E.g., 11/17/2019
E.g., 11/17/2019

My AI Boothmate & Me: How Interpreters, Translators, and LSPs can use AI to Drive Quality for the End Client

Marty Zhu

Monday, 25 March, 2019
Free for GALA Members
$75.00 for Non-Members

Details

Industry stakeholders need up-to-date information on the current state of AI in the translation and interpretation (T&I) professions and strategies for acquiring and utilizing such technologies to drive performance. This presentation with provide an overview of the current state of AI, its capabilities, and how it can improve performance. It introduces different types of AI through its training methods, including: supervised learning; transfer learning; unsupervised learning; and reinforcement learning. Once the audience has a basic understanding of AI, participants will brainstorm solutions to real-life problems in the daily work of an interpreter, translator, LSP, and client using the different types of AI as tools. The presentation will conclude with strategies for how senior leadership can manage a newly established AI team effectively and build the organizational structures necessary to drive performance inside the booth and across business functions though leveraging AI.

Marty Zhu

A Mandarin-English conference interpreter active in Silicon Valley, USA, Marty is experienced in interpreting finance, IT, entrepreneurship, and management-related topics since graduating from MIIS in 2008. After 8 years of working in the interpreting industry, Marty increased his education and received an MBA with duel specializations in finance and global management, as well as focused coursework in technology management from UCLA Anderson School of Management. Marty is passionate about interpreting and is actively studying the impact of machine learning (ML) on the translation and interpretation industry. Combining his experience in interpretation with knowledge in business strategy, Marty is keen on finding beneficial applications of ML/NLP technologies that will drive interpretation quality and increase business bottom-line.

randomness