Coffee Sessions #148

Intelligence & MLOps

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.

Transcript

In this episode

Karl Fezer

Karl Fezer

AI Developer Advocate, Lockheed Martin

Karl graduated in 2014 from the University of Georgia with a Masters 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.

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Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.

Abi Aryan

Abi Aryan

Host

Abi is a machine learning engineer and a live streamer. Over the past six years, her focus has been building machine learning models for various industries including short-form video hosting, OTT, e-commerce, insurance tech, etc., for startups across the US, UK, Canada, and India. Prior to that, she was a Data Science Fellow with Insight Toronto and a Visiting Research Scholar at UCLA working in AutoML, MultiAgent Systems, and Emotion Recognition. In her free time, she helps produce the MLOps Community Podcast.