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September 16-18, 2024
Vienna, Austria
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avatar for Diego Gosmar

Diego Gosmar

Open Voice Interoperability, LF AI&DATA
Chief AI Officer XCALLY

Contact Me

Successful international innovator, Diego Gosmar is a Chief AI Officer specialized in Artificial Intelligence, with particular focus on Generative Conversational AI, Natural Language Processing (NLP), Sentiment Analysis, Conversation Analysis, AI Agent interoperability, Sustainable and Ethical Conversational AI. Diego is member of the Open Voice Interoperability group from the Linux Foundation AI & Data, working on the definition of standards and guidelines for Conversational AI.
Diego is member of the Open Voice Interoperability and Trustmark group from the  Linux Foundation AI & Data, an International no-profit organization, dedicated to the definition of standards and guidelines for Conversational AI ethical and responsible use.
He is the author of the following publication (original research):
Gosmar, D. Conversational hyperconvergence: an onlife evolution model for conversational AI agency. Springer Nature AI Ethics (2024): 
https://doi.org/10.1007/s43681-024-00463-0
He is also the author of a Machine Learning Book available in multiple languages:
https://www.amazon.com/dp/B08GFL6NVM
 
He has been a trainer and speaker in the last ten years for several international events about innovation Telco technologies and AI. Here it is a list of Diego’s speeches:
https://www.gosmar.eu/index.html#events
Diego is member of the IEEE TechEthics Community and IEEE Young Professionals.
Previously, Diego has also led the international expansion of the XCALLY AI-Driven omnichannel software solution, reaching over 60 countries worldwide, managing partners and hundreds of customers scattered from Singapore to the Middle East and Japan, Europe, South Africa, United States, Brazil, and more.
He is the Head of AI Advisor for several start-ups and Mentor at the I3P, the Polytechnic University of Turin Innovative Companies Incubator, including Clearbox.AI leading company specializing in Explainable AI and Synthetic Data generation for AI Ethical models.
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