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Miguel Fierro is a Principal Data Science Manager at Microsoft and holds a PhD in robotics.
From Robotics to Recommender Systems // MLOps Podcast #240 with Miguel Fierro, Principal Data Science Manager at Microsoft.
Huge thank you to Zilliz for sponsoring this episode. Zilliz - https://zilliz.com/.
// Abstract
Miguel explains the limitations and considerations of applying ML in robotics, contrasting its use against traditional control methods that offer exactness, which ML approaches generally approximate. He discusses the integration of computer vision and machine learning in sports for player movement tracking and performance analysis, highlighting collaborations with European football clubs and the role of artificial intelligence in strategic game analysis, akin to a coach's perspective.
// Bio
Miguel Fierro is a Principal Data Science Manager at Microsoft Spain, where he helps customers solve business problems using artificial intelligence. Previously, he was CEO and founder of Samsamia Technologies, a company that created a visual search engine for fashion items, allowing users to find products using images instead of words, and founder of the Robotics Society of Universidad Carlos III, which developed different projects related to UAVs, mobile robots, humanoid robots, and 3D printers. Miguel has also worked as a robotics scientist at Universidad Carlos III of Madrid (UC3M) and King’s College London (KCL) and has collaborated with other universities like Imperial College London and IE University in Madrid. Miguel is an Electrical Engineer from UC3M, PhD in robotics by UC3M in collaboration with KCL, and graduated from MIT Sloan School of Management.
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// Related Links
Website: https://miguelgfierro.com
GitHub: https://github.com/miguelgfierro/
RecSys at Spotify // Sanket Gupta // MLOps Podcast #232 - https://youtu.be/byH-ARJA4gk
Recommenders joins LF AI & Data as new Sandbox project: https://cloudblogs.microsoft.com/opensource/2023/10/10/recommenders-joins-lf-ai-data-as-new-sandbox-project/
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Timestamps:
[00:00] Miguel's preferred coffee
[00:11] Takeaways
[02:25] Robotics
[10:44] Simpler solutions over ML
[15:11] Robotics and Computer Vision
[19:15] Basketball object detection
[22:43 - 23:50] Zilliz Ad
[23:51] Mr. Recommenders and Recommender systems' common patterns
[31:35] Embeddings and Feature Stores
[42:34] Experiment ROI for leadership
[47:17] Hi ROI investments
[51:13] LLMs in Recommender Systems
[54:51] Wrap up
