Speaker
Description
In light of emergent evolution in quantum technology, key industrial players allocate significant parts of their budget and resources to identify a real-world problem where quantum advantage, i.e. exponential increase in computational capacity, is expected to appear. The tense competition between quantum computing and simulations on classical hardware over the past decades has been further accelerated by the sever need to develop cost-effective technologies to manipulate things on the atomic and nano scale and control processes that could lead to new products to improve everybody’s life. Currently, Graphics Processing Units (GPUs) accelerated hardware provide unprecedented computational power leading to paradigmatic changes in various business cases. In this contribution, we will overview a class of quantum-inspired algorithms which increase the efficiency of classical computing algorithms without requiring any quantum hardware, and which at the same time are also capable to fully utilize state-of-the-art classical hardware available on high performance computing infrastructures. We will show-case recent results achieved in collaboration with NVIDIA, IBM and Google startup SandboxAQ also addressing important questions like scalability, energy demand and sustainability. Key aspects of transferring academic research to industrial world as part of productization will also be addressed. Finally, we argue that for such Blue Ocean Strategy the required technology is around us, thus raising related R&D to a professional stage would revolutionize future technologies in image recognition, data process, and AI among many others, and open entire new development directions in pharma industry, materials science and beyond.