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MIT and Microsoft Can Detect The Blind Spots in AI for Self-driving Cars

MIT and Microsoft Can Detect The Blind Spots in AI for Self-driving Cars

The Artificial Intelligence of the Self-driving cars is still not right and in the development phase. Such vehicles are prone to make mistakes as there is a lot to learn from different situations. Also, the blind spots are hazardous for any of the Driverless car. Now, the recent studies done by Microsoft and MIT suggest that both of the entities can help detect the Blind Spots in the AI based car and improve the obstacles detection for safer driving. The MIT and Microsoft’s Module can help identify the blind spots which are just the gaps in the knowledge for Driverless car makers.

Using this module, the driverless car AI can learn from the human counterpart on how to act in certain situations. For example, the AI can learn how to make way for the ambulance by determining for the human drivers with the module developed by Microsoft and MIT. Even if anything goes sour with the AI like technical difficulties, the human counterparts can take over the car and drive it safely to the destination to avoid issues with the blind spots.

The field of Driverless cars is not mature yet as the AI can become overconfident and the processing lag might have a negative impact. That’s why learning phase which is dubbed as the blind spot for the cars is critical. The AI learning in real-time is essential to understand which one is the appropriate response assessing the nearby situations. As this module from MIT and Microsoft is still on paper, they need a practical test on the driverless cars to see if the AI can learn from the other drivers and react according to the situation.

William Thomas

William is a research analyst and he is a tech expert and healthcare industry editor. He has been working for the news industry for over five years. Michael has been a leading news writer in his career. He is keen in helping people with respect to online marketing via the skillful content he provides.


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