Language, Graphs, and AI in Industry // Paco Nathan // #201
MLOps.community
Ensemble Models and Specialized Models in Language Models
The speakers discuss the benefits of using ensemble models and specialized models in language models, highlighting talks from an AI conference in San Francisco. They also mention the success of specialized models in the industry and a startup challenging dominant narratives in the news cycle.
Paco Nathan is the Managing Partner at Derwen, Inc., and author of Latent Space, along with other books, plus popular videos and tutorials about machine learning, natural language, graph technologies, and related topics.
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. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // 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/
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