Harvey Ducayhddatascience.tech·Dec 5, 2024Uncovering Semantic Relationships with the Universal Sentence EncoderAs the amount of text data we interact with on a daily basis continues to grow, the ability to quickly identify meaningful connections between pieces of information becomes increasingly valuable. This is where semantic similarity models can be incred...DiscussTensorFlow
Yoeven D KhemlaniforJigsawStack Blogblog.jigsawstack.com·Nov 28, 2024Introducing Multimodal Multilingual Embedding Model for Images, Audio and PDFs in AlphaWe launched our State-of-the-art embedding model that supports a wide range of document types including PDF, Images, Audio and more. Quick Technical specs: Support inputs: text, image, pdf, audio Supports auto embedding chunking: yes 80+ languages...Discussembedding
Rodrigo Mansueliblog.mansueli.com·Nov 21, 2024Executing Dynamic JavaScript Code on Supabase with Edge FunctionsSupabase is a powerful backend service that makes it easy for developers to work with real-time data, authentication, and more. One of the most interesting features it offers is Supabase Edge Functions, which allow you to create and run serverless fu...Discuss·28 readssupabase
karthik hublitext-embedding.hashnode.dev·Nov 21, 2024From Words to Vectors: Understanding the Magic of Text EmbeddingTransformers are the backbone of large language models (LLMs) and have revolutionized natural language processing by enabling models to handle vast amounts of text efficiently. Unlike traditional neural networks, transformers use a self-attention mec...DiscussAI
Sai Prasanna Maharanasaimaharana.hashnode.dev·Oct 23, 2024Embedding Techniques in LangChain and How to Implement ThemIntroduction Embeddings are numerical representations of text, images, or other data types that capture their semantic meaning in a vector space. In natural language processing (NLP) and applications involving large language models (LLMs), embeddings...DiscussGen AIlangchain
Muneer Ahmedthisismuneer.hashnode.dev·Oct 1, 2024You are the average of the five others around you.At its core, modern Natural Language Processing is built on a fascinating idea: "A word is characterized by the company it keeps." When I first learned about vector embeddings, this concept instantly reminded me of the saying "You are the average of ...Discuss·1 like·41 readsvector embeddings
Richard Kovacsrichardkovacs.hashnode.dev·May 1, 2024Three Key Concepts to Build Future-Proof AI ApplicationsCurrent AI models won't reach AGI. Not even larger ones. GPT-5, GPT-6, Llama 4, Llama 5, Gemini Ultra Pro Max, it doesn't matter. We are currently living in the age of mixed computing. Deterministic computing is still the dominant type, as the majori...DiscussAI
Yash Saxenadevelopwithyash.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·395 readsSpringAi
Akriti Upadhyayakritiu.hashnode.dev·Feb 28, 2024Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and QdrantIntroduction In 1950, when Alan Turing introduced the term "Machine Intelligence" in his paper "Computing Machinery and Intelligence," no one had imagined that one day, in the future, it would lead to various innovations using artificial intelligence...Discussimagebind
Akshat Jainautonomics.hashnode.dev·Sep 15, 2023Understanding Knowledge Embeddings in SuperAGIThe quality of output generated by AI agents is limited by LLM constraints such as information cutoff & lack of quality data for niche tasks, which can fail to deliver context-rich, domain-specific outputs. However, by integrating knowledge embedding...Discussembedding
