LIRNEasia is a regional ICT policy and regulation think tank active across the Asia Pacific

Showcasing Big Data and Machine Learning work at OpenAI SOCML 2016

I was competitively selected to attend the Self-Organizing Conference on Machine Learning 2016 organized by OpenAI which was held in San Francisco on October 7-8, 2016.

OpenAI is a non-profit artificial intelligence (AI) research company initiated by Elon Musk and top research scientists in AI and machine learning (ML) to promote safe and friendly AI. Since its inception in late 2015 the company has attracted top researchers and scientists from both industry and academia to work on most interesting problems of AI. The Self-Organizing Conference on Machine Learning 2016 was an experimental gathering that OpenAI organized for the first time to promote collaboration amongst AI/ML researchers, overcoming the overheads of a conventional academic conference. This is how they presented the motive behind organizing this event.

Machine learning is moving incredibly quickly. To keep up, many practitioners spend several weeks a year at conferences. However, conference presentations are all on work submitted months prior, meaning that people are already intimately familiar with the content (and it’s often already been surpassed).

We’d like to try instead hosting an event focused on the most valuable part of any conference: the people. Please join us for our first Machine Learning Unconference, an experimental gathering driven by its participants rather than an organizing committee.

We had proposed a session on “Machine Learning for Development and Poverty Mapping” which was accepted. This session attracted experts with diverse backgrounds and led to an informative knowledge sharing session on utilizing machine learning and data science for development purposes. We had also done a poster presentation on our ongoing work (see poster HERE) which elicited interesting comments and input from participants, which will inform and benefit our ongoing research and potentially lead to collaborations in future.


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