Category Archives: AI
Creating a multi-agent application — Part 3
In the previous post, we examined how to load the libraries we need and how to create the Blogger agent. In this post, we’ll examine the Research agent. You’ll no doubt notice the pattern of defining the template, the agent … Continue reading
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Creating a multi-agent application – Part 1
The following text was created by a multi-agent application designed to create blog posts. In my next post we’ll take the application apart, step by step. For now, here is a test run with the prompt Use of multiagents in … Continue reading
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ReAct and Agents in AI
In the previous post, we looked at the use of Chain of Thought (CoT) reasoning in the context of LLMs. For an LLM to take action in the world, however, it needs agents. The paradigm for this is called ReAct—that … Continue reading
AI Reasoning and Planning
Until very recently, it was observed that LLMs had a very hard time with complex problems. Context was lost, memory of previous steps was distorted, and so forth. This led to unreliable results (hallucinations) and, consequently, to a lack of … Continue reading
PEAS for Agent AI
A classic AI framework to define an agent’s task environment is PEAS. It stands for:
The R in RAG
In my previous post we looked at saving to the vector store. In this short post we’ll look at retrieving that information. The simple search is a good starting point and depends on writing a good prompt, but we can … Continue reading
RAG In Detail
In my previous post I walked through a RAG example but glossed over the details. In this post I’ll back up and walk through the program line by line. The key steps in RAG are
RAG – A Quick Example
In the previous blog post, we imported a few Python modules and configured our AI key, using Colab. In this blog post we’ll use Retrieval-Augmented Generation (RAG) to extend an LLM that we’ll get from OpenAI. I’ll use a number … Continue reading
Creating Our Python AI Project
As noted in a previous blog post, we’ll be building our project on two platforms: Python and .NET (C#). For Python, we’ll build on Colab. For now, you can use a free account. The first step is to get an … Continue reading
Get on the bus, or get run over by it
On March 28 I’m presenting on Fundamentals of AI to the Boston Code Camp. While I will cover what you need to know about the various aspects of using and creating various AI components, the key message is it is … Continue reading
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HyperVideo Features
In a previous post, I laid out the basic idea of an AI demonstration project I call HyperVideo. In this short post, I’d like to review some of the features I imagine for this project. Some will be implemented in … Continue reading
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CoPilot Gets Us Started
In yesterday’s post I described the project I want to build: HyperVideo. This morning I created a new Blazor application and the first thing I did was to open CoPilot and give it a prompt. Specifically, I asked it to … Continue reading
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