A new look for Maluuba


At Maluuba, we are fascinated by the potential of artificial intelligence. 

This year we opened the world’s first research lab focused solely on natural language and deep learning. We’re an early leader in using reinforcement learning to solve language-understanding problems and we’re applying our capabilities to power AI experiences in a range of industries.

As we continue to invest in both research and application, we felt it was time to deploy a new brand identity. This new look helps communicate our philosophy and approach while celebrating the importance of our research.

M for Maluuba

Our new logo is a stylised letter M, from our name Maluuba. But it suggests more than that.

In machine learning, we often imagine datapoints to lie on some complex manifold whose shape and properties we would like to discover. Discovering this manifold through algorithms enables us to understand and model the data.

As such, we’ve also taken some inspiration from the Mobius strip, a fun and mind-bending manifold that symbolizes the challenge of this process. It appears to have two sides like any normal ring, but in fact it has only one side. If you started coloring a white Mobius strip blue at a single point and kept coloring, you'd cover the entire surface in blue without ever crossing an edge.

Maluuba's logo also connotes the mathematical symbol for infinity. It represents the seemingly endless possibilities for artificial intelligence and highlights the importance of mathematics in making our algorithms work.

Since Maluuba launched in 2011 we’ve grown to see our technology used in over tens of millions of devices around the world. With the opening of our Montreal lab we’ve increased our focus in three areas of AI research. We’re also developing solutions that can apply across specific industries and verticals.

Accordingly, we needed to update our web presence and we’re excited to share our new website at www.maluuba.com. You’ll also find us actively engaging via our social channels.

We’re excited about the future applications of deep learning and natural language and we’ll be sharing more of our insights, academic papers, datasets, products and applications in 2017 and beyond.


CompanyPaul Gray