AI/ML functions are moving to the edge to save power and reduce latency. This enables local processing without the overhead of transmitting large volumes of data over power hungry and slow communication links to servers in the cloud. Of course, the cloud offers high performance and capacity for processing the workloads. Yet, … Read More
Last month, eMemory Technology hosted a webinar titled “eMemory’s Embedded Logic-NVM Solution for AI Chips.” While the purpose was to present their embedded Logic-NVM solution, the webinar nicely sets the stage by highlighting Analog NVM’s value as it relates to neural networks. Of course, the algorithms of neural networks… Read More
During the week of April 19th, Linley Group held its Spring Processor Conference 2021. The Linley Group has a reputation for convening excellent conferences. And this year’s spring conference was no exception. There were a number of very informative talks from various companies updating the audience on the latest research and… Read More
It is long past the time when general purpose processors could meet the needs of sensor fusion. Sensor fusion performs operations to process and integrate raw sensor data so that downstream processing is simplified and is performed at a higher level. When done properly it offers several other significant benefits such as lower… Read More
Wally Rhines is President and CEO of Cornami, Inc., a company named for its “tsunami of cores”. The company has developed a “TruStream” programming environment that generates independent executable streams of data and control. They have also designed a chip that provides the computational fabric for multi-core execution of… Read More
In all the hubbub about AI/ML, it’s easy to see why visual ML gets more attention. It’s got appeal because of applications such as autonomous driving. Because of this it’s easy to overlook the importance of audio ML. I own a Tesla and putting it into autopilot is very cool, but even it has voice recognition built in as an important feature… Read More
Machine Learning (ML) has become extremely important for many computing applications, especially ones that involve interacting with the physical world. Along with this trend has come the development of many specialized ML processors for cloud and mobile applications. These chips work fine in the cloud or even in cars or phones,… Read More
In early May of this year, eSilicon announced the tape-out of a test chip which included the latest additions to its neuASIC™ IP platform. At the upcoming Hot Chips Symposium to be held at Stanford on August 19 and 20, 2019, eSilicon will be demonstrating the software component of this AI-enabling IP platform. At the event, eSilicon… Read More
Security and machine learning (ML) are among the hottest areas in tech, especially for the IoT. The need for higher security is, or should be, blindingly obvious at this point. We struggle to fend off daily attacks even in our mainstream compute and networking environment. How defenseless will we be when we have billions of devices… Read More
Machine learning-based applications have become prevalent across consumer, medical, and automotive markets. Still, the underlying architecture(s) and implementations are evolving rapidly, to best fit the throughput, latency, and power efficiency requirements of an ever increasing application space. Although ML is … Read More
