In traffic, humans are used to constantly anticipating what will happen next. This reasoning ability is something that today’s self-driving vehicles and AI systems in general are lacking. In a recent study, together with colleagues in Germany and India, Mehul Bhatt has shown that combining modern neural learning with common-sense reasoning can overcome some of the pitfalls ailing self-driving vehicles today. The study was published in the Artificial Intelligence journal (AIJ).
« The developed AI method results in self-driving vehicles learning to understand the world much like humans. With understanding also comes the ability to explain decisions, » says Mehul Bhatt.
As a result, self-driving vehicles can recognize that a cyclist hidden behind a car for a few seconds still exists until it reappears. The approach enables self-driving vehicles to demonstrate a wide range of similar human-like common-sense capabilities. Such capabilities have not been achievable in self-driving vehicles or other AI technologies that are based on machine learning alone.
Comment reconnaître une attaque de phishing et s’en protéger Le phishing ou « hameçonnage »…
Qu’est-ce que la cybersécurité ? Définition, enjeux et bonnes pratiques en 2025 La cybersécurité est…
Cybersécurité : les établissements de santé renforcent leur défense grâce aux exercices de crise Face…
L'IA : opportunité ou menace ? Les DSI de la finance s'interrogent Alors que l'intelligence…
Sécurité des identités : un pilier essentiel pour la conformité au règlement DORA dans le…
La transformation numérique du secteur financier n'a pas que du bon : elle augmente aussi…
This website uses cookies.