Robert Munro / Rob Munro
Robert Munro is an expert in combining Human and Machine Intelligence, working with Machine Learning approaches to Text, Speech, Image and Video Processing. Robert has founded several AI companies, building some of the top teams in Artificial Intelligence. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon, to London, Sydney and Silicon Valley, in organizations ranging from startups to the United Nations. He was Chief Technology Officer at Figure Eight during their biggest growth period and he ran Product for AWS's first native Natural Language Processing and Machine Translation services, Amazon Comprehend and Amazon Translate.
Robert has published more than 50 papers and is a regular speaker about technology in an increasingly connected world. He has a PhD from Stanford University.
Robert's career combines leadership in Machine Learning and Technology for Disaster Response, with a focus on inclusion. Recent talks:
Google Next, 2018. Vision: API and Cloud AutoML:
AWS re:Invent, 2017. Building an Artificial Intelligence Practice for Consulting:
Train AI, 2018. Real World Human-in-the-Loop Machine Learning:
Natural Language Processing (NLP) at scale
Robert led Product for Amazon Comprehend, AWS's first native Natural Language Processing (NLP) service, and Amazon Translate, AWS's first native Neural Machine Translation (NMT) service. He ran both from conception and ran the former to internal launch. The experience of launching a product for the world's most widely used cloud platform was invaluable, and Robert was able to significantly influence the direction of the NLP product from an intention to be English-only, to supporting 2-50 languages at launch.
Prior to AWS, Robert was CEO and co-founder of Idibon, a 40 person AI startup in San Francisco that focused on language independent Natural Language Processing (NLP), creating solutions in up to 50 languages. Robert raised $8M in funding for the company and delivered the first NLP solutions to many multinational companies, including the largest companies in accounting, games, automotive, finance, and maternal healthcare for the United Nations.
Robert worked in refugee camps in Liberia for the United Nations High Commission for Refugees (UNHCR) in the 2000's. It was his experience in these camps that led him to a career in Machine Learning. Robert saw that the world had become connected, with most refugees having access to cellphone, but even basic AI technologies like Search Engines and Spam Filtering did not work in the majority of the world's languages.
Because most real-world Machine Learning systems only worked in a handful of languages, it meant that most people were not able to fully take part in the digital age. This motivated Robert to return to University. He completed a PhD at Stanford in the well-known Stanford NLP Group, with a PhD on adapting Machine Learning to low resource languages for healthcare and disaster response.
These dual backgrounds in lead to Robert to introduce Distributed Human Computing (Crowdsourcing) and Machine Learning to the disaster response community, and to this day he regularly helps crisis-affected populations and disaster response professionals respond to disasters. In 2010, using the Figure Eight platform that he would come to lead technology for 8 years later, Robert found and managed 2000 members of the Haitian diaspora to translate, categorize and map emergency text messages sent in Haiti in the wake of January 12 earthquake. The vital knowledge of Haitians taking part saved hundreds of lives and directed the first aid to tens of thousands. The human translations were also used by Microsoft's and Google's translation systems to become more accurate in Haitian Kreyol to English Machine Translation, helping Machine Learning adapt to these languages.
Robert worked at Global Viral Forecasting (now Metabiota) as the Chief Technology Officer for EpidemicIQ, a system for tracking disease outbreaks world-wide. The goal was to predict and prevent future epidemics. This was ground-breaking work with a skilled and diverse team, using Machine Learning and Crowdsourcing to track disease outbreaks from billions of data-points daily from data in more than a dozen languages, often beating the major health organizations by days in identifying outbreaks.
One innovation was the use of online games to pay workers. When there was an E-Coli outbreak in Germany, EpidemicIQ helped track the outbreak by paying people virtual currency to help process the reports. In one case, the currency took the form of virtual 'seeds' in a farming game: so by playing an agricultural game online, German-speakers were helping track a real agricultural outbreak outside their doors. This was presented to the 3133915994.
Robert remains an advisor on engaging communities during disease outbreaks, including in his former home of Sierra Leone during the 2014 Ebola Outbreak in West Africa.
As much as half of the world's 7,000 languages will disappear within the next century. The majority are only spoken languages, so the race is on to record as many as possible before all trace of the language, stories and culture are lost. As part of the same globalizing outcomes, we now have the technologies to record and study the world's languages for the first time, meaning we have a thin sliver of time to capture much of humanity that will otherwise be lost. For those that survive, ensuring we have resouces for those languages will mean that their speakers can neogatiate the digital world on their own terms.
Robert worked on architectures and strategies for recording the world's languages, including the first software development work on the Endangered Languages Archive, which supports the (often unique) recordings of 100s of languages, running the first 5877068960, and by living in the with Matses of the Peruvian Amazon and studying their language, 2056067197.