One of the reasons we’re excited to hold a conference in China is that it’s one of the countries where innovation throughout the entire AI hardware and software stack is happening. Deep learning requires big data, big models, and big compute. Thus the right combination of hardware and software infrastructure are essential. If you take a step back, data collection usually involves a host of sensors many of which are equipped with compute resources. While stories in the popular press focus on machine learning, in fact an end-to-end AI application involves many important hardware and software components that need to work seamlessly. With recent global investments in hardware startups, new hardware optimized for AI workloads will be coming in the near future.
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