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Nuance Research Conference 2017: Reflections on Deep Learning and AI innovation

Nuance’s annual Research Conference brings together Nuance’s research team with leading minds in academia to tackle and discuss a range of topics on the advancements and challenges to be solved in Deep Learning and AI. In this post, I share key takeaways from speakers such as John Searle, as well as point to how Nuance will drive forward innovation in these areas to create the next generation of solutions for automotive, healthcare, customer care and beyond.

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bringing together leading minds to tackle advancements in AI

Every year, I look forward to our annual Nuance Research Conference (NRC), an opportunity for our global research organization to come together to collaborate, converse, and drive forward Nuance’s vision for designing and building intelligent, conversational solutions.

This year, Deep Learning and AI took center stage along with sessions focused on advancing innovation in ASR, TTS, speech signal enhancement, and language innovation (to name a few), and our discussions have primarily centered around how we at Nuance can continue to pioneer advancements that improve the dialogue between people and technology.

We were fortunate to kick off the NRC with a presentation given by John Searle, a thought leader in theories of the mind and distinguished professor at the University of California, Berkeley.  Prof. Searle is well known for his work on speech acts, the “Chinese room” thought experiment, and, as we found out during the course of his talk, a passionate user of Dragon dictation.

Searle spoke extensively about AI and the associated problems of consciousness, arguing that  a state of consciousness that is inclusive of all the feelings and sentience of a being is a prerequisite of true intelligence. So, till we find it how consciousness originates in the brain we won’t be able to reproduce it in machines, and we can’t claim today’s AI systems to be accurate models of the human brain. What we can claim, though, is that AI systems are great engineering solutions for practical problems, and Prof. Searle was very supportive of that idea. This is an important topic, and one of much discussion, for those of us who are building successful applications of AI every day.  Personally, I found it rewarding to see how such a fundamental philosophical question (which I had read about back in my university days) seems more relevant than ever, and sparked an engaged discussion with my Research colleagues.

Following John’s keynote, Prof. Barbara Grosz, Higgins Professor of Natural Sciences at Harvard University, and a pioneering researcher on the cooperation of artificial and human agents working toward a common goal, spoke about computational models of collaboration and to support healthcare coordination.

Again, it was amazing how this work, which has grown over decades of research, remains relevant today, as my colleagues in the healthcare IT research industry work to design and build assistants that collaborate with doctors to improve patient care.  It also raises questions of interoperability, for instance, how will all the AI systems that are now appearing everywhere work together and support their human users.

In total, by the end of the conference, we’ll see more than 100 contributions by our research colleagues from around the world, including additional keynotes by external speakers covering themes from the fields of Artificial Intelligence, and its use in Enterprise, Mobile, and Healthcare applications, as well as foundational technologies like speech recognition and synthesis, natural language understanding, clinical language understanding, voice biometrics, signal enhancement, and of course, underlying all of these progress on deep learning.

Both keynote speakers stressed that this is the time where AI takes center stage and received attention as never before. This energy and excitement was clearly also felt here at the Nuance Research conference. We can also expect great innovations to come out in the next few years.

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