Who I am, why I write, and why you might be interested — First of all — thank you so much for reading this post! While I’ve been writing on Medium for a couple of years now, I haven’t yet gotten to introducing myself on Medium. I’m a data scientist but my journey has not been typical. I started off getting my PhD…

Organizations are in a race to adopt Large Language Models. Let’s dive into how you can build industry-specific LLMs Through RAG — Companies stand to gain a lot of productivity improvements through LLMs like ChatGPT. But try asking ChatGPT “what is the current inflation in the U.S.” and it gives: I apologize for the confusion, but as an AI language model, I don’t have real-time data or browsing capabilities. My responses are…

A tutorial on fine-tuning the Hugging Face RoBERTa QA Model on custom data and obtaining significant performance boosts — Question Answering and Transformers BERT is a transformer model that took the world by storm in 2019. BERT was trained on unlabeled data by masking words and training the model to predict these masked words based on context. BERT was later fine-tuned on multiple tasks and achieved state of the art performance on many…

LLMs are fundamentally changing the way practitioners evaluate performance . Let’s look at the recent progress towards evaluating LLMs in production. — Prior to the release of Large Language Models (LLMs) like ChatGPT that do extremely well out of the box on custom use-cases, model evaluations were fairly typical. You split your data into training/test/dev sets — trained your model on the training set, and evaluated performance on the test/dev set. I’m…

A comprehensive guide to building a customized chatbot using Generative AI, a popular vector database, prompt chaining, and UI tools — As multiple organizations are racing to build customized LLMs, a common question I have been asked is — what are the tools out there to streamline this process? In this article, I show you how to build a fully functional application for engaging in conversations through a chatbot built on…

A deep dive into considerations for using and hosting large language models — There have been many new exciting developments in Generative AI over the last couple of months. ChatGPT was released in late 2022 and took the world of AI by storm. In response, industries started inquiring into large language models and how to incorporate them into their business. …

Every use case is different — depending on customer needs, and industry-specific guidelines. Learn how to make the right LLM choices, using 4 key rubrics — Over the past few months, I’ve had the opportunity to chat with folks from the legal, healthcare, finance, tech, insurance industries on LLM adoption. And each of them comes with unique requirements and challenges. In healthcare, for example — privacy is king. In finance, getting the numbers right is paramount…

Generative AI has many exciting benefits for the education sector but also poses opportunities for misuse. Here’s how to adapt — emphasizing reasoning, step-by-step thinking, and ethical AI — Key Takeaways Educators must think about whether to try to control or adapt to the new technology to minimize cases of misuse. Suggested solutions such as watermarks and classifiers (that identify AI-generated content) are flawed, and there is no obvious solution to this challenge.

A tutorial on how to use the Microsoft Azure ML catalog for deploying LLM endpoints as APIs and a comparison with AWS — I recently wrote an article about deploying LLMs as APIs using AWS — when someone commented that they would like a similar article but using Azure ML instead. So I decided to write this article discussing how to deploy LLM endpoints on Azure ML. …