The world in all its complexity
Today, the rewards of AI are mostly enjoyed by just a few countries in what the Oxford Web Institute dubs the “Compute North.” These countries, comparable to the US, the U.K., France, Canada, and China, have dominated research and development, and built state-of-the-art AI infrastructure capable of coaching foundational models. This could come as no surprise, as these countries are home to lots of the world’s top universities and huge tech corporations.
But this concentration of innovation comes at a price for the billions of people that live outside these dominant countries and have different cultural backgrounds.
Large language models (LLMs) are illustrative of this disparity. Researchers have shown that lots of the preferred multilingual LLMs perform poorly with languages apart from English, Chinese, and a handful of other (mostly) European languages. Yet, there are roughly 6,000 languages spoken today, lots 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 globe.
For instance, LLaMA 2 performs as much as 50% higher in English in comparison with 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 one solution to develop AI applications that work for everyone seems to be by creating latest institutions outside the Compute North that consistently and conscientiously spend money on constructing tools designed for the 1000’s of language communities internationally.
Environments of innovation
One solution to design latest institutions is to check history and understand how today’s centers of gravity in AI research emerged a long time ago. Before Silicon Valley earned its repute as the middle of world technological innovation, it was called Santa Clara Valley and was known for its prune farms. Nevertheless, the principal catalyst was Stanford University, which had built a repute as probably the greatest places on the earth to check electrical engineering. Through the years, through a mix of government-led investment through grants and focused research, the university birthed countless inventions that advanced computing and created a culture of entrepreneurship. The outcomes speak for themselves: Stanford alumni have founded corporations comparable to Alphabet, NVIDIA, Netflix, and PayPal, to call just a few.
Today, like MBZUAI’s predecessor in Santa Clara Valley, we’ve a chance to construct a brand new technology hub centered around a university.
And that’s why I selected to affix MBZUAI, the world’s first research university focused entirely on AI. From MBZUAI’s position on the geographical crossroads of East and West, our goal is to draw the brightest minds from around the globe and equip them with the tools they should push the boundaries of AI research and development.
