LED Display of incoming Data Through Clothing

All the Information You Need Could Be in Your Pocket

University of Waterloo Cheriton School of Computer Science (Canada)

October 12, 2021

Researchers at the University of Waterloo's Cheriton School of Computer Science in Canada have developed a tool to display basic information from incoming messages to smartphones and other wireless devices by shining it through one’s apparel. The PocketView technology uses light-emitting diode (LED) displays that can serve either as standalone devices or be linked wirelessly to smartphones through Bluetooth. Cheriton's Antony Albert Raj Irudayaraj said the displays show only minimal information, which is "good enough if you're walking or biking, for example, to show basic navigation instruction." Experiments found thin and light-colored fabrics transmit LED light better, while many darker-colored fabrics and denser, patterned weaves are sufficiently transparent to see the lit LEDs underneath, especially indoors.

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Waterloo Develops Faster 5G for IOT

Implications of 5G for broader more effective IOT?

Waterloo Researchers Develop 200X Faster, Low-Cost Network for 5G Connectivity 
International Business Times
Soorya Kiran
August 29, 2019

Researchers at the University of Waterloo in Canada have developed a more affordable and efficient technique to enable 5G wireless connectivity for Internet of Things (IoT) devices. The mmX millimeter wave network delivers multi-gigahertz of unlicensed bandwidth, 200-fold more bandwidth than that allocated to current Wi-Fi and cellular networks. MmX supports a significantly higher bitrate than Wi-Fi and Bluetooth. Said Waterloo's Ali Abedi. "Any sensor you have in your home, which traditionally used Wi-Fi and lower frequency, can now communicate using high-speed millimeter wave networks. Autonomous cars are also going to use a huge number of sensors in them which will be connected through wire; now you can make all of them wireless and more reliable."  ... " 

DarwinAI to Automate AI Development

Another move towards the automating of AI, from U of Waterloo

DarwinAI launches from stealth to automate artificial intelligence development  By Maria Deutscher in SiliconAngle

 Artificial intelligence projects usually rely on existing code. Engineers sift through the AI models available from sources such as academic publications, pick the one deemed most suitable and then customize it to their requirements.

Canada’s DarwinAI Inc. wants to reduce the amount of work involved in the last two steps. The startup today launched from stealth with $3 million in funding and a specialized development platform that promises to automate AI projects.

DarwinAI’s software is based on research conducted by co-founder Alexander Wong at the University of Waterloo, where he serves as a professor with the systems design engineering department. The platform can customize an existing AI for the requirements of an application using its own built-in neural network.

According to DarwinAI, the software works by deriving a series of new models from the original based on user-defined parameters. Engineers can then pick the version with the particular combination of characteristics that best matches their target use case and, if necessary, make further enhancements. The startup said AI models created with its software are not only faster but also considerably more efficient.  ... " 

Getting Your TV to Understand You

Its  the ultimate challenge, understanding complex context.  Good direction.

Understanding in Context   University of Waterloo News

Researchers at the University of Waterloo in Canada, the University of Maryland, and the Comcast Applied AI Research Laboratory have developed a method to improve the voice query understanding capabilities of home entertainment platforms. The method relies on artificial intelligence (AI) technology to achieve the most natural speech-based interaction with TVs to date. The researchers utilized a technique known as hierarchical recurrent neural networks to better model context and improve the system's accuracy. In January, the researchers' neural network model was deployed in production to answer queries from live users, and they found that it handles the majority of highly complicated queries appropriately, greatly enhancing user experience. Waterloo's Jimmy Lin said, "What's special about this approach is that we take advantage of context—such as previously watched shows and favorite channels—to personalize results, thereby increasing accuracy."and is to shoppers in a broader category. ... "