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In some interesting news last month, latest research from the Massachusetts Institute of Technology (MIT) has demonstrated that ‘blind spots’ in the artificial intelligence (AI) of self-driving cars could be adjusted and redressed using input from humans. The Massachusetts Institute of Technology team in collaboration with Microsoft, developed an ingenious model where AI learns any changes in behaviour it needs to make as it observes the human under the scenario. In order for this to be achieved, they make sure the AI system is put through simulation training before putting a human through the same scenario in the real world hence allowing it to pick up on visual and reactive signals by humans to accordingly amend its behaviour in similar circumstances. So far, the system has only been tested in video games but nonetheless study author (and  graduate student in MIT’s computer science and artificial intelligence lab) Ramya Ramakrishnan, said:…

..to new emerging mobility services and platforms The evolution of transportation, in similar fashion to humankind evolution, has gone through trials and tribulations as it has evolved through time. The world is ever-changing, at a faster pace than ever before and with increasing mobility demand and evolving mobility needs, transport providers of all kinds (private cars or other means of transport such as buses and train lines) have to satisfy demand for services that are increasingly convenient, fast and predictable. Changes in consumer habits in recent years demonstrate that some users are prepared to sacrifice individual forms of mobility, such as the private car, in favour of other modes of transport that offer these features. This has led to the successful introduction and rapid penetration of new mobility solutions. Meanwhile, traditional mobility ecosystems have diversified, employing a wider array of actors, and the emergence of new concepts, such as Mobility-as-a-Service (MaaS), have forced them to re-organize interactions…