[행사/세미나] Developing customer-facing product features using machine learning and generative AI(23.3.16. 10:30)
- 인공지능융합학과(일반대학원)
- 조회수2383
- 2023-03-08
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Title: Developing customer-facing product features using machine learning and generative AI
Speaker: Dr. Marshal Gavalda https://www.linkedin.com/in/marsalgavalda/
Time : 2023 March 16th 10:30 ~ 11:45
Location: Hybrid
- Online: https://xinics.zoom.us/j/84223153778 (Passcode: 37923448)
- In-person: 26223
Language: English speech & English slides
Abstract:
As Machine Learning and Generative AI becomes a core component of any forward-looking company, how can we weave ML-driven functionality into the products and services we offer? This talk will explain the methodology we follow at Square when developing ML-driven customer-facing product features, a process based on paying close attention to four key and interdependent aspects, namely: Design, Modeling, Engineering, and Analytics.
Design is concerned about the usefulness and remarkability of the feature, and thus cares about the overall functionality, ease of use, and aesthetics of the experience.
Modeling is concerned about the accuracy of the ML model, and thus cares about the training data, the features and performance of the model, and —crucially for a customer-facing product— how the application behaves in the face of the mistakes the model will inevitably make (e.g, false positives, false negatives, or lack of predictions above a certain confidence).
Engineering in turn is concerned about running the ML model at scale, and thus cares about the latency, throughput, and robustness of the inferencing service.
Finally, Analytics is concerned about the adoption of the feature, and thus cares about the instrumentation to capture detailed usage, the definition of success metrics and dashboards, and the collection of feedback in a manner that the ML model can learn from, and thus keep improving over time.
When all these aspects align, we can create remarkable ML-powered experiences that delight our customers.
Bio:
Marsal Gavalda is a senior R&D executive with deep expertise in speech, language, and machine learning (ML) technologies. Marsal currently leads the Commerce ML team at Square and develops ML-driven seller personalization and commerce intelligence features that serve Square's overarching purpose of economic empowerment. Previously, Marsal headed the Machine Intelligence team at the social media platform Yik Yak and also served as the Director of Research at MindMeld (acquired by Cisco). Marsal holds a PhD in Language Technologies and an MS in Computational Linguistics, both from Carnegie Mellon University, and a BS in Computer Science from Universitat Politècnica de Catalunya. He is the author of over thirty technical and literary publications, fourteen issued patents, and is fluent in six languages. Every summer Marsal organizes a science and humanities summit in his hometown of Barcelona on topics as diverse as machine translation, music, or the neuroscience of free will.
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