DiscoverThe AI FundamentalistsWhy AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning
Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning

Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning

Update: 2023-05-11
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The AI Fundamentalists - Ep1 

Summary

  • Welcome to the first episode. 0:03
    • Welcome to the first episode of the AI Fundamentalists podcast.
    • Introducing the hosts.
  • Introducing Sid and Andrew. 1:23
    • Introducing Andrew Clark, co-founder and CTO of Monitaur.
    • Introduction of the podcast topic.
  • What is the proper rigorous process for using AI in manufacturing? 3:44
    • Large language models and AI.
    • Rigorous systems for manufacturing and innovation.
  • Predictive maintenance as an example of manufacturing. 6:28
    • Predictive maintenance and predictive maintenance in manufacturing.
    • The Apollo program and the Apollo program.
  • The key things you can see when you’re new to running. 8:31
    • The importance of taking a step back.
    • Getting past the plateau in software engineering.
  • What’s the game changer in these generative models? 10:47
    • Can Chat-GPT become a lawyer, doctor, or teacher?
    • The inflection point with generative models.
  • How can we put guardrails in place for these systems so they know when to not answer? 13:46
    • How to put guardrails in place for these systems.
    • The concept of multiple constraints.
  • Generative AI isn’t new, it’s embedded in our daily lives. 16:20
    • Generative AI is not new, but not a new technology.
    • Examples of generative AI.
  • The importance of data in machine learning. 19:01
    • The fundamental building blocks of machine learning.
    • AI is revolutionary, but it's been around for years.
  •  What can AI learn from systems engineering? 20:59
    • Nasa Apollo program, systems engineering.
    • Systems engineering fundamentals world, rigor, testing and validating.
    • Understanding the why, data and holistic systems management.
    • The AI curmudgeons, the AI fundamentalists.


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Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning

Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning

Susan Peich