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Element AI leverages presence at Montreal conference

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Montreal-based AI firm seeks to make an impact with the global community during Neural Information Processing Systems (NeurIPS) Conference

Montreal-based provider of AI software products Element AI will open its arms to the global AI community in this city, as it plays host to the largest annual AI and deep learning conference this week.

Element AI welcomes the global AI community at Montréal-Pierre Elliott Trudeau International Airport where “MTL is AI” (CNW Group/Element AI)

The Neural Information Processing Systems (NeurIPS) will be held at Palais des Congrès de Montréal December 2nd to 8th. Element AI will welcome local and visiting AI research scientists to share the latest scientific theories and breakthroughs in deep learning, the underlying technology for AI-driven products designed to automate and augment decision-making.

“Since we launched Element AI in 2016, we have focused on high-calibre fundamental research and exploration of what data and computing power can achieve,” says Element AI CEO JF Gagné.  “Working closely with Yoshua Bengio, PhD, Nicolas Chapados, PhD, and Philippe Beaudoin, PhD, we have proven that deep learning and AI innovations are helping bridge the gap between theory and making an impact by solving real-world problems. We welcome all attendees to NeurIPS next week, and invite them to visit us and learn more about our company located here in one of the key hubs of AI development in Canada,” added Gagné.

Dedicated to expanding fundamental research through an open and collaborative approach, Element AI employs over 100 PhDs working with a broad and diverse international network of academic fellows and research institutions. The investment in these global research efforts has resulted in five papers; three published directly by Element AI research scientists and two in collaboration with research fellows and associates.


The three featured AI papers presented at NeurIPS include:

Improving Explorability in Variational Inference with Annealed Variational Objectives.Huang, C.-W., Tan, S., Lacoste, A., and Courville, A.
TADAM: Task dependent adaptive metric for improved few-shot learning. Oreshkin, B.N., Rodriguez, P., and Lacoste, A.
Bayesian Model-Agnostic Meta-Learning. Kim, T., Yoon, J., Dia, O., Kim, S., Bengio, Y., and Ahn, S.

Element AI is committed to harnessing this technology as a force for good.  The company will present a panel session on AI & Human Rights on December 2nd with guests Ed Santow, Australian Human Rights Commissioner, and Eimear Farrell, Advocate and Adviser for Technology and Human Rights, Amnesty International. The company will participate at the AI for Social Good workshop,  presenting research submitted by the Element AI ‘AI for Good’ lab in London, led by Julien Cornebise.

As with algorithms, without equal and diverse representation, biases can be created. In solidarity with the many diversity initiatives at NeurIPS, Element AI is proud to support the Black in AI and Women in Machine Learning gatherings.



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