MLOps Coffee Sessions #148 with Karl Fezer, Intelligence & MLOps co-hosted by Abi Aryan.

// Abstract
This conversation explores various topics, including biases, defining intelligence, and the future of large language models and MLOps. Karl discusses his paper on defining intelligence and how it relates to the increasing interest in Artificial Intelligence. Karl shares his thoughts on the overlap between foundational models and MLOps, emphasizing the importance of making high-impact tasks more efficient and easier. The conversation touched on philosophical tangents but ultimately circled back to practical applications of these concepts.

// Bio
Karl graduated in 2014 from the University of Georgia with a Master's in Science in Artificial Intelligence. Since then, he has continued to stay on top of the latest iterations of Machine Learning and loves trying new open-source frameworks.   
For the last 6 years, he has been purely focused on AI Developer Relations. First at Mycroft, the voice assistant startup, then Intel, Arm, briefly at Wallaroo.ai, and now at Lockheed Martin.   
He currently lives in Seattle and spends his free time writing, reading, sailing, and camping.

// MLOps Jobs board  
jobs.mlops.community

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
Intelligence Primer paper by Karl Fezer and Andrew Sloss: https://arxiv.org/abs/2008.07324
Computing Machinery and Intelligence paper by Alan Turing: https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
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Connect with Karl on LinkedIn: https://www.linkedin.com/in/karlfezer/

Timestamps:

[00:00] Karl's preferred coffee

[00:52] Takeaways

[04:05] Subscribe to our newsletters, join our Slack channel, and keep listening to the podcasts

[04:49] Key to a successful podcast

[10:01] Open source toolkit

[13:04] Evangelizing

[16:46] Living in an adjusted simulator

[17:26] Intelligence Primer paper

[19:51] Intelligence vs Artificial Intelligence

[23:52] Biomimicry

[28:04] Dualism

[29:23] Conscious learning vs Unconscious learning

[34:00] Artificial Intelligence mismatch

[37:07] Infrastructure around machine learning

[41:30] Cloud primitives and current databases collaboration

[43:33] MLOps tools explosion and their duration

[45:04] Open-source tools investment

[48:05] Management service trade-offs

[49:48] Key winning factors for companies with MLOps in the next 5 years

[51:05] Wrap up