The recording of our tech talk at NVIDIA's GTC Silicon Valley 2018 is available on NVIDIA's website:
The abstract for the talk is below:
Machine learning is rapidly advancing the state-of-the-art in algorithm performance for wireless telecommunications systems. Building on our work presented at GTC Silicon Valley, recasting fundamental wireless signal processing problems as data-centric deep learning problems, we present further evidence that learned signal processing algorithms can empower the next generation of wireless systems with significant reductions in power consumption and improvements in density, throughput, and accuracy when compared to the brittle and manually designed systems of today. This talk will introduce the core enabling technologies and fundamental approaches, share our latest work and results in deep learning-based sensing and learned communications, and discuss applications such as 5G and IoT, commercial cyber-threat sensing, and defense RF sensing to illustrate the wide range of fields these technologies will impact over the next several years.
One of our Principal Engineers, Nathan West, gave an invited talk at NEWSDR 2018. The recording of the talk includes our first public disclosure of some of our real-time RF sensing work and learned physical layers. If you're new to the field of deep learning for signal processing and communications, this video is a great way to catch up on the latest scientific advances.
If you are interested in learning more about DeepSig and our solutions, contact us!