David Weber, Head of Smart City Zurich, gives an inside look of how Zurich uses tech like AR, AI and digital twins to improve the city’s infrastructure and safety. 

By Liew Ming En
It can be difficult for Ironman to differentiate friend from foe when speeding through the skies. But he can easily do so with the augmented reality (AR) technology inbuilt in his suit, which automatically targets enemies and avoids civilians.

AR in the real world is still a long way away from science fiction films like Ironman, but progress in recent years is revealing use cases in various sectors. In Zurich, for example, AR is used to visualise how planned buildings will look before they are constructed.

David Weber, the Head of Smart City Zurich, shares how Zurich uses tech like AR, AI and digital twins to improve urban planning, increase citizen participation, and better citizen safety.

By Adam Hadhazy,  Stanford University

Stanford researchers have developed an algorithm that may help discern if someone has autism by looking at brain scans. The novel algorithm, driven by recent advances in artificial intelligence (AI), also successfully predicts the severity of autism symptoms in individual patients. With further honing, the algorithm could lead to earlier diagnoses, more targeted therapies, and broadened understanding of autism’s origins in the brain.

The algorithm pores over data gathered through functional magnetic resonance imaging (fMRI) scans. These scans capture patterns of neural activity throughout the brain. By mapping this activity over time in the brain’s many regions, the algorithm generates neural activity “fingerprints.” Although unique for each individual just like real fingerprints, the brain fingerprints nevertheless share similar features, allowing them to be sorted and classified.

As described in a new study published in Biological Psychiatry, the algorithm assessed brain scans from a sample of approximately 1,100 patients. With 82% accuracy, the algorithm selected out a group of patients whom human clinicians had diagnosed with autism.

“Although autism is one of the most common neurodevelopmental disorders, there is so much about it that we still don’t understand,” says lead author Kaustubh Supekar, a Stanford clinical assistant professor of psychiatry and behavioral sciences and Stanford HAI affiliate faculty. “In this study, we’ve shown that our AI-driven brain ‘fingerprinting’ model could potentially be a powerful new tool in advancing diagnosis and treatment.”