Practical AI: Machine Learning, Data Science, LLM

Explainable AI that is accessible for all humans

Mar 28, 2023

45:37

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Highlights

AI Chapters

Episode notes

How to Use Conversational AI to Generate Fluff

02:27

Issues with Pre-Trained Data in Generative Transformers

01:24

The Challenges of the AI Community

02:40

Introduction

3min

How to Integrate Your Model Into Production

3min

How to Use Conversational AI to Generate Fluff

2min

The Evolution of Toxicity in AI

2min

How to Reach Out to an Ontology and Communicate With It

3min

How to Use Generative AI to Engage People

2min

How to Use Conversational AI to Engage Users

2min

How to Use AI to Influence Your Business

6min

Artificial Intelligence and Bias

2min

10.

The Importance of Access to Generative AI

2min

11.

The Challenges of Open AI

2min

12.

The Importance of Giving Users Credit

5min

13.

The Joy of Automated AI

2min

14.

How to Use Chat GPT to Increase Your Business

2min

15.

Combining Knowledge Graphs and Ontologies With Generative Models

1min

16.

The Future of Attribution and AI

2min

17.

The Future of AI

2min

18.

Practical AI: A Look at the Future of Visual Thinking

2min

We are seeing an explosion of AI apps that are (at their core) a thin UI on top of calls to OpenAI generative models. What risks are associated with this sort of approach to AI integration, and is explainability and accountability something that can be achieved in chat-based assistants?

Beth Rudden of Bast.ai has been thinking about this topic for some time and has developed an ontological approach to creating conversational AI. We hear more about that approach and related work in this episode.

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