Advanced Computing in the Age of AI|Saturday, June 6, 2020
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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.

As mathematical representations of biological intelligence in machines, massive matrix operations have given the world a generation of effective technologies that can outperform humans in many narrow domain areas. The advent of deep learning, CNNs, RNNs, GANs and all of the other permutations of mainstream AI research have imbued real life products and services with sometimes mind-boggling capabilities. Deep learning mimics the functionality of the brain and has seen great success despite disregarding any practical emulation of the structure, or physiology, of the brain.

However, there are also companies designing AI that take inspiration from the physiology of the brain. In the case of neuromorphic hardware engineering, physical neurons are implemented in silicon that compute far more energy-efficient, albeit less performant, spiking neural networks. Vicarious AI’s Recursive Cortical Network is inspired by the computational principles of the human brain, and takes sensory data, mathematics, and biological plausibility into consideration when making decisions. Numenta have been diligently reconstructing the neocortex in an effort to create intelligent sensorim otor systems that can learn, plan, and act.

But what are the advantages of approaching AI in this way? Where might the two approaches converge, or coincide to help overcome technology bottlenecks facing the AI industry?

The Brain Inspired Computing Congress will gather together the critical mass of companies and academics that are developing machine intelligence inspired by the brain, including Vicarious AI, Numenta, Neuralink, Applied Brain Research, OpenAI, Another Brain, BMW, Accenture plus many more… This is the first event that has ever focused on this ecosystem and will look at application areas such as autonomous vehicles, robot arm control and dynamic vision sensing.

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