After three successful events (two in the US, one in China) we’re delighted to be bringing the AI Hardware Summit to Munich. We’ve been honoured with previous keynote speakers such as Dr. John L. Hennessey, Chairman of Alphabet, Lip-Bu Tan, CEO of Cadence Systems and Naveen Rao, CVP & GM of Intel’s AIPG. Europe is struggling to keep up with developments in machine learning at the same pace as the US and China, where many of the top labs are located and investments are significantly larger. Due to its academic strength in AI, the potential for Europe to catch up in AI research is massive and could add enormous value to its combined economic output. Institutes like the ELLIS Society are working closely with top European academics to enable Europe to perform the best fundamental AI research, but there is still a large gap in GDP investment when compared to the US and China. Given Europe’s strength in automation across industrial, robotics and autonomous vehicles manufacturing, this summit will focus on inference systems in edge computing, connecting these industries through common challenges in systems architecture/engineering. The AI Hardware Summit Europe will bring together key players across the AI hardware ecosystem to promote innovation and adoption of systems & silicon for processing AI.

The Quantum Partnerships Forum focuses on creating and growing key partnerships within the quantum computing ecosystem. The inaugural forum in 2020 will be a virtual event and center around the themes of commercialization and supply chain. Similar to an ‘exchange’ format, forum attendees are expected to fill out profiles in order to increase the effectiveness of networking. The structure and content of the event emphasizes networking and the formation and dynamics of partnerships over product pitches, updates, and industry timelines. More panels and group discussions than presentations.The Quantum Partnerships Forum 2020 will bring together researchers, hardware & systems builders, and equipment manufacturers to discuss design & engineering challenges, technical requirements, and case studies of successful industry partnerships.

The Brain Inspired Computing Congress will bring together the leading start-ups, researchers and multinational companies who are exploring technologies spanning neuromorphic engineering, event-based sensors, brain-inspired algorithms and biologically plausible neural networks. This congress will provide an overview of these technologies in addition to deep-dive sessions on new architectures for neuromorphic chips, event-based sensors, and efforts to create biologically plausible algorithms.The Brain Inspired Computing Congress will focus on the prime applications for brain-inspired technologies including autonomous vehicles, robotic arm control and dynamic vision sensing. Given the scope for ultra-low-power and edge applications, this technology can be used where conventional deep learning methods are not well suited, such as brain-implants, where it is vital to adhere to power and temperature constraints. Therefore, this congress will also openly discuss the overlap and differentiation between applications for conventional deep learning and brain-inspired computing, exploring how these technologies can complement one another.

AI optimization and acceleration so far has mostly been driven by novel hardware innovations. However, recently there have been new products developed by the AI start-up and research communities that operate at the software level in the machine learning technology stack, which reduce training length, inference time, energy consumption and memory usage of AI and machine learning (ML) models.Learning how to benchmark, deploy, and use these tools, as well as scrutinizing existing real-world use-cases is business-critical because these tools disrupt the AI market by: Enhancing the running of ML models on CPUs, therefore, reducing the costs of ownership of AI hardwareImproving the performance of standard AI accelerators (GPUs, FPGAs, DSPs etc.)Helping more data science and machine learning projects get into full productionIncreasing the competitiveness of products in the crowded edge device and IoT marketsThe Software for AI Optimization Summit will demonstrate how to deploy and integrate the latest novel software optimization tools into AI/ML workflows. Consequently, innovators and adopters in data science, machine learning, AI engineering and IoT solutions will uncover new techniques that enable the training and inference of AI and ML models to be faster, more cost-efficient, and still maintain high levels of performance and accuracy.Consequently, you will be ahead of the latest innovations across the ML technology stack enabling you to make informed decisions about strategic partnerships on who to partner with to optimize AI on the cloud and at the edge.