Azure AI Search's Scalar Quantization and 'Stored' Property EnhancementsAzure AI Search has recently launched new storage limits, enhancing its capabilities with two innovative features aimed at optimizing price-performance: Scalar Quantization and a new "stored" property for vector fields. This blog post delves into the...Discuss·31 likes·739 readsAzure
Alberto Meneghinimenalb.hashnode.dev·Apr 26, 2024Semantic Search With Vector EmbeddingTraditionally, searching for a concept in a text involves identifying keywords and matching them with some user input.Semantic search provides a different approach. It tries to establish relationships between the meanings of words. With the rise in p...Discussatlas vector search
Fotie M. Constantblog.fotiecodes.com·Apr 11, 2024Explaining Embeddings in Machine Learning like I'm 10Words are very powerful! To help people understand us, we use them to communicate our ideas and thoughts. The funny thing is, although humans understand words, AI models don't actually understand them. All they understand are numbers! Thus, we need t...Discuss·10 likesMachine Learning
Vivek AtwalProengblog.vivekatwal.com·Apr 1, 2024Vector search in elasticsearchhttps://twitter.com/lintool/status/1681333664431460353?s=20 Take on how lucene can win the vector database race. There are few reason why this might happen Pure vector search doesn't work well. Need hybride solutions like 1. HNSW+Inverted index or...DiscussVectorSearch
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 28, 2024Components of a RAG ApplicationRAG (Retrieval-Augmented Generation) includes three main components: Embedding Model: This model takes textual information (queries, documents, etc.) and transforms them into numerical representations called "embeddings." These embeddings capture th...Discussgenerative ai
John Vesterjohnjvester.hashnode.dev·Mar 21, 2024Using pgvector To Locate Similarities In Enterprise DataSoftware engineers occupy an exciting place in this world. Regardless of the tech stack or industry, we are tasked with solving problems that directly contribute to the goals and objectives of our employers. As a bonus, we get to use technology to mi...Discussvector
Kevin NaidooProkevincoder.co.za·Mar 8, 2024How to build a PDF chatbot with Langchain 🦜🔗 and FAISSWhile ChatGPT and other similar models are great and can give you relatively good information on any topic. A common problem is hallucination and verifying the source of the model's response. To improve the accuracy and limit the scope of these LLMs ...Discuss·5 likes·323 readsMachine Learning
Yash SaxenaforDevelop with Yashdevelopwithyash.hashnode.dev·Mar 5, 2024AI & Java : Integrating GPT with SpringBoot using SpringAI, Retrieval Augmented Generation(RAG) and PG Vector DatabaseIn today's dynamic software development landscape, staying ahead means integrating cutting-edge technologies seamlessly into our projects. Spring Boot, with its rapid application development capabilities, is a popular choice for building enterprise-l...Discuss·107 readsSpringAi