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[ Purposes of Collection and Use of Personal Information ]
- Basic Information of the person who requested speaker, for the purpose to respond
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- Enhancement of service quality (Customer-oriented service)

[ Period of Retention and Use of Personal Information ]
- In principle, personal information collected from speaker request and newsletter subscription will be retained in the database for 3 years. It is only used for speaker request related consultation, newsletter mailing service and enhancement of service quality. All personal information is destroyed immediately after 3 years.

SPEAKERSSearch for the Speakers

Laurence Moroney
Google, (Former) Global AI Advocacy Lead
AI / Robotics, Technology(ICT)

Laurence Moroney is a Thought Leader, Innovator, and Visionary. With a storied career spanning multiple breakthroughs in artificial intelligence and machine learning, Laurence Moroney stands at the forefront of global technology discourse.

As a best-selling author and award-winning AI researcher, Laurence has shaped the AI strategies of leading corporations and governments, making complex concepts accessible and actionable. Whether it’s delivering captivating keynotes, engaging in panel discussions, leading workshops, or providing expert training, Laurence translates cutting-edge technology into strategic opportunities for all. 

At Google, Laurence launched the transformative TensorFlow framework, and brought it to millions of developers through online advocacy, helping build AI in some of the world’s largest companies. His online courses for developers were cited by the World Economic Forum as essential skills for the ‘jobs of tomorrow’. 

As a fellow of the AI Fund Laurence helps startups cut through the complexity of makiing decisions around how and where to invest in AI. 

Organization / Position
Google (Former) Global AI Advocacy Lead
Microsoft (Former) Senior Developer Evangelist / Product Manager
Education
Cardiff University Physics and Computer Science
Career
AI Fund Senior Fellow
Publication
AI and Machine Learning for On-Device Development
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