Waterloo-based Machine Learning startup Maluuba has officially opened its new Montreal office devoted to deep learning R&D research, and the startup is doing it with some big-name help.

Maluuba helps machines think, reason and communicate with human-like intelligence. Its new office has been in the works since December, 2015.

Perhaps most excitingly, it has partnered with machine learning and neural computation expert Yoshua Bengio, from the Montreal Institute for Learning Algorithms (MILA). Also coming on board will be reinforcement learning expert Richard Sutton from the Alberta Innovates Centre for Machine Learning.

According to many experts within the Montreal artificial intelligence (AI) startup community, Bengio holds near-legendary status within the field of Machine Learning in Canada, and even North America. His work at the Universite de Montreal has led to advancements in the field for at least two decades.

“Deep learning” is a new algorithmic paradigm for Machine Learning that allows the technology to emulate some of the capabilities of humans, like image recognition, speech recognition, natural language process and more.

Maluuba’s new research lab will be staffed by 13 deep learning research scientists led by Maluuba’s CTO, Kaheer Suleman, an information retrieval and artificial intelligence expert. With a focus on the development of proprietary algorithms to solve language problems, Maluuba’s goal is to build “the world’s most advanced research facility in deep learning and AI.”

“While we’re closer to the goal of getting machines to exercise reasoning and understand conversational language, we still have a long way to go,” said Bengio. “Maluuba has made great strides with its contributions to the field of machine learning and NLP. Their long-term vision and focus on truly perfecting the methodology is refreshing and makes me confident that we’ll see exciting tech and research advancements from them this year.”

Maluuba said in a release it’s focused on two research streams within machine learning: dialogue and machine reading. Within these realms, the startup claims it has achieved the highest performance by an existing system when tested against external performance tests.

“For a computer to understand humans speaking in natural language and respond appropriately, it needs to capture and represent a large amount of knowledge that is not just words, but also common sense and context about the topic being discussed by the human,” said Sam Pasupalak Maluuba’s CEO. “Maluuba is working… to design systems that can represent knowledge and answer questions in natural language. The potential applications of this research are staggering.”

Maluuba uses deep reinforcement learning to solve language-understanding problems and in training machines to model decision-making capabilities of the human brain. In January, the company raised $9 million in funding, and has raised $11 million in total.

The company currently enables interactive natural language and conversational dialogue experiences in over 50 million smart devices globally including IoT, mobile phones and smart TVs. Supporting more than 10 languages, Maluuba provides its technology for several industry OEMs including LG.