A few years ago, I had to make one of the biggest decisions of my life: continue as a professor at the University of Melbourne or move to another part of the world to help build a brand new university focused entirely on artificial intelligence.
With the rapid development we have seen in AI over the past few years, I came to the realization that educating the next generation of AI innovators in an inclusive way and sharing the benefits of technology across the globe is more important than maintaining the status quo. I therefore packed my bags for the Mohammed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi.
The world in all its complexity
Today, the rewards of AI are mostly enjoyed by a few countries in what the Oxford Internet Institute dubs the “Compute North.” These countries, such as the US, the U.K., France, Canada, and China, have dominated research and development, and built state of the art AI infrastructure capable of training foundational models. This should come as no surprise, as these countries are home to many of the world’s top universities and large tech corporations.
But this concentration of innovation comes at a cost for the billions of people who live outside these dominant countries and have different cultural backgrounds.
Large language models (LLMs) are illustrative of this disparity. Researchers have shown that many of the most popular multilingual LLMs perform poorly with languages other than English, Chinese, and a handful of other (mostly) European languages. Yet, there are approximately 6,000 languages spoken today, many of them in communities in Africa, Asia, and South America. Arabic alone is spoken by almost 400 million people and Hindi has 575 million speakers around the world.
For example, LLaMA 2 performs up to 50% better in English compared to Arabic, when measured using the LM-Evaluation-Harness framework. Meanwhile, Jais, an LLM co-developed by MBZUAI, exceeds LLaMA 2 in Arabic and is comparable to Meta’s model in English (see table below).
The chart shows that the only way to develop AI applications that work for everyone is by creating new institutions outside the Compute North that consistently and conscientiously invest in building tools designed for the thousands of language communities across the world.
Environments of innovation
One way to design new institutions is to study history and understand how today’s centers of gravity in AI research emerged decades ago. Before Silicon Valley earned its reputation as the center of global technological innovation, it was called Santa Clara Valley and was known for its prune farms. However, the main catalyst was Stanford University, which had built a reputation as one of the best places in the world to study electrical engineering. Over the years, through a combination of government-led investment through grants and focused research, the university birthed countless inventions that advanced computing and created a culture of entrepreneurship. The results speak for themselves: Stanford alumni have founded companies such as Alphabet, NVIDIA, Netflix, and PayPal, to name a few.
Today, like MBZUAI’s predecessor in Santa Clara Valley, we have an opportunity to build a new technology hub centered around a university.
And that’s why I chose to join MBZUAI, the world’s first research university focused entirely on AI. From MBZUAI’s position at the geographical crossroads of East and West, our goal is to attract the brightest minds from around the world and equip them with the tools they need to push the boundaries of AI research and development.
A community for inclusive AI
MBZUAI’s student body comes from more than 50 different countries around the globe. It has attracted top researchers such as Monojit Choudhury from Microsoft, Elizabeth Churchill from Google, Ted Briscoe from the University of Cambridge, Sami Haddin from the Technical University of Munich, and Yoshihiko Nakamura from the University of Tokyo, just to name a few.
These scientists may be from different places but they’ve found a common purpose at MBZUAI with our interdisciplinary nature, relentless focus on making AI a force for global progress, and emphasis on collaboration across disciplines such as robotics, NLP, machine learning, and computer vision.
In addition to traditional AI disciplines, MBZUAI has built departments in sibling areas that can both contribute to and benefit from AI, including human computer interaction, statistics and data science, and computational biology.
Abu Dhabi’s commitment to MBZUAI is part of a broader vision for AI that extends beyond academia. MBZUAI’s scientists have collaborated with G42, an Abu Dhabi-based tech company, on Jais, an Arabic-centric LLM that is the highest-performing open-weight Arabic LLM; and also NANDA, an advanced Hindi LLM. MBZUAI’s Institute of Foundational Models has created LLM360, an initiative designed to level the playing field of large model research and development by publishing fully open source models and datasets that are competitive with closed source or open weights models available from tech companies in North America or China.
MBZUAI is also developing language models that specialize in Turkic languages, which have traditionally been underrepresented in NLP, yet are spoken by millions of people.
Another recent project has brought together native speakers of 26 languages from 28 different countries to compile a benchmark dataset that evaluates the performance of vision language models and their ability to understand cultural nuances in images.
These kinds of efforts to expand the capabilities of AI to broader communities are necessary if we want to maintain the world’s cultural diversity and provide everyone with AI tools that are useful to them. At MBZUAI, we have created a unique mix of students and faculty to drive globally-inclusive AI innovation for the future. By building a broad community of scientists, entrepreneurs, and thinkers, the university is increasingly establishing itself as a driving force in AI innovation that extends far beyond Abu Dhabi, with the goal of developing technologies that are inclusive for the world’s diverse languages and culture.
This content was produced by the Mohamed bin Zayed University of Artificial Intelligence. It was not written by MIT Technology Review’s editorial staff.
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