DeepSig to Speak at NVIDIA GTC DC 2018

DeepSig to Speak at NVIDIA GTC DC 2018

We will be presenting at NVIDIA's GPU Technology Conference (GTC) DC 2018, which is taking place October 22nd - 24th in Washington D.C. Building on the work presented in our GTC Silicon Valley 2018 Talk, and expanded upon in an article featured by NVIDIA, we will be presenting "Deep Learning for RF Sensing and Communications". Information about the talk can be found on the NVIDIA GTC DC 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.

If you'll be at GTC DC and are interested in chatting, please send us a note at info@deepsig.io! We would love to meet up at the conference or host you in our offices just outside of D.C. while you're in town.

Virginia Tech partners with startup DeepSig to protect wireless devices

Technology invented at Virginia Tech that harnesses a new area of artificial intelligence to improve wireless performance and defend wireless devices has taken a major step toward the public market.

The university and an Arlington-based start-up, DeepSig, recently executed a licensing agreement that allows the company to further develop for consumer use the innovative wireless communications and cybersecurity technology invented by researchers at Virginia Tech’s Hume Center for National Security and Technology.

“This technology leverages a field of artificial intelligence called machine learning in a new way in order to design a next generation of powerful wireless communications systems,” said Virginia Tech researcher and DeepSig founder Tim O’Shea. “It will be faster, more cost efficient, more secure, and easier to deploy than today’s wireless systems.”

Read More at vt.edu

NVIDIA DevBlog Post on Deep Learning for Wireless Communications

The complexity of wireless system design is continually growing. Communications engineering strives to further improve metrics like throughput and interference robustness while simultaneously scaling to support the explosion of low-cost wireless devices. These often-competing needs makes system complexity intractable. Furthermore, algorithmic and hardware components are designed separately, then optimized, and integrated to form complete systems. This approach makes globally optimizing the end-to-end communications link extremely difficult, if not impossible.

DeepSig overcomes this complexity barrier by designing neural networks that learn how to effectively communicate, even under harsh impairments. To accomplish this, we leverage our background in radio and signal processing, recent developments in deep learning, and technology from NVIDIA such as GPU hardware and software libraries optimized for machine learning. Our work in learned communications demonstrates that machines easily match the performance of human-designed systems in simple scenarios, as shown in Figure 1. In more complex scenarios, a deep learning-based system can dramatically outperform existing approaches by learning a physical layer (PHY) inherently optimized for the radio hardware and channel.

Read more on the NVIDIA blog post

DeepSig's GTC Silicon Valley 2018 Talk Recording

The recording of our tech talk at NVIDIA's GTC Silicon Valley 2018 is live! You can view it here on NVIDIA's website: http://on-demand.gputechconf.com/gtc/2018/video/S8791/

This talk, delivered by DeepSig co-founder and CTO Tim O'Shea, provides an introduction to RF sensing and learned physical layers - the two core technologies underpinning DeepSig's product line. For a deeper dive on these topics, see our scientific publications.

DeepSig's NEWSDR 2018 Recorded Talk

One of our Principal Engineers, Nathan West, gave an invited talk at NEWSDR 2018 in March of this year. The recording of the talk just went live, and 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.