To provide a better understanding of the concepts related to large language models (LLMs) and Retrieval-Augmented Generation (RAG) systems, which are integral to AI product development, Anand offered a detailed discussion by explaining the workflow of the RAG evaluation framework. RAG Evaluation Fram...
Five of the most common and complex challenges organizations face in putting large language models into production and how to tackle them. Credit: Michael Rivera Many organizations are building generative AI applications driven by large language models (LLMs), but few are transitioning successfully ...
Large language models (LLMs) have created a new paradigm for machine learning applications. On the one hand, you have a machine learning model that you can customize for your own needs and tasks. On the other hand, you don’t have access to the model’s weights and hyperparameters. You ...
Learn to build AI applications using the OpenAI API. Start Upskilling For Free If you're captivated by the transformative powers of Generative AI and LLMs, this tutorial is perfect for you. Here, we explore LangChain - An open-source Python framework for building applications based on Large ...
We defined a test intest_hallucinations.pyso we can find out if our application is generating quizzes that aren’t in our test bank. This is a basic example of a model-graded evaluation, where we use one LLM to review the results of AI-generated output from another LLM. ...
In the context of natural language processing (NLP), embedding models are algorithms designed to learn and generate embeddings for a given piece of information. In today’s AI applications, embeddings are typically created using large language models (LLMs) that are trained on a massive corpus of...
Why Even Test LLMs? While we all know what LLMs are, at least on a basic level. However, when it comes to implementing one into your processes, it becomes challenging to picktheLLM for your project. There are two concerns when it comes to picking an LLM.First, overall performance again...
ALarge Language Model (LLM)is a type of generative artificial intelligence (AI) that relies on deep learning and massive data sets to understand, summarize, translate, predict and generate new content. LLMs are most commonly used innatural language processing(NLP) applications like ChatGPT, where...
Deep learning, a subset of machine learning, uses neural networks with multiple layers (hence 'deep') to model and understand complex patterns in datasets. It's behind many of the most advanced AI applications today, from voice assistants to self-driving cars. Deep Learning in Python Skill Tra...
“Top 10 for LLM Applications 2025,”a comprehensive guide to the most critical security risks to LLM applications. The 2025 list shifts the priority level of some of the risks we saw inlast year’s list, as well as introduces some new risks that hadn’t previously reached the top 10. ...