Episode description
Episode description
Recently, Zapata AI, BMW, and MIT's Center for Quantum Engineering collaborated to solve a complex problem: how can you most efficiently schedule vehicle production? This problem needs to take into account many many variables, so how did the team optimize the process? With AI of course! Listen to this episode to find out more about how exactly they did and what results they found.
My two hand-picked episodes for you:
- https://podcasters.spotify.com/pod/show/thequantumpod/episodes/Yudong-Cao-and-Quantum-Generative-AI---Episode-11-e206uia/a-a9fihof
- https://podcasters.spotify.com/pod/show/thequantumpod/episodes/Alejandro-Perdomo-Ortiz--Yudong-Cao--and-Quantum-Optimization-in-the-Real-World---Episode-4-e14tfk1/a-a66sd56
More recommended resources:
- How We Harness Industrial Generative AI for Optimization: https://zapata.ai/industrial-generative-ai-for-optimization/
- Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the Race to Practical Quantum Advantage: https://zapata.ai/publications/synergy-between-quantum-circuits-and-tensor-networks-short-cutting-the-race-to-practical-quantum-advantage/
- Zapata, BMW and MIT’s The Center for Quantum Engineering Publish Research On Optimizing Vehicle Production Planning Using Quantum-Inspired Generative AI Techniques: https://zapata.ai/news/bmw-optimizes-vehicle-production-planning-using-quantum-inspired-generative-ai-techniques/
Intro/Outro music: Oblivious by Nihilore (https://www.nihilore.com/synthwave)
Nihilore license: https://creativecommons.org/licenses/by/4.0/legalcode
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The Quantum Pod is produced by Zapata AI
Host: Ethan Hansen
Guests: Shima Bab Hadiashar, Will Banner, and Marcin Ziolkowski
Editing: Ethan Hansen
Special thanks to: Mick Emmett and Rob Kerstens