MLOps podcast #201 with Paco Nathan, Managing Partner at Derwen, Inc., Language, Graphs, and AI in Industry.

// Abstract

Let's talk about key findings from these conferences, specifically summarizing teams that have ROI on machine learning in production: what are the things in common they're doing, and what are the most important caveats they urge other teams to consider when getting started? Because these key takeaways aren't found in the current AI news cycle.

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// Related Links

AI Conference: https://aiconference.com/

K1st World: https://www.k1st.world/

Corunna Innovation Summit: https://corunna.dataspartan.com/

"Cloud Computing on Amazon AWS EC2" UC Berkeley EECS guest lecture (2009)

https://vimeo.com/manage/videos/3616394

"Hardware - Software - Process: Data Science in a Post-Moore’s Law World"

https://www.nvidia.com/en-us/ai-data-science/resources/hardware-software-process-book/

“LLMs in Production: Learning from Experience” by Waleed Kadous @ Anyscale

https://www.youtube.com/watch?v=xa7k9MUeIdk

"Supercharging Industrial Operations with Problem-Solving GenAI & Domain Knowledge" by Christopher Nguyen @ Aitomatic

https://www.k1st.world/2023-program/supercharging-industrial-operations-with-problem-solving-genai-domain-knowledge

“The Next Million AI Systems” by Mark Huang @ Gradient: https://www.youtube.com/watch?v=lA0Npe4PqFw

"AI in a Box" by Useful Sensors

https://usefulsensors.com/#products

"Opportunities in AI - 2023" by Andrew Ng

https://www.youtube.com/watch?v=5p248yoa3oE

"Advancing the Marine Industry Through the Harmony of Fishermen Knowledge and Al" by Akinori Kasai @ Furuno

https://www.k1st.world/2023-program/advancing-the-marine-industry-through-the-harmony-of-fishermen-knowledge-and-al

Macy conferences (1941-1960)

https://en.wikipedia.org/wiki/Macy_conferences

https://www.asc-cybernetics.org/foundations/history/MacySummary.htm

https://press.uchicago.edu/ucp/books/book/distributed/C/bo23348570.html

second-order cybernetics

https://pangaro.com/designconversation/wp-content/uploads/dubberly-pangaro-chk-journal-2015.pdf

https://en.wikipedia.org/wiki/Second-order_cybernetics

Project Cybersyn

https://jacobin.com/2015/04/allende-chile-beer-medina-cybersyn/

https://thereader.mitpress.mit.edu/project-cybersyn-chiles-radical-experiment-in-cybernetic-socialism/

https://99percentinvisible.org/episode/project-cybersyn/

https://medium.com/@rjog/project-cybersyn-an-early-attempt-at-iot-governance-and-how-we-can-apply-its-learnings-5164be850413

https://www.sustema.com/post/project-cybersyn-how-a-chilean-government-almost-controlled-the-economy-from-a-control-room

https://transform-social.org/en/texts/cybersyn/

Humberto Maturana, Francisco Varela: Autopoeisis

"De Maquinas y Seres Vivos"

"Everything said is said by an observer"

https://proyectos.yura.website/wp-content/uploads/2021/06/de_maquinas_y_seres_vivos_-_maturana.pdf

https://en.wikipedia.org/wiki/Autopoiesis_and_Cognition:_The_Realization_of_the_Living

Fernando Flores

(led Project Cybersyn, imprisoned, later worked with Prof. Terry Winograd @ Stanford, the grad advisor for what became Google)

https://lorenabarba.com/gallery/prof-barba-gave-keynote-at-pycon-2016/

https://conversationsforaction.com/fernando-flores

"Navigating the Risk Landscape: A Deep Dive into Generative AI" by Ben Lorica and Andrew Burt

https://thedataexchange.media/mitigating-generative-ai-risks/

"SpanMarker" by Tom Aarsen @ Hugging Face

https://tomaarsen.github.io/SpanMarkerNER/

Examples of "the math catching up with the machine learning":

Guy Van den Broeck @ UCLA

https://web.cs.ucla.edu/~guyvdb/talks/

Charles Martin @ Calculations Consulting

https://weightwatcher.ai/