Quantum Machine Learning: Innovative interface between AI and quantum computing
Research advances at DLR are bringing quantum computing and artificial intelligence a decisive step closer. At the DLR QCI All Hands event in Hamburg, scientists presented three key projects that are exploring the potential of these future technologies. Today, machine learning is computationally intensive in many areas - from logistics and mechanical engineering to autonomous systems. The DLR Institute for AI Safety and Security is investigating how quantum computers can fundamentally improve the efficiency of AI systems.
The projects presented here show the range of research approaches:
· Quant²AI: The project aims to quantify the quantum advantages for AI applications. Suitable quantum algorithms will be identified using quantum-based testing methods. · QuTeNet: In cooperation with the DLR Institute of Quantum Technologies and the Institute of Software Technology, researchers are developing innovative quantum methods. The focus is on the combination of quantum simulation and quantum AI using tensor networks. · NeMoQC: This research approach combines quantum computing with neuromorphic computing concepts. In cooperation with various DLR institutes, novel quantum reservoir computing methods for prediction and optimisation are being investigated.
The interdisciplinary approach is the key to success: the complex challenges of quantum machine learning can only be mastered through close cooperation between different specialist areas.
