Autonomous Agents in the context of Large Language Models With Large Language Models (LLMs) implementations expanding in scope, a number of requirements arise: 1. The capacity to program LLMs and

There has been a recent surge in Visual Programming tools which enable developers to chain large language model prompts into an application, thus creating a conversational user interface. Introduction A

In previous articles, I argued that a data-centric approach should be taken when engineering training data for Natural Language Understanding (NLU). Building on this, this article will discuss the importance

Reaching targeted levels of intent recognition can be quickly achieved by verifying intents before deployment, rather than adopting a corrective strategy as a response. Intro Each organisation has a benchmark

The notion to create workflows (chains) which leverage Large Language Models (LLMs) are necessary and needed. But there are a few considerations, one of which is Prompt Drift. Chaining, also

New approaches and tools built upon the strength of Generative AI are emerging to create engaging conversational experiences. For years, I have been exploring the Conversational AI landscape, analysing how

In order to ensure the successful deployment of any application built on LLM API calls, it is essential to generate true business value from it. For successful scaling of applications

Google launched Vertex AI on 18 May 2021 at Google I/O & it seems like the product has faired well considering all the recent advances in LLMs and Generative AI

NLU pipelines are well-honed and excel in extremely precise tweaking of intents and entities with no significant expense and rapid iteration cycles. I’m currently the Chief Evangelist @ HumanFirst. I

I gained an appreciation for the power of Natural Language Understanding (NLU) engines while experimenting with the predictive and classification capabilities of Large Language Models (LLMs). I’m currently the

What role can prompt engineering play in preventing LLM hallucination, and what constitutes a good LLM prompt? Furthermore, how are OpenAI's models impacting this? I’m currently the Chief Evangelist

Traditional NLU Can Be Leveraged By Following A Hybrid NLU & NLG Approach I’m currently the Chief Evangelist @ HumanFirst. I explore and write about all things at the intersection of

LLMs can be divided into two categories: generative & predictive. The generative capabilities of LLMs have been the subject of much attention and discussion, and rightly so – they are incredibly impressive

Here I will discuss why ChatML, introduced alongside OpenAI's ChatGPT and Whisper APIs on 1 March 2023, is an important development that should not be overlooked. A short Recap The

ChatGPT is currently powered by gpt-3.5-turbo-0301, the most advanced OpenAI language model. Although OpenAI has made the API for this model accessible, the API does not automatically manage conversations

A while ago OpenAI has released the API for The LLM gpt-3.5-turbo, the same model used in ChatGPT. Additionally, the Whisper speech-to-text large-v2 model is available through an API

OpenAI has implemented modes in their playground and development interface, each one having its own dedicated Large Language Model (LLM). OpenAI has been focusing on two key areas to introduce

To start using the HumanFirst [https://www.humanfirst.ai] / Cohere [https://www.cohere.ai] integration you will need a Cohere [https://cohere.ai] API key...in order to get your