Hartmut Neven: Artificial Intelligence or: Why Google is Building a Quantum Computer
Hartmut Neven (Director of Engineering, Google Quantum Artificial Intelligence Laboratory)
"Artificial Intelligence or: why Google is building a quantum computer" (lecture held in German)
March 8, 2016, 4:15 pm
Anatomy/Pathology Lecture Hall, Albertstraße 19
Mar 08, 2016
from 05:15 PM to 06:30 PM
|Where||Lecture Hall Pathology/Anatomy, Albertstr. 19|
|Contact Name||Anna Blattner|
|Contact Phone||+49 (0)761 203-97362|
öffentlich / open to the public
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Artificial Intelligence: Why Google is building a quantum computer (Lecture held in German)
On March 8, 2016 at 4:15 pm, Hartmut Neven, development manager of the Google Quantum Artificial Intelligence Laboratorium, will give a lecture on “Artificial Intelligence: Why Google is building a quantum computer” (in German). Neven is a leading expert in the fields of: quantum computing, computer vision, robotics and computational neuroscience. He is best known for his work in face- and object recognition and machine learning. Moreover, as one of the former development managers of Google Googles and Co-Founder of the Google Glass project, he is one of the pioneers in the area of visual search technologies. Currently, Neven is working in a team of worldwide leading quantum researchers at the University of California Santa Barbara, as development manager of the Google Quantum Artificial Intelligence Lab. The team is working on the development and improvement of artificial intelligence as well as the enhancement of the processing power of computer systems. As a collaborative project by Google, the US-space agency Nasa and the Universities Space Research Association, a union of more than 100 universities with higher education studies in Aeronautics Research, the team aims to develop and build new quantum information processors.
In his lecture, Neven will talk about the architecture of the processor types: quantumoptimizer (quantum annealer) and quantum circuit. A quantumoptimizer is a promising instrument to find better solutions for difficult combinatory optimization problems. As an example how quantum optimization is used in machine learning, he will demonstrate how a system can profit from heavy noisy training data. His team has used quantum circuit to put a quantum neuronal network into effect. The project has implemented such a network in a first application, in order to identify energies of molecular hydrogen with chemical accuracy. Another common area of application for quantum computers is quantum simulation.
In his talk, Hartmut Neven will explain why quantum computers can accelerate the development of artificial intelligence.