Truth-based AI - LLMs and knowledge graphs

Episode 2. Back to the basics of LLMs and knowledge graphs. Also in this episode, timely discussions about truth-based AI, regulations for AI, and data privacy effects on generative AI

Show Notes

What’s NOT new and what is new in the world of LLMs. 3:10

What is AI and subsequently LLM regulation going to look like for tech organizations? 5:55

What does it mean to regulate generative AI models? 7:51

  • Concerns with regulating generative AI models.
  • Concerns about the call for regulation from Open AI.

What is data privacy going to look like in the future? 10:16

  • Regulation of AI models and data privacy.
  • The NIST AI Risk Management Framework.
  • Making sure it's being used as a productivity tool.
  • How it's different from existing processes.

What’s different about these models vs old models? 15:07

  • Public perception of new machine learning models vs old models.
  • Hallucination in the field.

Does the use of chatbots change the tendency toward hallucinations? 17:27

  • Bing still suffers from the same problem with their LLMs.
  • Multi-objective modeling and multi-language modeling.

What does truth-based AI look like? 20:17

Algorithms have a really interesting potential application which is a plugin library model. 23:00

  • Algorithms have an interesting potential application.
  • The benefits of a plugin library model.

What’s the future of large language models? 25:35