This post is divided into three parts; they are: • Understanding Context Vectors • Visualizing Context Vectors from Different Layers • Visualizing Attention Patterns Unlike traditional word embeddings (such as Word2Vec or GloVe), which assign a fixed vector to each…
In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation remains: the inability to effectively process long-context multimodal data such as high-resolution imagery or extended video sequences. Many existing VLMs…
Reliable evaluation of large language model (LLM) outputs is a critical yet often complex aspect of AI system development. Integrating consistent and objective evaluation pipelines into existing workflows can introduce significant overhead. The Atla MCP Server addresses this by exposing…
This post is divided into two parts; they are: • Contextual Keyword Extraction • Contextual Text Summarization Contextual keyword extraction is a technique for identifying the most important words in a document based on their contextual relevance. Source link
Quantization might sound like a topic reserved for hardware engineers or AI researchers in lab coats. Source link
Machine learning models are trained on historical data and deployed in real-world environments. Source link
LLMs show impressive capabilities across numerous applications, yet they face challenges due to computational demands and memory requirements. This challenge is acute in scenarios requiring local deployment for privacy concerns, such as processing sensitive patient records, or compute-constrained environments like…
Using llama. Source link
In this notebook, we demonstrate how to build a fully in-memory “sensor alert” pipeline in Google Colab using FastStream, a high-performance, Python-native stream processing framework, and its integration with RabbitMQ. By leveraging faststream.rabbit’s RabbitBroker and TestRabbitBroker, we simulate a message…
This post is divided into three parts; they are: • Building a Semantic Search Engine • Document Clustering • Document Classification If you want to find a specific document within a collection, you might use a simple keyword search. Source…
