Maluuba advisor Yoshua Bengio speaks with Harry Shum, Microsoft EVP, AI & Research
When Microsoft acquired Maluuba in January 2017, Maluuba’s highly respected advisor, the deep learning pioneer Yoshua Bengio, agreed to continue advising Microsoft on its artificial intelligence efforts. Bengio, head of the Montréal Institute for Learning Algorithms, had advised Maluuba since 2015, providing guidance and insight to our continued research into language understanding .
Recently, he visited Microsoft’s Redmond, Washington, campus, and took some time for a chat with Harry Shum, EVP AI & Research at Microsoft. Their conversation spanned the history of deep learning research, recent breakthroughs and what the future holds for artificial intelligence.
Frames dataset released
Maluuba's Frames dataset is designed to help drive research that enables truly conversational agents that can support decision-making in complex settings. Prepared through human-to-human conversations, the dataset contains complex, natural dialogues with users considering different options, comparing packages, and progressively building rich descriptions through conversation.
News and updates
the next challenges for reinforcement learning research
14 Mar 2017
We explore some of the remaining challenges in the field of reinforcement learning.
Towards Artificial General Intelligence: Creating curious machines
10 Jan 2017
Teaching artificial agents to accomplish tasks through efficient information-seeking behaviour.
memory and machines: a milestone study in goal-oriented dialogue systems
21 Dec 2016
Access our paper and Frames, our new dataset for goal-oriented dialogue research.
Dedicated to tackling big challenges in language understanding and artificial intelligence
With a focus on deep learning and reinforcement learning, our growing team of renowned experts is working closely with industry and academia. Now, as part of Microsoft, Maluuba is accelerating our approach to drive breakthroughs in AI research and application. Learn more about our vision, access our academic publications and interact with our public datasets.
At Maluuba, we believe that language understanding is inextricable from solving Artificial Intelligence.
Our goal is to teach machines to model human-like reasoning and the decision making capabilities of the brain.