Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning
May 11, 2023
The AI Fundamentalists - Ep1
- 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.
Do you have a question or a discussion topic for the Fundamentalists? Let them know at email@example.com