LeeBoonstra.dev

Writing Generative AI, LLM, Dialogflow, Conversational AI & CCAI Articles

Beside writing this blog, I’ve also published my work elsewhere.

Press

Google/Kaggle Whitepaper Prompt Engineering

Whitepaper Prompt Engineering by Lee Boonstra
When thinking about a large language model input and output, a text prompt (sometimes accompanied by other modalities such as image prompts) is the input the model uses to predict a specific output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt. However, crafting the most effective prompt can be complicated. Many aspects of your prompt affect its efficacy: the model you use, the model’s training data, the model configurations, your word-choice, style and tone, structure, and context all matter. Therefore, prompt engineering is an iterative process. Inadequate prompts can lead to ambiguous, inaccurate responses, and can hinder the model’s ability to provide meaningful output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt.
When you chat with the Gemini chatbot, you basically write prompts, however this whitepaper focuses on writing prompts for the Gemini model within Vertex AI or by using the API, because by prompting the model directly you will have access to the configuration such as temperature etc.
This whitepaper discusses prompt engineering in detail. We will look into the various prompting techniques to help you getting started and share tips and best practices to become a prompting expert. We will also discuss some of the challenges you can face while crafting prompts.

Read my Prompt Engineering whitepaper on Kaggle: https://www.kaggle.com/whitepaper-prompt-engineering

External Blogs & Articles

Apress - the Definitive Guide to Conversational AI With Dialogflow and Google Cloud

The Definitive Guide to Conversational AI with Dialogflow and Google Cloud
Written by an expert Google developer advocate who works closely with the Dialogflow product team.

Build enterprise chatbots for web, social media, voice assistants, IoT, and telephony contact centers with Google’s Dialogflow conversational AI technology. This book will explain how to get started with conversational AI using Google and how enterprise users can use Dialogflow as part of Google Cloud Platform. It will cover the core concepts such as Dialogflow essentials, deploying chatbots on web and social media channels, and building voice agents including advanced tips and tricks such as intents, entities, and working with context.

The Definitive Guide to Conversational AI with Dialogflow and Google Cloud Platform also explains how to build multilingual chatbots, orchestrate sub chatbots into a bigger conversational platform, use virtual agent analytics with popular tools, such as BigQuery or Chatbase, and build voice bots. It concludes with coverage of more advanced use cases, such as building fulfillment functionality, building your own integrations, securing your chatbots, and building your own voice platform with the Dialogflow SDK and other Google Cloud machine learning APIs.

After reading this book, you will understand how to build cross-channel enterprise bots with popular Google tools such as Dialogflow, Google Cloud AI, Cloud Run, Cloud Functions, and Chatbase.

The Definitive Guide to Conversational AI with Dialogflow and Google Cloud

Find on Apress. ISBN 978-1-4842-7014-1 & ISBN 978-1-4842-7013-4

​​What You Will Learn

  • Discover the different conversational AI tools offered by Google
  • Work with Dialogflow and Contact Center AI
  • Create Dialogflow projects for individuals and for enterprise usage
  • Secure your chatbots on Google Cloud Platform with Compute, Cloud Functions, and Cloud Run
  • Build webhook fulfillments
  • Integrate your virtual agent with your own web and voice platforms

Who This Book Is For

Everyone who is interested in building chatbots for the web, social media, voice assistants, or contact centers.

FWW: All royalities of my book, will go to charity; “Stichting Meer Dan Gewenst”.

The Ultimate Guide to Conversational Analytics - White Paper

It seems that most organizations that use chat and / or voice bots still make little use of conversational analytics. A missed opportunity, given the smart use of conversational analytics can help to organize relevant data and improve the customer experience.

While setting up conversational analytics, there are three specific categories of metrics relevant to designing a voice bot: conversation-related metrics, chat session & funnel metrics, and bot health metrics. Conversation-related metrics can help understanding conversations and shining a light on questions like what’s been said, by who, when, and where? To effectively monitor conversation-related metrics, data could be stored in a data warehouse: an enormous database to which several data sources can be connected. Here, you can store as much structured data as you want, whether it’s website data, website logs, login data, advertising data, or Dialogflow chatbot conversations. The more data you gather, the better you can understand and help your customers.

Do you use chat or voice to communicate with customers? Then it is important that you have your conversational analytics in order and you collect the right data. This is the only way you can optimize your channel as well as possible and improve the customer experience. In this white paper, the DDMA Committee Voice tells you all about it. Download it now from: https://ddma.nl/ca/

O'Reilly - Hands-on Sencha Touch 2 Book

Build snappy web apps for mobile devices with Sencha Touch 2, the user interface JavaScript framework built specifically for the mobile Web.

With this book, you’ll learn how to build a complete HTML5-based multi-device app…
Find on Amazon. ISBN: 9781449366520

Disclaimer: The opinions stated here are my own, not those of my company. - 2022 ® Lee Boonstra