Collaborating Authors


The future of AI research is in Africa


Sitting in a hotel lobby in Tangier, Morocco, Charity Wayua laughs as she recounts her journey to the city for a conference on technology and innovation. After starting her trip in Nairobi, Kenya, where she leads one of IBM's two research centers in Africa, she had to fly past her destination for a layover in Dubai, double back to Casablanca, and then take a three-and-a-half-hour drive to Tangier. What would have been a seven- to eight-hour direct flight was instead a nearly 24-hour odyssey. This is not unusual, she says. The hassle of traveling within the region isn't the only thing making things difficult for Africa's research community: the difficulty of traveling out of the region has often left its researchers out of the international conversation.

Artificial Intelligence in Morocco: 'Not Just for Silicon Valley'


Rabat – At a July 20 McKinsey & Company conference in Morocco, a presentation on artificial intelligence algorithms highlighted the powerful potential of digitizing sectors of Morocco's economy. The global management consulting firm, which specializes in digital transformation, hosted the conference "Potential of Digital and Artificial Intelligence (AI)" this past Friday. Casablanca Sector General Manager Jalil Bensouda and his associate Yassine Sekkat emphasized in their presentation the possibilities of dynamic digital incorporation in Morocco. "The 20th century Grail was oil. The 21st is the data," Bensouda declared.

From Data to the p-Adic or Ultrametric Model Machine Learning

We model anomaly and change in data by embedding the data in an ultrametric space. Taking our initial data as cross-tabulation counts (or other input data formats), Correspondence Analysis allows us to endow the information space with a Euclidean metric. We then model anomaly or change by an induced ultrametric. The induced ultrametric that we are particularly interested in takes a sequential - e.g. temporal - ordering of the data into account. We apply this work to the flow of narrative expressed in the film script of the Casablanca movie; and to the evolution between 1988 and 2004 of the Colombian social conflict and violence.

The Structure of Narrative: the Case of Film Scripts Artificial Intelligence

We analyze the style and structure of story narrative using the case of film scripts. The practical importance of this is noted, especially the need to have support tools for television movie writing. We use the Casablanca film script, and scripts from six episodes of CSI (Crime Scene Investigation). For analysis of style and structure, we quantify various central perspectives discussed in McKee's book, "Story: Substance, Structure, Style, and the Principles of Screenwriting". Film scripts offer a useful point of departure for exploration of the analysis of more general narratives. Our methodology, using Correspondence Analysis, and hierarchical clustering, is innovative in a range of areas that we discuss. In particular this work is groundbreaking in taking the qualitative analysis of McKee and grounding this analysis in a quantitative and algorithmic framework.