GDDR6 PHYs: From The Data Center To Self-Driving Cars


The demand for ever-increasing bandwidth has resulted in a growing interest in GDDR across a number of market verticals, including data centers and the automotive sector. As an example of the former, deep learning applications require ever-increasing speed and bandwidth memory solutions in the data center. In deep learning and other emerging technologies, GDDR memory can help companies addre... » read more

Deep Learning Spreads


Deep learning is gaining traction across a broad swath of applications, providing more nuanced and complex behavior than machine learning offers today. Those attributes are particularly important for safety-critical devices, such as assisted or autonomous vehicles, as well as for natural language processing where a machine can recognize the intent of words based upon the context of a convers... » read more

Babblelabs: Deep Learning Speech Processing


Pronounced “babble labs,” a startup that is the brainchild of serial entrepreneur [getperson id="11244" comment="Chris Rowen"] is setting out to transform speech processing and will leverage deep learning to do so. Rowen, CEO of Babblelabs, has spoken for some time about move of processing to more general purpose hardware, with applications layered on top, so it’s not so surprising his... » read more

System Bits: Jan. 2


Robots imagine their future to learn By playing with objects and then imagining how to get the task done, UC Berkeley researchers have developed a robotic learning technology that enables robots to figure out how to manipulate objects they have never encountered before. The team expects this technology could help self-driving cars anticipate future events on the road and produce more intel... » read more

System Bits: Dec. 5


[caption id="attachment_429586" align="aligncenter" width="300"] Vivienne Sze, an associate professor of electrical engineering and computer science at MIT. Source: MIT[/caption] Building deep learning hardware A new course at MIT is bringing together both electrical engineering and computer science to educate student in the highly sought after field of deep learning. Vivienne Sze, an assoc... » read more

The Week in Review: IoT


Products/Services At this week’s AWS re:Invent conference in Las Vegas, Nevada, Amazon Web Services introduced a number of products and services for the Internet of Things, machine learning, and other areas. These include Amazon FreeRTOS (an operating system for IoT microcontrollers), AWS IoT Device Defender (security management), AWS IoT 1-Click, AWS IoT Device Management, AWS IoT Analytics... » read more

One-On-One: Mike Muller


Arm CTO Mike Muller sat down with Semiconductor Engineering to discuss a wide range of technology and market shifts, including the impact of machine learning, where new market opportunities will show up and how the semiconductor industry will need to change to embrace them. What follows are excerpts of that conversation. SE: It's getting to the point where instead of just developing chips, w... » read more

Power/Performance Bits: Nov 28


Deep learning to detect nuclear reactor cracks Inspecting nuclear power plant components for cracks is critical to preventing leaks, as well as to control in maintenance costs. But the current vision-based crack detection approaches are not very effective. Moreover, they are prone to human error, which in the case of nuclear power can be disastrous. To address this problem, Purdue Universit... » read more

System Bits: Nov. 21


MIT-Lamborghini to develop electric car Members of the MIT community were recently treated to a glimpse of the future as they passed through the Stata Center courtyard as the Lamborghini Terzo Millenio (Third Millennium) was in view, which is an automobile prototype for the third millennium. [caption id="attachment_429209" align="alignnone" width="300"] Lamborghini is relying on MIT to make i... » read more

Software Framework Requirements For Embedded Vision


Deep learning techniques such as convolutional neural networks (CNN) have significantly increased the accuracy—and therefore the adoption rate—of embedded vision for embedded systems. Starting with AlexNet’s win in the 2012 ImageNet Large Scale Visual Recognition Challenge (ILSVRC), deep learning has changed the market by drastically reducing the error rates for image classification and d... » read more

← Older posts Newer posts →