ChatGPT

Industrial insight and articles from Winder.AI, focusing on the topic ChatGPT

Testing and Evaluating Large Language Models in AI Applications

Published
Author
Dr. Phil Winder
CEO

With the rapidly expanding use of large language models (LLMs) in downstream products, the need to ensure performance and reliability is crucial. But with random outputs and non-deterministic behaviour how do you know if you application performs, or works at all? This webinar offers a comprehensive, vendor-agnostic exploration of techniques and best practices for testing and evaluating LLMs, ensuring they meet the desired success criteria and perform effectively across varied scenarios.

Read more

Retrieval-Augmented Generation (RAG) Examples and Use Cases

Published
Author
Dr. Phil Winder
CEO

Watch our webinar to explore Retrieval Augmented Generation (RAG) and its integration with Large Language Models (LLMs). Learn about RAG use cases, advanced LLM architectures, and techniques to enhance AI applications. Ideal for professionals utilizing or interested in RAG and LLM-powered systems.

Read more

Build a Voice-Based Chatbot with OpenAI, Vocode, and ElevenLabs

Published
Author
Natalia Kuzminykh
Associate Data Science Content Editor

Why might we want to make an LLM talk? The concept of having a human-like conversation with an advanced AI model is an interesting idea that has many practical applications. Voice-based models are transforming how we interact with technology, making interactions more natural and intuitive. By enabling AI to talk, we open the door to numerous practical applications, from accessibility to enhanced human-machine interactions. This guide explores how to create a voice-based chatbot using OpenAI, Vocode and ElevenLabs.

Read more

LLM Architecture: RAG Implementation and Design Patterns

Published
Author
Dr. Phil Winder
CEO

This presentation investigates several common production-ready architectures for RAG and discusses the pros and cons of each. At the end of this talk you will be able to help design RAG augmented LLM architectures that best fit your use case.

Read more

Exploring Small Language Models

Published
Author
Natalia Kuzminykh
Associate Data Science Content Editor

Large language models (LLMs) are powerful but demand significant resources, making them less ideal for smaller setups. Small language models (SLMs) are a practical, resource-efficient alternative, offering quicker deployment and easier maintenance. This article discusses the benefits and applications of SLMs, focusing on their efficiency, speed, robustness, and security in contexts where LLMs are not feasible.

Read more

Big Data in LLMs with Retrieval-Augmented Generation (RAG)

Published
Author
Natalia Kuzminykh
Associate Data Science Content Editor

Retrieval-Augmented Generation (RAG) improves Language Large Models (LLMs) by integrating external data through indexing, retrieval, and generation steps. This method allows LLMs to access up-to-date information and specific details, enhancing their applicability across various domains by providing more accurate, relevant responses and enabling real-time updates and domain-specific customization.

Read more

LLM Prompt Best Practices For Large Context Windows

Published
Author
Natalia Kuzminykh
Associate Data Science Content Editor

This article delves into the nuances of using large language models (LLMs) with large context windows, highlighting the benefits and challenges they present, from enhancing coherence and relevance to demanding more computational resources. Learn practical strategies for prompt design, maintaining narrative coherence, and utilizing attention mechanisms effectively.

Read more

Calculating LLM Token Counts: A Practical Guide

Published
Author
Natalia Kuzminykh
Associate Data Science Content Editor

This article discusses the concept of token counts in large language models (LLMs) and their impact. Tokens are fragments of language used for text processing, representing words, parts of words, or punctuation marks. Code walkthroughs demonstrate how to calculate token counts and examples provide insight.

Read more

The Problem of Big Data in Small Context Windows (Part 2)

Published
Author
Dr. Phil Winder
CEO

An introduction to the challenge of fitting big data into the context windows of LLMs. In this second installment, discover the key strategies involved to improve your use of the context window. Subsequent articles will provide more examples.

Read more
}