Ingmar Posner parlando di come tecniche di machine learning può essere utilizzato per realizzare robot che può veramente pensare, sulla tecnologia stadio, a New Scientist Live
5616 x 3744 px | 47,5 x 31,7 cm | 18,7 x 12,5 inches | 300dpi
Data acquisizione:
20 settembre 2018
Ubicazione:
ExCel London
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We are experiencing an AI renaissance. Our imaginations are captured by the widespread adoption of voice assistants, the emergence of self-driving cars and machines that are increasingly beating humans in complex games such as Go. But how much of this progress can readily translate into our everyday lives? As humans, we are uncannily good at solving a variety of complex problems by constant improvisation. Our use of tools is held up as one of the tell-tale signs of intelligence. Our ability to introspect, to know when we don’t know, seems like a fundamental requirement for robustly mastering our everyday lives. In this talk, Ingmar Posner examines recent progress in robotics and artificial intelligence in search of similar introspection and creative problem solving. Ingmar Posner is an associate professor in engineering science at the University of Oxford where he leads the Oxford Applied AI Lab. His work explores core challenges in AI and machine learning to enable robots to robustly and effectively operate in complex, real-world environments. Ingmar and his team explore a number of intellectual challenges at the heart of robot learning, such as machine introspection in perception and decision making, data efficient learning from demonstration and the learning of complex tasks via a set of less complex ones. All the while Ingmar’s intellectual curiosity remains grounded in real-world robotics applications such as autonomous driving, logistics, manipulation and space exploration. In 2014, Ingmar co-founded Oxbotica, a leading provider of mobile autonomy software solutions.
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