System Bits: Nov. 8


Optimizing multiprocessor programs for non-experts While ‘dynamic programming’ is a technique that yields efficient solutions to computational problems in economics, genomic analysis, and other fields, adapting it to multicore chips requires a level of programming expertise that few economists and biologists have. But researchers from MIT’s Computer Science and Artificial Intelligence La... » read more

Should Processing Take Place At End Nodes?


Last week at ARM TechCon — which I found extremely interesting for the deep technical content — there was much discussion around where processing should happen in our connected world. (I’m really trying to stay away from the nebulous term, ‘IoT.’) Some believe the processing should happen at the edge nodes, while others believe it should all take place in the data center; I’ve ev... » read more

Ready For Social Robots?


After years of steady growth, innovation and sometimes disappointment, the robotics market is heating up on several fronts amid some new breakthroughs in the arena. Both the industrial and service robotics markets are hot. In addition, the consumer market is seeing a new level of interest, as the industry is invaded by the next wave of so-called personal assistant robots or social robots for... » read more

System Bits: Nov. 1


There is a lurking malice in cloud hosting services A team of researchers from the Georgia Institute of Technology, Indiana University Bloomington, and the University of California Santa Barbara has found — as part of a study of 20 major cloud hosting services — that as many as 10 percent of the repositories hosted by them had been compromised, with several hundred of the ‘buckets’ act... » read more

Making Waves In Deep Learning


A little more than two and a half years ago I wrote Making Waves in Low-Power Design, an article about a company (at the time) called Wave Semiconductor. Fast forward the the recent Linley Processor Conference, Wave Computing’s CTO Chris Nicol gave the audience an update on the company’s eagerly awaited and soon (planned for October) to be taped-out 16K-core dataflow processor for deep lea... » read more

Building Chips That Can Learn


The idea that devices can learn optimal behavior rather than relying on more generalized hardware and software is driving a resurgence in artificial intelligence, machine leaning, and cognitive computing. But architecting, building and testing these kinds of systems will require broad changes that ultimately could impact the entire semiconductor ecosystem. Many of these changes are wel... » read more

Looking Beyond Technology


The semiconductor industry is beginning to make real progress in deep learning and artificial intelligence, opening up bigger opportunities across more markets than have ever existed in the history of technology. But before this revolution goes much further, the industry also needs to step back and establish a set of guidelines about how this technology will be used. This is an entirely dif... » read more

Uncertainty Rocks Chip Market


The semiconductor industry is undergoing sweeping changes in every direction, making it far more difficult to figure out which path to take next, when to take it, and how to get there. The next few years will redefine which semiconductor companies emerge as leaders, which ones get pushed down or out or absorbed into other companies, and which markets will be the most lucrative. And that coul... » read more

System Bits: June 28


Deep-learning-based virtual reality tool Given that future systems which enable people to interact with virtual environments will require computers to interpret the human hand’s nearly endless variety and complexity of changing motions and joint angles, Purdue University researchers have created a convolutional neural network-based system that is capable of deep learning. [caption id="att... » read more

Decoding The Brain


At the Design Automation Conference this year, Lou Scheffer, principal scientist for the Howard Hughes Medical Institute, gave a visionary talk entitled Learning from Life: Biologically Inspired Electronic Design. Scheffer is an IC design guy who came through Stanford and Caltech and worked for HP and [getentity id="22032" e_name="Cadence"] before switching to the medical field eight years a... » read more

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